diff --git a/campaigns.yaml b/campaigns.yaml
index d4467c9..6d7deab 100644
--- a/campaigns.yaml
+++ b/campaigns.yaml
@@ -58,18 +58,13 @@ campaigns:
   title: Linear-solver accuracy and cost
   status: active
   updated: '2026-10-08'
-  next: 'Phase 4a MERGED 2026-10-08 (autolens_profiling#398, fe9ca472; issue #397 closed; A100 job 399050): the A100-only
-    jacobi batched/unbatched difference is deterministic batch-shape-dependent Cholesky rounding (cho_factor/cho_solve differ
-    on 50/50 lanes from initialize at ~1e-15), amplified to order one within 1-2 iterations on the 24 Jacobi-unstable lanes
-    (all 20 of the 3a divergence set); not nondeterminism (deterministic-ops flag bit-identical), not a vmap defect; controls
-    pdip_raw <= 1.3e-13, certified <= 3.4e-12. Wiki wiki/research/jacobi_a100_batched_divergence.md with the decision table
-    (B ruled out, C unlikely, A or D need a Mapper corpus). Human chose option 2 (bounded evidence step): phase 5 Mapper
-    corpus ISSUED as #399 (delaunay_hst, rectangular_hst, slam_mixed_hst, optional interferometer_delaunay; accuracy,
-    timing and divergence cells; one authorized A100 job). Phase 5 delivered (PR #400, A100 job 399225): Jacobi converged 24/24 Mapper/mixed systems, 0 batch-sensitive lanes;
-    raw+polish 1.05-1.62x Jacobi cost. DECISION 2026-10-08 (decisions/linear-solver-mapper-default-jacobi.md): keep Jacobi
-    as the Mapper default, raw+polish for MGE-only, no library change. Next: /prm on the re-landed phase-5 PR (corpus out
-    of git, human choice); then close the programme in the task.'
-  evidence: https://github.com/PyAutoLabs/autolens_profiling/blob/fe9ca472/wiki/research/jacobi_a100_batched_divergence.md
+  next: 'Programme question CLOSED by decision 2026-10-08 (decisions/linear-solver-mapper-default-jacobi.md): keep Jacobi as
+    the Mapper default, raw+polish for MGE-only, no library change. Phase 5 merged as autolens_profiling#401 (766f8202; #400
+    superseded, corpus files out of git with sha256 + regenerate in the manifest, copies on RAL and the laptop); phases 3a/3b/4a
+    merged earlier (#394, #396, #398). Open evidence gaps, not tasks: wide-prior Mapper vectors, an interferometer corpus,
+    the n~1500 CPU batched/unbatched 4e-13 difference, rectangular criterion-2 failures. Campaign stays active for the
+    release re-runs of the solver cells; nothing issued.'
+  evidence: https://github.com/PyAutoLabs/PyAutoPulse/blob/main/decisions/linear-solver-mapper-default-jacobi.md
 - id: imaging
   title: Production imaging and likelihood breakdown
   status: active
@@ -207,17 +202,14 @@ tasks:
 - id: mge_nnls_fix_pyautoarray_571_slam_60
   campaign: linear-solver
   title: 'Linear-solver programme phase 3: GPU/vmap/A100 timing and parity rows for the solver corpus'
-  status: active
+  status: complete
   priority: medium
   path: tasks/mge_nnls_fix_pyautoarray_571_slam_60.md
   updated: '2026-10-08'
   issue: https://github.com/PyAutoLabs/autolens_profiling/issues/399
-  next: 'Phases 3a/3b/4a merged (#394, #396, #398; Mind records complete/2026/10/linear-solver-p3a-a100-parity.md,
-    linear-solver-p3b-gpu-timing.md, linear-solver-p4a-jacobi-a100-divergence.md). Phase 5 Mapper corpus issued as #399
-    (Mind active/linear_solver_phase5_mapper_corpus.md, worktree linear-solver-p5-mapper-corpus, Opus executing). Task
-    stays active until the re-landed phase-5 PR is merged. Decision taken 2026-10-08: keep Jacobi for Mapper, raw+polish
-    for MGE-only (decisions/linear-solver-mapper-default-jacobi.md).'
-  evidence: https://github.com/PyAutoLabs/autolens_profiling/pull/398
+  next: 'Complete 2026-10-08: phases 3a (#394), 3b (#396), 4a (#398) and 5 (#401) merged; Mind records complete/2026/10/linear-solver-p{3a-a100-parity,3b-gpu-timing,4a-jacobi-a100-divergence,5-mapper-corpus}.md.
+    Human decision recorded in decisions/linear-solver-mapper-default-jacobi.md. Revisit conditions live there; no follow-up issued.'
+  evidence: https://github.com/PyAutoLabs/autolens_profiling/pull/401
 - id: autofit_profiling_bootstrap
   campaign: autofit
   title: 'autofit_profiling: bootstrap the repo + general PyAutoFit profiling epic'
diff --git a/dashboard.html b/dashboard.html
index 051ae77..c4fdab3 100644
--- a/dashboard.html
+++ b/dashboard.html
@@ -645,7 +645,7 @@
 Work on GitHub:
 - PyAutoPulse: https://github.com/PyAutoLabs/PyAutoPulse
 - autolens_profiling: https://github.com/PyAutoLabs/autolens_profiling</textarea></details><div class="orchestration-freshness" data-freshness="grey"><details data-freshness-stamp data-refreshed-at="2026-10-08T12:50:11Z"><summary><span data-freshness-label>Last updated 2026-10-08 12:50:11 UTC</span></summary><time datetime="2026-10-08T12:50:11Z">2026-10-08 12:50:11 UTC</time></details><a data-refresh-link href="https://github.com/PyAutoLabs/PyAutoPulse/actions/workflows/dashboard_refresh.yml" title="Open the dashboard refresh controls">↻ Update</a></div></div><p class="orchestration-status" role="status" aria-live="polite"></p></section>
-<nav class="board-nav" aria-label="Board sections"><a class="board-nav-card" href="#campaigns"><span class="board-nav-label">Active campaigns</span></a><a class="board-nav-card" href="#evidence"><span class="board-nav-label">Profiling Results</span></a><a class="board-nav-card" href="#decision-history"><span class="board-nav-label">Decision History</span></a></nav><main><!-- pulse-campaigns:5561dbba1d4ce4ed1c8800f397a77dd99346300db80e0872771e47492295f923 --><details class="board-section"><summary><h2 id="campaigns">Active campaigns</h2></summary><div class="board-section-body"><div class="campaign-table"><table><thead><tr><th>Campaign</th><th>Status</th><th>Links</th></tr></thead><tbody><tr><td><strong>Setup baseline collection and scientific acceptance</strong><details id="campaign-setup-baseline" class="campaign-detail"><summary>1 task · next step</summary><p>Specification merged as draft v1 (autolens_profiling#385, 2026-10-06; issue #384 closed). Six unknowns remain: no frozen revisions/env lock; no collection authorization/window; hardware/affinity identity unselected; each cell needs complete settings, input hashes, witness + tolerances; compile per-cell builder unavailable; proposed fp64/mixed coverage is not evidence of support. Human freezes the manifest before separately authorizing collection.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/setup_baseline_campaign.md">Freeze the setup baseline specification, then collect and review evidence</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/384" aria-label="Issue for Freeze the setup baseline specification, then collect and review evidence" title="Issue">↗</a></h4><p class="review-meta">needs-decision · high</p><p>Specification merged as draft v1 (autolens_profiling#385, 2026-10-06). Human resolves the six recorded unknowns and freezes the specification; collection requires separate compute authorization. The report prepares evidence for human scientific review and never promotes baselines. CPU production arrays use ral only.</p></article></details></td><td><span class="pill">needs-decision</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/setup_baseline.md" aria-label="Evidence for Setup baseline collection and scientific acceptance" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-setup-baseline" data-open="campaign-setup-baseline" aria-label="Tasks for Setup baseline collection and scientific acceptance" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Point-source image plane · CPU</strong><details id="campaign-point-source-image-cpu" class="campaign-detail"><summary>1 task · next step</summary><p>Phases 1–4 shipped; completion evidence merged (autolens_profiling#373, 2026-10-04). Closing the epic is the human&#x27;s call. Owed leftovers (RAL cleanup, test move, register_model grad-zero prompt, CI smoke cells, constant_folding A/B, nopad deletion, quiet re-runs) are in the Mind draft point_source_cpu_campaign_owed_leftovers.md. RAL leftover folders not re-listed 2026-10-07 (unverified).</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/pointsolver_cpu_speed_campaign_remainder.md">Point-source (single-source) CPU campaign — carried leftovers and completion evidence</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/370" aria-label="Issue for Point-source (single-source) CPU campaign — carried leftovers and completion evidence" title="Issue">↗</a></h4><p class="review-meta">ready · low</p><p>Completion evidence merged (autolens_profiling#373, 2026-10-04). Still owed, via Mind draft draft/maintenance/autolens/point_source_cpu_campaign_owed_leftovers.md: RAL cleanup, test move, register_model grad-zero prompt, CI smoke cells, constant_folding A/B, nopad deletion, quiet re-runs.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/results/notes/point_source_cpu_campaign.md#campaign-completion-evidence-2026-10-04" aria-label="Evidence for Point-source image plane · CPU" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-point-source-image-cpu" data-open="campaign-point-source-image-cpu" aria-label="Tasks for Point-source image plane · CPU" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Point-source image plane · A100</strong><details id="campaign-point-source-image-gpu" class="campaign-detail"><summary>1 task · next step</summary><p>Phase 0+1 shipped. Forward-mode gradient NaN (PyAutoLens#767) fixed by PyAutoLens#768 (merged 2026-10-04) and released in 2026.10.7.1 (correctness). Remaining human decision: authorize the autolens_inference image-plane fit measurement. Heart unit-test timing rose on the rewritten #768 test file; not a controlled cost comparison (gradient_cost_probe is the instrument).</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/point_source_image_plane_gpu_breakdown.md">Point-source A100 speed-up campaign: profile and optimize with the shared breakdown</a><a class="icon-link" href="https://github.com/PyAutoLabs/PyAutoLens/issues/767" aria-label="Issue for Point-source A100 speed-up campaign: profile and optimize with the shared breakdown" title="Issue">↗</a></h4><p class="review-meta">needs-decision · high</p><p>Forward-mode NaN (PyAutoLens#767) closed: fixed by PyAutoLens#768 (merged 2026-10-04, 0659903d4), released in 2026.10.7.1. The autolens_inference image-plane fit measurement still awaits human authorisation.</p></article></details></td><td><span class="pill">needs-decision</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/point_source_gpu_breakdown.md" aria-label="Evidence for Point-source image plane · A100" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-point-source-image-gpu" data-open="campaign-point-source-image-gpu" aria-label="Tasks for Point-source image plane · A100" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Point-source source plane</strong><details id="campaign-point-source-source" class="campaign-detail"><summary>2 tasks · next step</summary><p>Core complete; parked. Nautilus leaf autolens_inference#17 merged 2026-10-02; no gradient-sampler leaf yet, so Blackjax stays parked (admission not met). Warm-up task option (a) merged as autolens_profiling#374 (2026-10-04); imaging cells and a release sweep remain.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/runtime_cell_single_jit_gpu_warmup.md">Runtime cells&#x27; A100 `single_jit` includes the post-compile warm-up — source-plane 0.642 ms vs a steady 0.267 ms on the same node</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/371" aria-label="Issue for Runtime cells&#x27; A100 `single_jit` includes the post-compile warm-up — source-plane 0.642 ms vs a steady 0.267 ms on the same node" title="Issue">↗</a></h4><p class="review-meta">active · low</p><p>Option (a) merged (autolens_profiling#374, 2026-10-04): full_pipeline_single_jit_median_ms (p10/p90) beside unchanged single_jit; GPU headline labelled &quot;first block after compile&quot;. Imaging release-sweep cells not wired. No release sweep on main yet (results/ commits since 2026-10-04: #375 streaming rows, a README refactor), so the new field has no sweep rows.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/point_source_source_plane_chi_squared_speed.md">Point-source source-plane chi-squared speed-up campaign — remaining candidates (phases 1–2e shipped)</a></h4><p class="review-meta">blocked · low</p><p>Still blocked: gradient-sampler admission not met (autolens_inference has only the Nautilus source-plane leaf, #17 merged 2026-10-02). Blackjax stays parked.</p></article></details></td><td><span class="pill">parked</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/point_source_source_plane.md" aria-label="Evidence for Point-source source plane" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-point-source-source" data-open="campaign-point-source-source" aria-label="Tasks for Point-source source plane" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Cluster PointSolver robustness and performance</strong><details id="campaign-cluster-pointsolver" class="campaign-detail"><summary>2 tasks · next step</summary><p>Unchanged since 2026-09-27; nothing issued or claimed. Wiki still points at the removed Mind draft (now Pulse tasks/). Pick one bounded phase: observable-overflow invalid-result policy + CI witness, or a representative-data baseline cell.</p><span class="review-meta">Reviewed 2026-10-04</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/cluster_pointsolver_speed.md">Cluster PointSolver — robustness, analysis settings and performance</a></h4><p class="review-meta">ready · normal</p><p>Unissued, no claim. Pick one bounded phase per Mind epics.md: observable-overflow invalid-result policy + CI witness, or a representative-data baseline cell.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/point_solver_profiling_cells.md">PointSolver profiling cells: lensed quasar → cluster runtime tier → single/multi-source → multiplane</a></h4><p class="review-meta">ready · normal</p><p>Unissued, no claim. Candidate first cell: a representative-data cluster likelihood_runtime baseline (single-source preset).</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/a93f37a7ade16fcb7673a7777dfde505183728ed/wiki/campaigns/cluster_pointsolver.md" aria-label="Evidence for Cluster PointSolver robustness and performance" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-cluster-pointsolver" data-open="campaign-cluster-pointsolver" aria-label="Tasks for Cluster PointSolver robustness and performance" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Interferometer likelihood and streaming</strong><details id="campaign-interferometer" class="campaign-detail"><summary>4 tasks · next step</summary><p>Decision matrix complete: last cell merged (autolens_profiling#372, 2026-10-04; 1.59e-3 nat CPU/A100 gap accepted by the human). Streaming scaling phase 1 CPU rows merged (#375); 1e8 CPU and A100 rows need compute authorization. fnnls memo back-off released in 2026.10.7.1 (PyAutoArray#615); the #332 after-measurement is owed. Curvature preload and W~ FFT tasks unstarted.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_fixed_mapper_curvature_preload.md">Interferometer fixed-mapper searches: reuse the W~ curvature matrix across likelihood calls via `preloads.curvature_matrix`</a></h4><p class="review-meta">ready · normal</p><p>Phase 1 Mind draft (2026-10-04) still unstarted; run it through start_dev. Human science call first - no production SLaM stage holds the mapper fixed today.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_nnls_memo_scattered_stream_guard.md">fnnls warm-start memo: stop it slowing scattered evaluation streams (interferometer CPU, autolens_profiling#332)</a><a class="icon-link" href="https://github.com/PyAutoLabs/PyAutoArray/issues/613" aria-label="Issue for fnnls warm-start memo: stop it slowing scattered evaluation streams (interferometer CPU, autolens_profiling#332)" title="Issue">↗</a></h4><p class="review-meta">active · medium</p><p>Library half shipped: PyAutoArray#615 (closes #613) merged 2026-10-06, in 2026.10.7.1. Local solver-only witness (n=576): iid memo on/off 1.49x → 1.17x; walk 0.18x unchanged. Owed: re-run the autolens_profiling#332 ALMA Delaunay 2.17x after-measurement (needs compute authorization).</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_streaming_scaling.md">Campaign: interferometer streaming (array-free) vs in-memory — memory and time scaling to 2e8 visibilities</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/368" aria-label="Issue for Campaign: interferometer streaming (array-free) vs in-memory — memory and time scaling to 2e8 visibilities" title="Issue">↗</a></h4><p class="review-meta">active · high</p><p>Phase 1 CPU cells + results/streaming_scaling rows merged (autolens_profiling#375, 2026-10-04); wiki/campaigns/interferometer_streaming.md. Optional: 1e8 CPU row and A100 rows (compute authorization). Library candidate unfiled: chunk transformer.image_from in apply_sparse_operator (memory).</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_w_tilde_fft_size_levers.md">Interferometer W~ curvature matrix is FFT-bound on the mask extent: pruned padded FFT and real-space pixel scale on the A100</a></h4><p class="review-meta">ready · normal</p><p>Unstarted (no PR/issue/branch/results, 2026-10-04). Select one bounded step when prioritised.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/interferometer_likelihood.md" aria-label="Evidence for Interferometer likelihood and streaming" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-interferometer" data-open="campaign-interferometer" aria-label="Tasks for Interferometer likelihood and streaming" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Linear-solver accuracy and cost</strong><details id="campaign-linear-solver" class="campaign-detail"><summary>1 task · next step</summary><p>Phase 4a MERGED 2026-10-08 (autolens_profiling#398, fe9ca472; issue #397 closed; A100 job 399050): the A100-only jacobi batched/unbatched difference is deterministic batch-shape-dependent Cholesky rounding (cho_factor/cho_solve differ on 50/50 lanes from initialize at ~1e-15), amplified to order one within 1-2 iterations on the 24 Jacobi-unstable lanes (all 20 of the 3a divergence set); not nondeterminism (deterministic-ops flag bit-identical), not a vmap defect; controls pdip_raw &lt;= 1.3e-13, certified &lt;= 3.4e-12. Wiki wiki/research/jacobi_a100_batched_divergence.md with the decision table (B ruled out, C unlikely, A or D need a Mapper corpus). Human chose option 2 (bounded evidence step): phase 5 Mapper corpus ISSUED as #399 (delaunay_hst, rectangular_hst, slam_mixed_hst, optional interferometer_delaunay; accuracy, timing and divergence cells; one authorized A100 job). Phase 5 delivered (PR #400, A100 job 399225): Jacobi converged 24/24 Mapper/mixed systems, 0 batch-sensitive lanes; raw+polish 1.05-1.62x Jacobi cost. DECISION 2026-10-08 (decisions/linear-solver-mapper-default-jacobi.md): keep Jacobi as the Mapper default, raw+polish for MGE-only, no library change. Next: /prm on the re-landed phase-5 PR (corpus out of git, human choice); then close the programme in the task.</p><span class="review-meta">Reviewed 2026-10-08</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/mge_nnls_fix_pyautoarray_571_slam_60.md">Linear-solver programme phase 3: GPU/vmap/A100 timing and parity rows for the solver corpus</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/399" aria-label="Issue for Linear-solver programme phase 3: GPU/vmap/A100 timing and parity rows for the solver corpus" title="Issue">↗</a></h4><p class="review-meta">active · medium</p><p>Phases 3a/3b/4a merged (#394, #396, #398; Mind records complete/2026/10/linear-solver-p3a-a100-parity.md, linear-solver-p3b-gpu-timing.md, linear-solver-p4a-jacobi-a100-divergence.md). Phase 5 Mapper corpus issued as #399 (Mind active/linear_solver_phase5_mapper_corpus.md, worktree linear-solver-p5-mapper-corpus, Opus executing). Task stays active until the re-landed phase-5 PR is merged. Decision taken 2026-10-08: keep Jacobi for Mapper, raw+polish for MGE-only (decisions/linear-solver-mapper-default-jacobi.md).</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/fe9ca472/wiki/research/jacobi_a100_batched_divergence.md" aria-label="Evidence for Linear-solver accuracy and cost" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-linear-solver" data-open="campaign-linear-solver" aria-label="Tasks for Linear-solver accuracy and cost" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Production imaging and likelihood breakdown</strong><details id="campaign-imaging" class="campaign-detail"><summary>3 tasks · next step</summary><p>No new results since the pin. Over-sampling phase 1: add --instrument production presets to the JAX Delaunay cells (CPU smoke only); PyAutoArray#606 S/N over-sampling helper (in 2026.10.4.1) is new context. Post-certified Blocked-by is stale (resolved 2026-09-27).</p><span class="review-meta">Reviewed 2026-10-04</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/imaging_production_over_sampling.md">Profile imaging pixelizations at production over-sampling</a></h4><p class="review-meta">ready · normal</p><p>Phase 1 (workspace-only): --instrument euclid|hst presets for the JAX Delaunay runtime/breakdown cells, keeping flat-1 selectable; CPU smoke only. A100 re-measure is a separate compute-authorized phase.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/post_certified_solver_likelihood_breakdown.md">Assess remaining likelihood bottlenecks after certified solver integration on CPU and GPUs</a></h4><p class="review-meta">needs-slicing · normal</p><p>Blocked-by is stale: resolved 2026-09-27 (PyAutoArray#567 in 2026.9.26.1). Unissued; scope one bounded phase from the full task contract.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/quick_update_plotting_cost.md">Quick-update plotting cost — minutes per update, and it is not JAX compile</a></h4><p class="review-meta">ready · medium</p><p>Unchanged; targets PyAutoLens/PyAutoGalaxy (PyAutoLens#680 closed 2026-07-31, no follow-up issue). Select one bounded step when prioritised.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/a93f37a7ade16fcb7673a7777dfde505183728ed/wiki/campaigns/post_certified_breakdown.md" aria-label="Evidence for Production imaging and likelihood breakdown" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-imaging" data-open="campaign-imaging" aria-label="Tasks for Production imaging and likelihood breakdown" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Measurement reliability and profiling tools</strong><details id="campaign-measurement-tools" class="campaign-detail"><summary>9 tasks · next step</summary><p>Only timing_noise_audit is issued (autolens_profiling#362: open, 0 comments, unassigned, unchanged since 2026-10-02); start its audit phase via start_dev. New related Mind draft draft/bug/autolens_profiling/call_accounting_ci_timing_threshold.md (2026-10-06). Other tasks unchanged and unissued.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/timing_noise_audit.md">Audit timing tests and profiling gates for measurement noise</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/362" aria-label="Issue for Audit timing tests and profiling gates for measurement noise" title="Issue">↗</a></h4><p class="review-meta">ready · high</p><p>Issued as autolens_profiling#362 (open, 0 comments, unassigned, unchanged since 2026-10-02). Related new Mind draft draft/bug/autolens_profiling/call_accounting_ci_timing_threshold.md (2026-10-06). Start the read-and-classify audit phase via start_dev.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/mge_likelihood_breakdown_steps_are_cumulative_an.md">MGE likelihood_breakdown steps are cumulative and `linear_gaussians` is reported as 0</a></h4><p class="review-meta">ready · low</p><p>Unchanged and unissued (no GitHub refs, 2026-10-04). Select one bounded step when measurement-tools is prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/gradient_cost_probe.md">A gradient-cost probe: forward vs `value_and_grad` ms/eval and a strict FD check, on any registry cell</a></h4><p class="review-meta">ready · low</p><p>Unissued. New context 2026-10-07: Heart unit-test timing flagged PyAutoLens forward-gradient tests +150%/+96% after PyAutoLens#768 rewrote that test file; not a controlled comparison, and this probe is the right instrument. Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/numba_breakdown_harness_memo_blind.md">Numba breakdown harness: perturb the instance so the operated-matrix memo cannot hide a step</a></h4><p class="review-meta">ready · medium</p><p>Unchanged and unissued (PyAutoArray#496 closed 2026-08-27). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/search_settings_estimation_infrastructure.md">Search settings-estimation + profiling infrastructure (n_starts / batch_size / n_batch)</a></h4><p class="review-meta">ready · normal</p><p>Unchanged and unissued (autolens_profiling#82 closed 2026-08-18). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/jax_compile_probe_needs_own_cell_builder.md">jax_compile/probe.py lost its cell builder with the searches tier — give profiling its own</a></h4><p class="review-meta">ready · normal</p><p>Unchanged and unissued; scripts/misc/jax_compile/probe.py still on main (run state unverified). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/profile_lens_aggregator_needs_config_dir.md">profile_lens_aggregator.py cannot run from the autolens_workspace_developer root: no config/ directory</a></h4><p class="review-meta">ready · low</p><p>Unchanged: workspace_developer main still has no root config/ (bug presumed live, not re-run). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/gradient_pixelization_pin_residual_drift.md">jax_profiling/gradient/imaging/pixelization.py: 3.2% of its pin move is unattributed</a></h4><p class="review-meta">ready · normal</p><p>Unchanged and unissued (PyAutoArray#490 merged 2026-08-26). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/pair_jax_xla_env_vars_with_measured.md">Pair JAX/XLA env vars with measured compile and run times, per backend</a></h4><p class="review-meta">ready · high</p><p>Unchanged and unissued. Context: the jax-version policy is now released (2026.10.7.1 libraries require Nerves with the JAX deadlock exclusions). Select one bounded step when prioritised.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/362" aria-label="Evidence for Measurement reliability and profiling tools" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-measurement-tools" data-open="campaign-measurement-tools" aria-label="Tasks for Measurement reliability and profiling tools" title="Open tasks">☷</a></div></td></tr><tr><td><strong>PyAutoFit profiling bootstrap</strong><details id="campaign-autofit" class="campaign-detail"><summary>1 task · next step</summary><p>Skeleton merged: autofit_profiling#1 (86c77345, 2026-10-07T21:17Z; AGENTS, hooks, hpc/sync, lint) under search-extensibility B1 (PyAutoMind#492). B1 docs legs PyAutoHeart#292 and .github#34 still open 2026-10-08. Porting unstarted; no producer registration until profiling-summary@2 is published (B4a).</p><span class="review-meta">Reviewed 2026-10-08</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/autofit_profiling_bootstrap.md">autofit_profiling: bootstrap the repo + general PyAutoFit profiling epic</a></h4><p class="review-meta">ready · normal</p><p>Adopted by the search-extensibility epic (Mind draft/research/autofit/search_extensibility_epic.md); skeleton merged as autofit_profiling#1 (2026-10-07T21:17Z) under PyAutoMind#492 (B1). Next is B4a (search.fit breakdown exporter, Pulse fit row, epic-1 bottleneck table), then B4b (EP/graphical baseline port). No producer registration until profiling-summary@2 is published (B4a).</p></article></details></td><td><span class="pill">ready</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autofit_profiling/pull/1" aria-label="Evidence for PyAutoFit profiling bootstrap" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-autofit" data-open="campaign-autofit" aria-label="Tasks for PyAutoFit profiling bootstrap" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Critical curves and evaluation grids</strong><details id="campaign-critical-curves" class="campaign-detail"><summary>0 tasks · next step</summary><p>Phase 3b cap fix shipped: PyAutoGalaxy#646 released in 2026.10.4.1 and autolens_workspace_test#343 merged 2026-10-04. Remaining per the wiki Next line: investigate seed coverage/path completion before cluster engine selection (human picks whether to scope it). Wiki page itself is stale (last edited 2026-10-02, still says #646 open).</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><p class="muted">No open tasks.</p></details></td><td><span class="pill">needs-decision</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/critical_curves.md" aria-label="Evidence for Critical curves and evaluation grids" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-critical-curves" data-open="campaign-critical-curves" aria-label="Tasks for Critical curves and evaluation grids" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Certified positive solver</strong><details id="campaign-certified-solver" class="campaign-detail"><summary>0 tasks · next step</summary><p>Parked by choice; wiki unchanged since ab1e4fd (2026-09-27). Its three library/workspace Mind drafts remain in Mind. Retain parked; read the project ledger before proposing new work.</p><span class="review-meta">Reviewed 2026-10-04</span><h3>Active tasks</h3><p class="muted">No open tasks.</p></details></td><td><span class="pill">parked</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/a93f37a7ade16fcb7673a7777dfde505183728ed/wiki/campaigns/certified_positive_solver.md" aria-label="Evidence for Certified positive solver" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-certified-solver" data-open="campaign-certified-solver" aria-label="Tasks for Certified positive solver" title="Open tasks">☷</a></div></td></tr></tbody></table></div><p class="review-meta">Open means tracked, not necessarily running. <a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/campaigns.yaml">Full ledger ↗</a></p></div></details><details class="board-section"><summary><h2 id="evidence">Profiling Results</h2></summary><div 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no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"baseline-not-defined","dataset":"point_source_source","id":"baseline/point_source_source/source_plane/unspecified","instrument":null,"label":"point_source_source/source_plane/unspecified · baseline pending","model":"source_plane","role":"planned_baseline","unknowns":{"instrument":"Instrument-independent or not yet declared by the baseline campaign."}},{"configuration":{"image_pixels_masked":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"baseline-not-defined","dataset":"cluster","id":"baseline/cluster/image_plane/unspecified","instrument":null,"label":"cluster/image_plane/unspecified · baseline pending","model":"image_plane","role":"planned_baseline","unknowns":{"instrument":"Instrument-independent or not yet declared by the baseline campaign."}},{"configuration":{"image_pixels_masked":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"baseline-not-defined","dataset":"multi_dataset","id":"baseline/multi_dataset/delaunay/unspecified","instrument":null,"label":"multi_dataset/delaunay/unspecified · baseline pending","model":"delaunay","role":"planned_baseline","unknowns":{"instrument":"Instrument-independent or not yet declared by the baseline campaign."}}],"static_memory_estimates":[{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_delaunay.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"delaunay","per_replica":{"unit":"MiB","value":921.913},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":62},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_delaunay_sparse.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"delaunay","per_replica":{"unit":"MiB","value":131.505},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_mge.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"mge","per_replica":{"unit":"MiB","value":16.411},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_mge_sparse.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"mge","per_replica":{"unit":"MiB","value":16.411},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_pixelization.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"rectangular","per_replica":{"unit":"MiB","value":931.004},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":62},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_pixelization_sparse.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"rectangular","per_replica":{"unit":"MiB","value":94.906},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/delaunay_nn/vmap_probe_delaunay_nn_batch64_cufft_failed.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"delaunay_nn","per_replica":{"unit":"MiB","value":770.97},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"point_source_source","evidence":{"fragment":null,"path":"results/runtime/point_source_source/source_plane_solved/vmap_probe_source_plane_solved.json"},"instrument":"simple","kind":"xla_static_buffer_estimate","model":"source_plane_solved","per_replica":{"unit":"MiB","value":0.0},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64}],"unbound_findings":[{"description":"The conversion maps every magnitude at or above 0.999 to q=0.000500250125062532. NumPy reaches the thin valid annulus below one but its constructor guard blocks the beyond-unit region; JAX arrays and tracers bypass that concrete-scalar guard.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.ell_comps.magnitude-saturation","path":"results/hazards/hazards_index.json"},"id":"component.ell_comps.magnitude-saturation","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"ell_comps","title":"ell_comps magnitude saturates at 0.999"},{"description":"A second, load-bearing saturation prevents the q=1 divisions in the elliptical Isothermal deflection from becoming 0/0. Its affected ell_comps disk is too small for prior-sampling discovery.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.isothermal.near-spherical-saturation","path":"results/hazards/hazards_index.json"},"id":"component.isothermal.near-spherical-saturation","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"isothermal","title":"Isothermal caps near-spherical axis ratios at 0.99999"},{"description":"`_wofz_rational` selects one of three rational branches with `xp.where` on |z|^2 and Im(z)^2. The value is continuous to ~1e-6 across a seam but the derivative is not, so `jax.grad` of any MGE deflection carries a kink wherever a grid point crosses a boundary. Autodiff derivative error just above the r2=2.5 seam reaches 7.71e-06 relative, against 1.3e-14 for the SciPy path the numpy backend uses.","discovery":{"models":[],"reason":"Shared MGE mass-profile deflection component study, not specifically the imaging MGE light-model likelihood. Consult the recorded component and revision before applying this finding.","shared":true},"evidence":{"fragment":"/findings/component.mge.faddeeva-seam-gradient","path":"results/hazards/hazards_index.json"},"id":"component.mge.faddeeva-seam-gradient","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"mge","title":"The JAX Faddeeva routine's region seams make its derivative discontinuous"},{"description":"The elliptical Faddeeva form is singular at q = 1, so the MGE machinery clamps the axis ratio to 0.9999. The numpy path escapes through an exact radial branch; the JAX path cannot, and every *Sph MGE-routed profile is biased by up to 6.18e-05 relative with a spurious cross-axis deflection of 0.000139 arcsec.","discovery":{"models":[],"reason":"Shared MGE mass-profile deflection component study, not specifically the imaging MGE light-model likelihood. Consult the recorded component and revision before applying this finding.","shared":true},"evidence":{"fragment":"/findings/component.mge.spherical-clamp-bias","path":"results/hazards/hazards_index.json"},"id":"component.mge.spherical-clamp-bias","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"mge","title":"Spherical MGE profiles are evaluated as ellipses at the q = 0.9999 clamp on JAX"},{"description":"The JAX backend replaces the exact SciPy hyp2f1 angular factor with a fixed 20-term omega series. Relative deflection error grows continuously to 0.297 over the measured factor curve.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.power-law.series-vs-hyp2f1-divergence","path":"results/hazards/hazards_index.json"},"id":"component.power-law.series-vs-hyp2f1-divergence","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"power_law","title":"PowerLaw's 20-term JAX series diverges from hyp2f1 at high ellipticity"},{"description":"The spherical radial coordinate returns the correct finite value zero at the profile centre, but JAX differentiation of sqrt(y^2+x^2) returns a non-finite gradient there.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.spherical-geometry.radial-sqrt-gradient-at-zero","path":"results/hazards/hazards_index.json"},"id":"component.spherical-geometry.radial-sqrt-gradient-at-zero","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"spherical_geometry","title":"Radial sqrt has a non-finite gradient at r=0"},{"description":"Using only the diagonal entries the policy actually touches, the absolute floor reaches 4.457e-05 of their scale. A reference-calibrated scale-aware counterfactual holds its fraction fixed with maximum relative output error 3.395e-05.","discovery":{"models":[{"dataset":"imaging","model":"rectangular"}],"reason":"The reproducer is the imaging rectangular-source likelihood fixture. This is related model evidence; it does not establish applicability to other configurations or measured versions.","shared":false},"evidence":{"fragment":"/findings/likelihood.imaging-pixelization.absolute-conditioning-floors","path":"results/hazards/hazards_index.json"},"id":"likelihood.imaging-pixelization.absolute-conditioning-floors","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"imaging_pixelization","title":"Absolute inversion floors move with dataset scale"},{"description":"The NumPy full-likelihood scan changes active support at 5 bounded Einstein-radius location(s). The report measures explicit epsilon-neighbourhood mass, not exact-kink prior mass.","discovery":{"models":[{"dataset":"imaging","model":"rectangular"}],"reason":"The reproducer is the imaging rectangular-source likelihood fixture. This is related model evidence; it does not establish applicability to other configurations or measured versions.","shared":false},"evidence":{"fragment":"/findings/likelihood.imaging-pixelization.nnls-active-set-kinks","path":"results/hazards/hazards_index.json"},"id":"likelihood.imaging-pixelization.nnls-active-set-kinks","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"imaging_pixelization","title":"NNLS support changes create likelihood kinks"},{"description":"2 argmax-switch location(s) found in [0.0, 3.0] (4 truth positions, 0 of them where max_sep is already over threshold — i.e. a second, threshold-independent gradient kink in the ACTIVE penalty region, from max_sep itself being a max of several smooth per-position functions).","discovery":{"models":[],"reason":"Shared positions-penalty method study. Whether a particular likelihood uses this penalty and is affected is not established.","shared":true},"evidence":{"fragment":"/findings/likelihood.positions-penalty.argmax-switch","path":"results/hazards/hazards_index.json"},"id":"likelihood.positions-penalty.argmax-switch","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"positions_penalty","title":"Which position-pair sets max_sep switches discontinuously across the sweep"},{"description":"Across 40/401 grid points with max_sep \u003c threshold, penalty value and gradient are exactly zero (max |value|=0.000e+00, max |grad|=0.000e+00) — a gradient-search lane deep inside the fence gets NO signal at all from the positions term, by construction.","discovery":{"models":[],"reason":"Shared positions-penalty method study. Whether a particular likelihood uses this penalty and is affected is not established.","shared":true},"evidence":{"fragment":"/findings/likelihood.positions-penalty.interior-plateau","path":"results/hazards/hazards_index.json"},"id":"likelihood.positions-penalty.interior-plateau","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"positions_penalty","title":"PositionsLH penalty is an exact-zero, zero-gradient plateau inside threshold"},{"description":"Sweeping einstein_radius in [0.0, 3.0] (401 pts, threshold=0.3, factor=1e+08), a tight (+/-1e-6) probe at each of 2 max_sep==threshold crossing(s) shows the penalty VALUE is continuous there (max gap 2.006e+02) while its jax-autodiff GRADIENT jumps by up to 2.006e+08 — zero on the interior side, nonzero on the exterior side. A gradient optimizer sees a step-function force switching on at the fence, not a smooth potential.","discovery":{"models":[],"reason":"Shared positions-penalty method study. Whether a particular likelihood uses this penalty and is affected is not established.","shared":true},"evidence":{"fragment":"/findings/likelihood.positions-penalty.threshold-hinge","path":"results/hazards/hazards_index.json"},"id":"likelihood.positions-penalty.threshold-hinge","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"positions_penalty","title":"PositionsLH penalty has a C0 hinge at the threshold crossing"},{"description":"The configured 1.0e-03 diagonal add ranges from dominant to negligible as synthetic curvature scale changes. Detection needs no dataset; judging scientific relevance does.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/matrix.curvature.absolute-diagonal-floor","path":"results/hazards/hazards_index.json"},"id":"matrix.curvature.absolute-diagonal-floor","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"matrix","subject_name":"curvature_matrix","title":"Absolute curvature-diagonal floor is scale dependent"}],"valid_until":null,"version":2},"instance":"lens","label":"PyAutoLens","repo":"https://github.com/PyAutoLabs/autolens_profiling","commit":"766f82029b2a10984f3f15e4be2f82a40b099c0e","shard_base":"https://raw.githubusercontent.com/PyAutoLabs/autolens_profiling/766f82029b2a10984f3f15e4be2f82a40b099c0e/dashboard/","local":false,"remote_shards":true}</script><p data-id="load-status" role="status" aria-live="polite"></p><div data-id="navigation"></div><section data-id="results" aria-label="Selected setup" hidden></section><noscript><details><summary>Original setup evidence (JavaScript disabled)</summary><ul><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_breakdown_v2026.7.23.1.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_breakdown_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_breakdown_v2026.7.6.649.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_breakdown_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_hpc_ral_cpu_fp64.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_local_cpu_fp64.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/source_plane_breakdown_v2026.7.23.1.json">cluster / source_plane / unspecified — results/breakdown/cluster/source_plane_breakdown_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/source_plane_breakdown_v2026.7.6.649.json">cluster / source_plane / unspecified — results/breakdown/cluster/source_plane_breakdown_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/datacube/delaunay_hpc_a100_fp64.json">datacube / delaunay / alma_high — results/breakdown/datacube/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/datacube/delaunay_hpc_a100_mp.json">datacube / delaunay / alma_high — results/breakdown/datacube/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_autotune4.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_autotune4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split_2026_09_05.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split_2026_09_05.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_control_2026_09_07.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_control_2026_09_07.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1_control.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_recon_split.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_walk_early_exit.json">imaging 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href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly_control.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk1024.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk1024.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk2048.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk2048.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk4096.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk4096.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk512.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk512.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_control_2026_09_07.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_control_2026_09_07.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_control.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000_sparse.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000_sparse.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_recon_split.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_sparse.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_vmap64.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_vmap64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_walk_early_exit.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_walk_early_exit.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_numba_breakdown_euclid_v2026.8.17.1.json">imaging / delaunay / euclid — results/breakdown/imaging/delaunay_numba_breakdown_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_numba_breakdown_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_numba_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2_control.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3_control.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n3000_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n3000_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_nn_hpc_a100_fp64_fixed_light.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_delaunay_nn_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_hpc_a100_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_hpc_a100_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_t1.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_t1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_tall.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_tall.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_hpc_a100_fp64_fixed_light_library.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_hpc_a100_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_t1.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_t1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_tall.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_tall.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_euclid_n1225_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / euclid — results/breakdown/imaging/fixed_light_library_rectangular_euclid_n1225_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / euclid — results/breakdown/imaging/fixed_light_library_rectangular_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_euclid_n484_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / euclid — results/breakdown/imaging/fixed_light_library_rectangular_euclid_n484_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_t1.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_t1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_tall.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_tall.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library_vmap2.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library_vmap2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_mp_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_n1225_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_n1225_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_n484_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_n484_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3025_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3025_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n12000.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n3000.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n5000.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_nn_hpc_a100_fp64_matrix_free.json">imaging / delaunay_nn / hst — results/breakdown/imaging/matrix_free_delaunay_nn_hpc_a100_fp64_matrix_free.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n12000.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n3000.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n5000.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_breakdown_hst_v2026.5.29.4.json">imaging / mge / hst — results/breakdown/imaging/mge_breakdown_hst_v2026.5.29.4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_breakdown_hst_v2026.7.6.649.json">imaging / mge / hst — results/breakdown/imaging/mge_breakdown_hst_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_breakdown_hst_v2026.8.17.1.json">imaging / mge / hst — results/breakdown/imaging/mge_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_hpc_a100_fp64.json">imaging / mge / hst — results/breakdown/imaging/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1_rtu.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1_rtu.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_recon_split.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_mp.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_mp_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_numba_breakdown_euclid_v2026.8.17.1.json">imaging / rectangular / euclid — results/breakdown/imaging/pixelization_numba_breakdown_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1_rtu.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1_rtu.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r2.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r5.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_mp.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64.json">interferometer / mge / alma_high — results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64_sparse.json">interferometer / mge / alma_high — results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/mge_hpc_a100_mp.json">interferometer / mge / alma_high — results/breakdown/interferometer/alma_high/mge_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r2.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r5.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_mp.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay / sma — results/breakdown/interferometer/delaunay_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64_constant_split.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64_r2.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64_r5.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_mp.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay / sma — results/breakdown/interferometer/delaunay_numba_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / alma — results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_levers.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_levers.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r4.25.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r4.25.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r6.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r6.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_jax_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / alma — results/breakdown/interferometer/delaunay_numba_jax_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_jax_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_jax_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_reference_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / alma — results/breakdown/interferometer/delaunay_numba_reference_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_reference_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_reference_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_source_loop_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_source_loop_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_symmetric_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_symmetric_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_two_stage_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_two_stage_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/delaunay_hpc_a100_fp64.json">interferometer / delaunay / jvla — results/breakdown/interferometer/jvla/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/delaunay_hpc_a100_mp.json">interferometer / delaunay / jvla — results/breakdown/interferometer/jvla/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/mge_hpc_a100_fp64.json">interferometer / mge / jvla — results/breakdown/interferometer/jvla/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/mge_hpc_a100_fp64_sparse.json">interferometer / mge / jvla — results/breakdown/interferometer/jvla/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/mge_hpc_a100_mp.json">interferometer / mge / jvla — results/breakdown/interferometer/jvla/mge_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/pixelization_hpc_a100_fp64.json">interferometer / rectangular / jvla — results/breakdown/interferometer/jvla/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/pixelization_hpc_a100_mp.json">interferometer / rectangular / jvla — results/breakdown/interferometer/jvla/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_alma_high_v2026.8.17.1.json">interferometer / mge / alma_high — results/breakdown/interferometer/mge_breakdown_alma_high_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1.json">interferometer / mge / alma — results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1_sparse.json">interferometer / mge / alma — results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1.json">interferometer / mge / sma — results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1_sparse.json">interferometer / mge / sma — results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_dft_breakdown_sma_v2026.8.17.1.json">interferometer / mge / sma — results/breakdown/interferometer/mge_dft_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_hpc_a100_fp64.json">interferometer / mge / alma — results/breakdown/interferometer/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_hpc_a100_fp64_sparse.json">interferometer / mge / alma — results/breakdown/interferometer/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n1000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n1000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n2500.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n4000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n4000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n1000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n1000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n2500.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n4000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n4000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n1024.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n1024.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n2500.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n4096.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n4096.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n1024.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n1024.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n2500.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n4096.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n4096.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular / sma — results/breakdown/interferometer/pixelization_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_fp64.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_fp64_r2.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_fp64_r5.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_mp.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular / sma — results/breakdown/interferometer/pixelization_numba_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / alma — results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / sma — results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_levers.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_levers.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r4.25.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r4.25.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r6.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r6.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_jax_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / alma — results/breakdown/interferometer/pixelization_numba_jax_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_jax_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / sma — results/breakdown/interferometer/pixelization_numba_jax_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_reference_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / alma — results/breakdown/interferometer/pixelization_numba_reference_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_reference_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / sma — results/breakdown/interferometer/pixelization_numba_reference_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/delaunay_hpc_a100_fp64.json">interferometer / delaunay / sdp81 — results/breakdown/interferometer/sdp81/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / sdp81 — results/breakdown/interferometer/sdp81/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64.json">interferometer / mge / sdp81 — results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64_sparse.json">interferometer / mge / sdp81 — results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/pixelization_hpc_a100_fp64.json">interferometer / rectangular / sdp81 — results/breakdown/interferometer/sdp81/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / sdp81 — results/breakdown/interferometer/sdp81/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r2.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r5.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_mp.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_ral_cpu_fp64.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/mge_hpc_a100_fp64.json">interferometer / mge / sma — results/breakdown/interferometer/sma/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter.json">interferometer / mge / sma — results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter_main_control.json">interferometer / mge / sma — results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter_main_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r2.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r5.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_mp.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_ral_cpu_fp64.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64.json">point_source_image / image_plane / simple — results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64_p4.json">point_source_image / image_plane / simple — results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64_p4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_image/image_plane_local_cpu_fp64.json">point_source_image / image_plane / simple — results/breakdown/point_source_image/image_plane_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_source/source_plane_hpc_a100_fp64.json">point_source_source / source_plane / simple — results/breakdown/point_source_source/source_plane_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_source/source_plane_hpc_ral_cpu_fp64.json">point_source_source / source_plane / simple — results/breakdown/point_source_source/source_plane_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_source/source_plane_local_cpu_fp64.json">point_source_source / source_plane / simple — results/breakdown/point_source_source/source_plane_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_constant_split.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_control_2026_09_07.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_control_2026_09_07.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_sparse.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_walk_early_exit.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_walk_early_exit.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_likelihood_summary_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64_sparse.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp_sparse.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64_sparse.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp_sparse.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly_control.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_autotune4.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_autotune4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_control.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_sparse.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_likelihood_summary_hst_v2026.8.17.1.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_euclid_v2026.8.17.1.json">imaging / delaunay / euclid — results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/comparison.json">imaging / other / ao — results/runtime/imaging/mge/ao/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/comparison.json">imaging / other / ao — results/runtime/imaging/mge/ao/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/mge_local_cpu_fp64.json">imaging / mge / ao — results/runtime/imaging/mge/ao/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/mge_local_cpu_mp.json">imaging / mge / ao — results/runtime/imaging/mge/ao/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_fp64.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_fp64_sparse.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_mp.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_mp_sparse.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_fp64.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_fp64_sparse.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_mp.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_mp_sparse.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/mge_likelihood_summary_hst_v2026.8.17.1.json">imaging / mge / hst — results/runtime/imaging/mge/mge_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge_mass_jax/mge_mass_jax_likelihood_summary_hst_v2026.8.17.1.json">imaging / mge / hst — results/runtime/imaging/mge_mass_jax/mge_mass_jax_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64_sparse.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp_sparse.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64_sparse.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp_sparse.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_recon_split.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_sparse.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1_rtu.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1_rtu.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_euclid_v2026.8.17.1.json">imaging / rectangular / euclid — results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization_numba_mge_mass/pixelization_numba_mge_mass_likelihood_summary_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/runtime/imaging/pixelization_numba_mge_mass/pixelization_numba_mge_mass_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/alma/comparison.json">interferometer / delaunay / alma — results/runtime/interferometer/delaunay/alma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/alma/delaunay_local_cpu_mp.json">interferometer / delaunay / alma — results/runtime/interferometer/delaunay/alma/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/comparison.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/comparison.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_fp64.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_mp.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/comparison.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/comparison.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/mge_local_cpu_fp64.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/mge_local_cpu_mp.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/comparison.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/comparison.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_fp64.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_mp.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_image/image_plane_solved/image_plane_solved_summary_v2026.7.23.1.json">point_source_image / image_plane / unspecified — results/runtime/point_source_image/image_plane_solved/image_plane_solved_summary_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/comparison.json">point_source_source / other / unspecified — results/runtime/point_source_source/source_plane_solved/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/comparison.json">point_source_source / other / unspecified — results/runtime/point_source_source/source_plane_solved/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_a100_fp64.json">point_source_source / source_plane / unspecified — results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_ral_cpu_fp64.json">point_source_source / source_plane / unspecified — results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/source_plane_solved_summary_v2026.7.23.1.json">point_source_source / source_plane / unspecified — results/runtime/point_source_source/source_plane_solved/source_plane_solved_summary_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/export_probe.json">experiments / mge / unspecified — scripts/misc/jax_compile/results/local_cpu/export_probe.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/export_probe.json">experiments / mge / unspecified — scripts/misc/jax_compile/results/local_cpu/export_probe.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">experiments / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">experiments / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/trace_profile.json">experiments / mge / unspecified — scripts/misc/jax_compile/results/local_cpu/trace_profile.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/mge.json">imaging / 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scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json</a></li></ul></details></noscript></section><!-- decision-history:8f1840916151d6a62b1cb1cd473edede0a3647c198fe8ef2371ce31a66c873a5 --></div></details><details class="board-section"><summary><h2>Decision History</h2></summary><div class="board-section-body"><section id="decision-history"><a class="model-choice" href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/decisions/linear-solver-mapper-default-jacobi.md" target="_blank" rel="noopener" title="Opens in a new tab">Keep Jacobi PDIP as the Mapper default and raw+polish as the MGE-only default</a></section></div></details></main><script>const MAX_PROMPT_CHARS = 50000;
+<nav class="board-nav" aria-label="Board sections"><a class="board-nav-card" href="#campaigns"><span class="board-nav-label">Active campaigns</span></a><a class="board-nav-card" href="#evidence"><span class="board-nav-label">Profiling Results</span></a><a class="board-nav-card" href="#decision-history"><span class="board-nav-label">Decision History</span></a></nav><main><!-- pulse-campaigns:bce1ae813dcdc2d614bbd30393760ee6b5dc2cff55b2444b1c3e62ef817fefb9 --><details class="board-section"><summary><h2 id="campaigns">Active campaigns</h2></summary><div class="board-section-body"><div class="campaign-table"><table><thead><tr><th>Campaign</th><th>Status</th><th>Links</th></tr></thead><tbody><tr><td><strong>Setup baseline collection and scientific acceptance</strong><details id="campaign-setup-baseline" class="campaign-detail"><summary>1 task · next step</summary><p>Specification merged as draft v1 (autolens_profiling#385, 2026-10-06; issue #384 closed). Six unknowns remain: no frozen revisions/env lock; no collection authorization/window; hardware/affinity identity unselected; each cell needs complete settings, input hashes, witness + tolerances; compile per-cell builder unavailable; proposed fp64/mixed coverage is not evidence of support. Human freezes the manifest before separately authorizing collection.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/setup_baseline_campaign.md">Freeze the setup baseline specification, then collect and review evidence</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/384" aria-label="Issue for Freeze the setup baseline specification, then collect and review evidence" title="Issue">↗</a></h4><p class="review-meta">needs-decision · high</p><p>Specification merged as draft v1 (autolens_profiling#385, 2026-10-06). Human resolves the six recorded unknowns and freezes the specification; collection requires separate compute authorization. The report prepares evidence for human scientific review and never promotes baselines. CPU production arrays use ral only.</p></article></details></td><td><span class="pill">needs-decision</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/setup_baseline.md" aria-label="Evidence for Setup baseline collection and scientific acceptance" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-setup-baseline" data-open="campaign-setup-baseline" aria-label="Tasks for Setup baseline collection and scientific acceptance" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Point-source image plane · CPU</strong><details id="campaign-point-source-image-cpu" class="campaign-detail"><summary>1 task · next step</summary><p>Phases 1–4 shipped; completion evidence merged (autolens_profiling#373, 2026-10-04). Closing the epic is the human&#x27;s call. Owed leftovers (RAL cleanup, test move, register_model grad-zero prompt, CI smoke cells, constant_folding A/B, nopad deletion, quiet re-runs) are in the Mind draft point_source_cpu_campaign_owed_leftovers.md. RAL leftover folders not re-listed 2026-10-07 (unverified).</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/pointsolver_cpu_speed_campaign_remainder.md">Point-source (single-source) CPU campaign — carried leftovers and completion evidence</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/370" aria-label="Issue for Point-source (single-source) CPU campaign — carried leftovers and completion evidence" title="Issue">↗</a></h4><p class="review-meta">ready · low</p><p>Completion evidence merged (autolens_profiling#373, 2026-10-04). Still owed, via Mind draft draft/maintenance/autolens/point_source_cpu_campaign_owed_leftovers.md: RAL cleanup, test move, register_model grad-zero prompt, CI smoke cells, constant_folding A/B, nopad deletion, quiet re-runs.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/results/notes/point_source_cpu_campaign.md#campaign-completion-evidence-2026-10-04" aria-label="Evidence for Point-source image plane · CPU" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-point-source-image-cpu" data-open="campaign-point-source-image-cpu" aria-label="Tasks for Point-source image plane · CPU" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Point-source image plane · A100</strong><details id="campaign-point-source-image-gpu" class="campaign-detail"><summary>1 task · next step</summary><p>Phase 0+1 shipped. Forward-mode gradient NaN (PyAutoLens#767) fixed by PyAutoLens#768 (merged 2026-10-04) and released in 2026.10.7.1 (correctness). Remaining human decision: authorize the autolens_inference image-plane fit measurement. Heart unit-test timing rose on the rewritten #768 test file; not a controlled cost comparison (gradient_cost_probe is the instrument).</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/point_source_image_plane_gpu_breakdown.md">Point-source A100 speed-up campaign: profile and optimize with the shared breakdown</a><a class="icon-link" href="https://github.com/PyAutoLabs/PyAutoLens/issues/767" aria-label="Issue for Point-source A100 speed-up campaign: profile and optimize with the shared breakdown" title="Issue">↗</a></h4><p class="review-meta">needs-decision · high</p><p>Forward-mode NaN (PyAutoLens#767) closed: fixed by PyAutoLens#768 (merged 2026-10-04, 0659903d4), released in 2026.10.7.1. The autolens_inference image-plane fit measurement still awaits human authorisation.</p></article></details></td><td><span class="pill">needs-decision</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/point_source_gpu_breakdown.md" aria-label="Evidence for Point-source image plane · A100" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-point-source-image-gpu" data-open="campaign-point-source-image-gpu" aria-label="Tasks for Point-source image plane · A100" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Point-source source plane</strong><details id="campaign-point-source-source" class="campaign-detail"><summary>2 tasks · next step</summary><p>Core complete; parked. Nautilus leaf autolens_inference#17 merged 2026-10-02; no gradient-sampler leaf yet, so Blackjax stays parked (admission not met). Warm-up task option (a) merged as autolens_profiling#374 (2026-10-04); imaging cells and a release sweep remain.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/runtime_cell_single_jit_gpu_warmup.md">Runtime cells&#x27; A100 `single_jit` includes the post-compile warm-up — source-plane 0.642 ms vs a steady 0.267 ms on the same node</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/371" aria-label="Issue for Runtime cells&#x27; A100 `single_jit` includes the post-compile warm-up — source-plane 0.642 ms vs a steady 0.267 ms on the same node" title="Issue">↗</a></h4><p class="review-meta">active · low</p><p>Option (a) merged (autolens_profiling#374, 2026-10-04): full_pipeline_single_jit_median_ms (p10/p90) beside unchanged single_jit; GPU headline labelled &quot;first block after compile&quot;. Imaging release-sweep cells not wired. No release sweep on main yet (results/ commits since 2026-10-04: #375 streaming rows, a README refactor), so the new field has no sweep rows.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/point_source_source_plane_chi_squared_speed.md">Point-source source-plane chi-squared speed-up campaign — remaining candidates (phases 1–2e shipped)</a></h4><p class="review-meta">blocked · low</p><p>Still blocked: gradient-sampler admission not met (autolens_inference has only the Nautilus source-plane leaf, #17 merged 2026-10-02). Blackjax stays parked.</p></article></details></td><td><span class="pill">parked</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/point_source_source_plane.md" aria-label="Evidence for Point-source source plane" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-point-source-source" data-open="campaign-point-source-source" aria-label="Tasks for Point-source source plane" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Cluster PointSolver robustness and performance</strong><details id="campaign-cluster-pointsolver" class="campaign-detail"><summary>2 tasks · next step</summary><p>Unchanged since 2026-09-27; nothing issued or claimed. Wiki still points at the removed Mind draft (now Pulse tasks/). Pick one bounded phase: observable-overflow invalid-result policy + CI witness, or a representative-data baseline cell.</p><span class="review-meta">Reviewed 2026-10-04</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/cluster_pointsolver_speed.md">Cluster PointSolver — robustness, analysis settings and performance</a></h4><p class="review-meta">ready · normal</p><p>Unissued, no claim. Pick one bounded phase per Mind epics.md: observable-overflow invalid-result policy + CI witness, or a representative-data baseline cell.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/point_solver_profiling_cells.md">PointSolver profiling cells: lensed quasar → cluster runtime tier → single/multi-source → multiplane</a></h4><p class="review-meta">ready · normal</p><p>Unissued, no claim. Candidate first cell: a representative-data cluster likelihood_runtime baseline (single-source preset).</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/a93f37a7ade16fcb7673a7777dfde505183728ed/wiki/campaigns/cluster_pointsolver.md" aria-label="Evidence for Cluster PointSolver robustness and performance" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-cluster-pointsolver" data-open="campaign-cluster-pointsolver" aria-label="Tasks for Cluster PointSolver robustness and performance" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Interferometer likelihood and streaming</strong><details id="campaign-interferometer" class="campaign-detail"><summary>4 tasks · next step</summary><p>Decision matrix complete: last cell merged (autolens_profiling#372, 2026-10-04; 1.59e-3 nat CPU/A100 gap accepted by the human). Streaming scaling phase 1 CPU rows merged (#375); 1e8 CPU and A100 rows need compute authorization. fnnls memo back-off released in 2026.10.7.1 (PyAutoArray#615); the #332 after-measurement is owed. Curvature preload and W~ FFT tasks unstarted.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_fixed_mapper_curvature_preload.md">Interferometer fixed-mapper searches: reuse the W~ curvature matrix across likelihood calls via `preloads.curvature_matrix`</a></h4><p class="review-meta">ready · normal</p><p>Phase 1 Mind draft (2026-10-04) still unstarted; run it through start_dev. Human science call first - no production SLaM stage holds the mapper fixed today.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_nnls_memo_scattered_stream_guard.md">fnnls warm-start memo: stop it slowing scattered evaluation streams (interferometer CPU, autolens_profiling#332)</a><a class="icon-link" href="https://github.com/PyAutoLabs/PyAutoArray/issues/613" aria-label="Issue for fnnls warm-start memo: stop it slowing scattered evaluation streams (interferometer CPU, autolens_profiling#332)" title="Issue">↗</a></h4><p class="review-meta">active · medium</p><p>Library half shipped: PyAutoArray#615 (closes #613) merged 2026-10-06, in 2026.10.7.1. Local solver-only witness (n=576): iid memo on/off 1.49x → 1.17x; walk 0.18x unchanged. Owed: re-run the autolens_profiling#332 ALMA Delaunay 2.17x after-measurement (needs compute authorization).</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_streaming_scaling.md">Campaign: interferometer streaming (array-free) vs in-memory — memory and time scaling to 2e8 visibilities</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/368" aria-label="Issue for Campaign: interferometer streaming (array-free) vs in-memory — memory and time scaling to 2e8 visibilities" title="Issue">↗</a></h4><p class="review-meta">active · high</p><p>Phase 1 CPU cells + results/streaming_scaling rows merged (autolens_profiling#375, 2026-10-04); wiki/campaigns/interferometer_streaming.md. Optional: 1e8 CPU row and A100 rows (compute authorization). Library candidate unfiled: chunk transformer.image_from in apply_sparse_operator (memory).</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/interferometer_w_tilde_fft_size_levers.md">Interferometer W~ curvature matrix is FFT-bound on the mask extent: pruned padded FFT and real-space pixel scale on the A100</a></h4><p class="review-meta">ready · normal</p><p>Unstarted (no PR/issue/branch/results, 2026-10-04). Select one bounded step when prioritised.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/interferometer_likelihood.md" aria-label="Evidence for Interferometer likelihood and streaming" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-interferometer" data-open="campaign-interferometer" aria-label="Tasks for Interferometer likelihood and streaming" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Linear-solver accuracy and cost</strong><details id="campaign-linear-solver" class="campaign-detail"><summary>0 tasks · next step</summary><p>Programme question CLOSED by decision 2026-10-08 (decisions/linear-solver-mapper-default-jacobi.md): keep Jacobi as the Mapper default, raw+polish for MGE-only, no library change. Phase 5 merged as autolens_profiling#401 (766f8202; #400 superseded, corpus files out of git with sha256 + regenerate in the manifest, copies on RAL and the laptop); phases 3a/3b/4a merged earlier (#394, #396, #398). Open evidence gaps, not tasks: wide-prior Mapper vectors, an interferometer corpus, the n~1500 CPU batched/unbatched 4e-13 difference, rectangular criterion-2 failures. Campaign stays active for the release re-runs of the solver cells; nothing issued.</p><span class="review-meta">Reviewed 2026-10-08</span><h3>Active tasks</h3><p class="muted">No open tasks.</p></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/decisions/linear-solver-mapper-default-jacobi.md" aria-label="Evidence for Linear-solver accuracy and cost" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-linear-solver" data-open="campaign-linear-solver" aria-label="Tasks for Linear-solver accuracy and cost" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Production imaging and likelihood breakdown</strong><details id="campaign-imaging" class="campaign-detail"><summary>3 tasks · next step</summary><p>No new results since the pin. Over-sampling phase 1: add --instrument production presets to the JAX Delaunay cells (CPU smoke only); PyAutoArray#606 S/N over-sampling helper (in 2026.10.4.1) is new context. Post-certified Blocked-by is stale (resolved 2026-09-27).</p><span class="review-meta">Reviewed 2026-10-04</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/imaging_production_over_sampling.md">Profile imaging pixelizations at production over-sampling</a></h4><p class="review-meta">ready · normal</p><p>Phase 1 (workspace-only): --instrument euclid|hst presets for the JAX Delaunay runtime/breakdown cells, keeping flat-1 selectable; CPU smoke only. A100 re-measure is a separate compute-authorized phase.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/post_certified_solver_likelihood_breakdown.md">Assess remaining likelihood bottlenecks after certified solver integration on CPU and GPUs</a></h4><p class="review-meta">needs-slicing · normal</p><p>Blocked-by is stale: resolved 2026-09-27 (PyAutoArray#567 in 2026.9.26.1). Unissued; scope one bounded phase from the full task contract.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/quick_update_plotting_cost.md">Quick-update plotting cost — minutes per update, and it is not JAX compile</a></h4><p class="review-meta">ready · medium</p><p>Unchanged; targets PyAutoLens/PyAutoGalaxy (PyAutoLens#680 closed 2026-07-31, no follow-up issue). Select one bounded step when prioritised.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/a93f37a7ade16fcb7673a7777dfde505183728ed/wiki/campaigns/post_certified_breakdown.md" aria-label="Evidence for Production imaging and likelihood breakdown" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-imaging" data-open="campaign-imaging" aria-label="Tasks for Production imaging and likelihood breakdown" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Measurement reliability and profiling tools</strong><details id="campaign-measurement-tools" class="campaign-detail"><summary>9 tasks · next step</summary><p>Only timing_noise_audit is issued (autolens_profiling#362: open, 0 comments, unassigned, unchanged since 2026-10-02); start its audit phase via start_dev. New related Mind draft draft/bug/autolens_profiling/call_accounting_ci_timing_threshold.md (2026-10-06). Other tasks unchanged and unissued.</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/timing_noise_audit.md">Audit timing tests and profiling gates for measurement noise</a><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/362" aria-label="Issue for Audit timing tests and profiling gates for measurement noise" title="Issue">↗</a></h4><p class="review-meta">ready · high</p><p>Issued as autolens_profiling#362 (open, 0 comments, unassigned, unchanged since 2026-10-02). Related new Mind draft draft/bug/autolens_profiling/call_accounting_ci_timing_threshold.md (2026-10-06). Start the read-and-classify audit phase via start_dev.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/mge_likelihood_breakdown_steps_are_cumulative_an.md">MGE likelihood_breakdown steps are cumulative and `linear_gaussians` is reported as 0</a></h4><p class="review-meta">ready · low</p><p>Unchanged and unissued (no GitHub refs, 2026-10-04). Select one bounded step when measurement-tools is prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/gradient_cost_probe.md">A gradient-cost probe: forward vs `value_and_grad` ms/eval and a strict FD check, on any registry cell</a></h4><p class="review-meta">ready · low</p><p>Unissued. New context 2026-10-07: Heart unit-test timing flagged PyAutoLens forward-gradient tests +150%/+96% after PyAutoLens#768 rewrote that test file; not a controlled comparison, and this probe is the right instrument. Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/numba_breakdown_harness_memo_blind.md">Numba breakdown harness: perturb the instance so the operated-matrix memo cannot hide a step</a></h4><p class="review-meta">ready · medium</p><p>Unchanged and unissued (PyAutoArray#496 closed 2026-08-27). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/search_settings_estimation_infrastructure.md">Search settings-estimation + profiling infrastructure (n_starts / batch_size / n_batch)</a></h4><p class="review-meta">ready · normal</p><p>Unchanged and unissued (autolens_profiling#82 closed 2026-08-18). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/jax_compile_probe_needs_own_cell_builder.md">jax_compile/probe.py lost its cell builder with the searches tier — give profiling its own</a></h4><p class="review-meta">ready · normal</p><p>Unchanged and unissued; scripts/misc/jax_compile/probe.py still on main (run state unverified). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/profile_lens_aggregator_needs_config_dir.md">profile_lens_aggregator.py cannot run from the autolens_workspace_developer root: no config/ directory</a></h4><p class="review-meta">ready · low</p><p>Unchanged: workspace_developer main still has no root config/ (bug presumed live, not re-run). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/gradient_pixelization_pin_residual_drift.md">jax_profiling/gradient/imaging/pixelization.py: 3.2% of its pin move is unattributed</a></h4><p class="review-meta">ready · normal</p><p>Unchanged and unissued (PyAutoArray#490 merged 2026-08-26). Select one bounded step when prioritised.</p></article><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/pair_jax_xla_env_vars_with_measured.md">Pair JAX/XLA env vars with measured compile and run times, per backend</a></h4><p class="review-meta">ready · high</p><p>Unchanged and unissued. Context: the jax-version policy is now released (2026.10.7.1 libraries require Nerves with the JAX deadlock exclusions). Select one bounded step when prioritised.</p></article></details></td><td><span class="pill">active</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/issues/362" aria-label="Evidence for Measurement reliability and profiling tools" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-measurement-tools" data-open="campaign-measurement-tools" aria-label="Tasks for Measurement reliability and profiling tools" title="Open tasks">☷</a></div></td></tr><tr><td><strong>PyAutoFit profiling bootstrap</strong><details id="campaign-autofit" class="campaign-detail"><summary>1 task · next step</summary><p>Skeleton merged: autofit_profiling#1 (86c77345, 2026-10-07T21:17Z; AGENTS, hooks, hpc/sync, lint) under search-extensibility B1 (PyAutoMind#492). B1 docs legs PyAutoHeart#292 and .github#34 still open 2026-10-08. Porting unstarted; no producer registration until profiling-summary@2 is published (B4a).</p><span class="review-meta">Reviewed 2026-10-08</span><h3>Active tasks</h3><article class="campaign-task"><h4><a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/autofit_profiling_bootstrap.md">autofit_profiling: bootstrap the repo + general PyAutoFit profiling epic</a></h4><p class="review-meta">ready · normal</p><p>Adopted by the search-extensibility epic (Mind draft/research/autofit/search_extensibility_epic.md); skeleton merged as autofit_profiling#1 (2026-10-07T21:17Z) under PyAutoMind#492 (B1). Next is B4a (search.fit breakdown exporter, Pulse fit row, epic-1 bottleneck table), then B4b (EP/graphical baseline port). No producer registration until profiling-summary@2 is published (B4a).</p></article></details></td><td><span class="pill">ready</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autofit_profiling/pull/1" aria-label="Evidence for PyAutoFit profiling bootstrap" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-autofit" data-open="campaign-autofit" aria-label="Tasks for PyAutoFit profiling bootstrap" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Critical curves and evaluation grids</strong><details id="campaign-critical-curves" class="campaign-detail"><summary>0 tasks · next step</summary><p>Phase 3b cap fix shipped: PyAutoGalaxy#646 released in 2026.10.4.1 and autolens_workspace_test#343 merged 2026-10-04. Remaining per the wiki Next line: investigate seed coverage/path completion before cluster engine selection (human picks whether to scope it). Wiki page itself is stale (last edited 2026-10-02, still says #646 open).</p><span class="review-meta">Reviewed 2026-10-07</span><h3>Active tasks</h3><p class="muted">No open tasks.</p></details></td><td><span class="pill">needs-decision</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/719459fefb40c7e5be157f652818dbf923830557/wiki/campaigns/critical_curves.md" aria-label="Evidence for Critical curves and evaluation grids" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-critical-curves" data-open="campaign-critical-curves" aria-label="Tasks for Critical curves and evaluation grids" title="Open tasks">☷</a></div></td></tr><tr><td><strong>Certified positive solver</strong><details id="campaign-certified-solver" class="campaign-detail"><summary>0 tasks · next step</summary><p>Parked by choice; wiki unchanged since ab1e4fd (2026-09-27). Its three library/workspace Mind drafts remain in Mind. Retain parked; read the project ledger before proposing new work.</p><span class="review-meta">Reviewed 2026-10-04</span><h3>Active tasks</h3><p class="muted">No open tasks.</p></details></td><td><span class="pill">parked</span></td><td><div class="link-icons"><a class="icon-link" href="https://github.com/PyAutoLabs/autolens_profiling/blob/a93f37a7ade16fcb7673a7777dfde505183728ed/wiki/campaigns/certified_positive_solver.md" aria-label="Evidence for Certified positive solver" title="Campaign evidence">↗</a><a class="icon-link" href="#campaign-certified-solver" data-open="campaign-certified-solver" aria-label="Tasks for Certified positive solver" title="Open tasks">☷</a></div></td></tr></tbody></table></div><p class="review-meta">Open means tracked, not necessarily running. <a href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/campaigns.yaml">Full ledger ↗</a></p></div></details><details class="board-section"><summary><h2 id="evidence">Profiling Results</h2></summary><div class="board-section-body"><section class="setup-browser" data-setup-browser="lens" aria-label="autolens_profiling setups"><script type="application/json" class="setup-payload">{"catalogue":{"archive_record_count":20709,"comparison_policy":{"id":"no-temporal-comparisons"},"comparisons":[],"coverage":{"excluded":[],"expected":{"baseline_cells":29,"cells":101,"planned_slots":435},"observed":{"records":112,"selected":98,"setups":540}},"evidence_shards":[{"axes":["breakdown"],"axis_devices":{"breakdown":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/eb112c2ba02f1d8956d3.json","precisions":["precision not recorded"],"records":8,"setup_id":"cluster/image_plane/unspecified/07bd0ee5a96fb26cb66f","sha256":"018d1a6796c76256f417b0a8e3fd781a0f4dd866834689f65b8b564189cb9500"},{"axes":["breakdown"],"axis_devices":{"breakdown":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/7b1b0860730056355cb6.json","precisions":["precision not 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recorded"],"records":8,"setup_id":"cluster/source_plane/unspecified/f8ed0d4a341f22830f33","sha256":"dd3638c79b2b6645116c7f7b1fb52f8220a907cd8c70eea202efe07950fb8791"},{"axes":["breakdown"],"axis_devices":{"breakdown":["a100"]},"devices":["a100"],"path":"catalogue/shards/8d08365c80db809fe6ef.json","precisions":["float64"],"records":1,"setup_id":"datacube/delaunay/alma_high/6861c7695d52974b0ea3","sha256":"869edcbc976ddba1edfa05809d9ba6c01d90e9cef8e1028e90d3d6c1db37b745"},{"axes":["breakdown"],"axis_devices":{"breakdown":["a100"]},"devices":["a100"],"path":"catalogue/shards/9ed9973b39d5e1a1cbf6.json","precisions":["mixed"],"records":1,"setup_id":"datacube/delaunay/alma_high/f7e1c1f32cc47c5229ea","sha256":"2486b88fe0dc095712fb312bb2f1fb2ab407062ea106104c9e25b0b34c2f2ac7"},{"axes":["breakdown"],"axis_devices":{"breakdown":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/162eaf4183b703aa2ae7.json","precisions":["precision not 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no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"baseline-not-defined","dataset":"point_source_source","id":"baseline/point_source_source/source_plane/unspecified","instrument":null,"label":"point_source_source/source_plane/unspecified · baseline pending","model":"source_plane","role":"planned_baseline","unknowns":{"instrument":"Instrument-independent or not yet declared by the baseline campaign."}},{"configuration":{"image_pixels_masked":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"baseline-not-defined","dataset":"cluster","id":"baseline/cluster/image_plane/unspecified","instrument":null,"label":"cluster/image_plane/unspecified · baseline pending","model":"image_plane","role":"planned_baseline","unknowns":{"instrument":"Instrument-independent or not yet declared by the baseline campaign."}},{"configuration":{"image_pixels_masked":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"baseline-not-defined","dataset":"multi_dataset","id":"baseline/multi_dataset/delaunay/unspecified","instrument":null,"label":"multi_dataset/delaunay/unspecified · baseline pending","model":"delaunay","role":"planned_baseline","unknowns":{"instrument":"Instrument-independent or not yet declared by the baseline campaign."}}],"static_memory_estimates":[{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_delaunay.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"delaunay","per_replica":{"unit":"MiB","value":921.913},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":62},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_delaunay_sparse.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"delaunay","per_replica":{"unit":"MiB","value":131.505},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_mge.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"mge","per_replica":{"unit":"MiB","value":16.411},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_mge_sparse.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"mge","per_replica":{"unit":"MiB","value":16.411},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_pixelization.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"rectangular","per_replica":{"unit":"MiB","value":931.004},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":62},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/a100_probes/vmap_probe_pixelization_sparse.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"rectangular","per_replica":{"unit":"MiB","value":94.906},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/delaunay_nn/vmap_probe_delaunay_nn_batch64_cufft_failed.json"},"instrument":"hst","kind":"xla_static_buffer_estimate","model":"delaunay_nn","per_replica":{"unit":"MiB","value":770.97},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64},{"dataset":"point_source_source","evidence":{"fragment":null,"path":"results/runtime/point_source_source/source_plane_solved/vmap_probe_source_plane_solved.json"},"instrument":"simple","kind":"xla_static_buffer_estimate","model":"source_plane_solved","per_replica":{"unit":"MiB","value":0.0},"reason":"Compiler memory_analysis estimate; not observed peak VRAM or a validated batch recommendation.","recommended_batch_size":64}],"unbound_findings":[{"description":"The conversion maps every magnitude at or above 0.999 to q=0.000500250125062532. NumPy reaches the thin valid annulus below one but its constructor guard blocks the beyond-unit region; JAX arrays and tracers bypass that concrete-scalar guard.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.ell_comps.magnitude-saturation","path":"results/hazards/hazards_index.json"},"id":"component.ell_comps.magnitude-saturation","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"ell_comps","title":"ell_comps magnitude saturates at 0.999"},{"description":"A second, load-bearing saturation prevents the q=1 divisions in the elliptical Isothermal deflection from becoming 0/0. Its affected ell_comps disk is too small for prior-sampling discovery.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.isothermal.near-spherical-saturation","path":"results/hazards/hazards_index.json"},"id":"component.isothermal.near-spherical-saturation","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"isothermal","title":"Isothermal caps near-spherical axis ratios at 0.99999"},{"description":"`_wofz_rational` selects one of three rational branches with `xp.where` on |z|^2 and Im(z)^2. The value is continuous to ~1e-6 across a seam but the derivative is not, so `jax.grad` of any MGE deflection carries a kink wherever a grid point crosses a boundary. Autodiff derivative error just above the r2=2.5 seam reaches 7.71e-06 relative, against 1.3e-14 for the SciPy path the numpy backend uses.","discovery":{"models":[],"reason":"Shared MGE mass-profile deflection component study, not specifically the imaging MGE light-model likelihood. Consult the recorded component and revision before applying this finding.","shared":true},"evidence":{"fragment":"/findings/component.mge.faddeeva-seam-gradient","path":"results/hazards/hazards_index.json"},"id":"component.mge.faddeeva-seam-gradient","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"mge","title":"The JAX Faddeeva routine's region seams make its derivative discontinuous"},{"description":"The elliptical Faddeeva form is singular at q = 1, so the MGE machinery clamps the axis ratio to 0.9999. The numpy path escapes through an exact radial branch; the JAX path cannot, and every *Sph MGE-routed profile is biased by up to 6.18e-05 relative with a spurious cross-axis deflection of 0.000139 arcsec.","discovery":{"models":[],"reason":"Shared MGE mass-profile deflection component study, not specifically the imaging MGE light-model likelihood. Consult the recorded component and revision before applying this finding.","shared":true},"evidence":{"fragment":"/findings/component.mge.spherical-clamp-bias","path":"results/hazards/hazards_index.json"},"id":"component.mge.spherical-clamp-bias","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"mge","title":"Spherical MGE profiles are evaluated as ellipses at the q = 0.9999 clamp on JAX"},{"description":"The JAX backend replaces the exact SciPy hyp2f1 angular factor with a fixed 20-term omega series. Relative deflection error grows continuously to 0.297 over the measured factor curve.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.power-law.series-vs-hyp2f1-divergence","path":"results/hazards/hazards_index.json"},"id":"component.power-law.series-vs-hyp2f1-divergence","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"power_law","title":"PowerLaw's 20-term JAX series diverges from hyp2f1 at high ellipticity"},{"description":"The spherical radial coordinate returns the correct finite value zero at the profile centre, but JAX differentiation of sqrt(y^2+x^2) returns a non-finite gradient there.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.spherical-geometry.radial-sqrt-gradient-at-zero","path":"results/hazards/hazards_index.json"},"id":"component.spherical-geometry.radial-sqrt-gradient-at-zero","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"spherical_geometry","title":"Radial sqrt has a non-finite gradient at r=0"},{"description":"Using only the diagonal entries the policy actually touches, the absolute floor reaches 4.457e-05 of their scale. A reference-calibrated scale-aware counterfactual holds its fraction fixed with maximum relative output error 3.395e-05.","discovery":{"models":[{"dataset":"imaging","model":"rectangular"}],"reason":"The reproducer is the imaging rectangular-source likelihood fixture. This is related model evidence; it does not establish applicability to other configurations or measured versions.","shared":false},"evidence":{"fragment":"/findings/likelihood.imaging-pixelization.absolute-conditioning-floors","path":"results/hazards/hazards_index.json"},"id":"likelihood.imaging-pixelization.absolute-conditioning-floors","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"imaging_pixelization","title":"Absolute inversion floors move with dataset scale"},{"description":"The NumPy full-likelihood scan changes active support at 5 bounded Einstein-radius location(s). The report measures explicit epsilon-neighbourhood mass, not exact-kink prior mass.","discovery":{"models":[{"dataset":"imaging","model":"rectangular"}],"reason":"The reproducer is the imaging rectangular-source likelihood fixture. This is related model evidence; it does not establish applicability to other configurations or measured versions.","shared":false},"evidence":{"fragment":"/findings/likelihood.imaging-pixelization.nnls-active-set-kinks","path":"results/hazards/hazards_index.json"},"id":"likelihood.imaging-pixelization.nnls-active-set-kinks","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"imaging_pixelization","title":"NNLS support changes create likelihood kinks"},{"description":"2 argmax-switch location(s) found in [0.0, 3.0] (4 truth positions, 0 of them where max_sep is already over threshold — i.e. a second, threshold-independent gradient kink in the ACTIVE penalty region, from max_sep itself being a max of several smooth per-position functions).","discovery":{"models":[],"reason":"Shared positions-penalty method study. Whether a particular likelihood uses this penalty and is affected is not established.","shared":true},"evidence":{"fragment":"/findings/likelihood.positions-penalty.argmax-switch","path":"results/hazards/hazards_index.json"},"id":"likelihood.positions-penalty.argmax-switch","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"positions_penalty","title":"Which position-pair sets max_sep switches discontinuously across the sweep"},{"description":"Across 40/401 grid points with max_sep \u003c threshold, penalty value and gradient are exactly zero (max |value|=0.000e+00, max |grad|=0.000e+00) — a gradient-search lane deep inside the fence gets NO signal at all from the positions term, by construction.","discovery":{"models":[],"reason":"Shared positions-penalty method study. Whether a particular likelihood uses this penalty and is affected is not established.","shared":true},"evidence":{"fragment":"/findings/likelihood.positions-penalty.interior-plateau","path":"results/hazards/hazards_index.json"},"id":"likelihood.positions-penalty.interior-plateau","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"positions_penalty","title":"PositionsLH penalty is an exact-zero, zero-gradient plateau inside threshold"},{"description":"Sweeping einstein_radius in [0.0, 3.0] (401 pts, threshold=0.3, factor=1e+08), a tight (+/-1e-6) probe at each of 2 max_sep==threshold crossing(s) shows the penalty VALUE is continuous there (max gap 2.006e+02) while its jax-autodiff GRADIENT jumps by up to 2.006e+08 — zero on the interior side, nonzero on the exterior side. A gradient optimizer sees a step-function force switching on at the fence, not a smooth potential.","discovery":{"models":[],"reason":"Shared positions-penalty method study. Whether a particular likelihood uses this penalty and is affected is not established.","shared":true},"evidence":{"fragment":"/findings/likelihood.positions-penalty.threshold-hinge","path":"results/hazards/hazards_index.json"},"id":"likelihood.positions-penalty.threshold-hinge","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"likelihood","subject_name":"positions_penalty","title":"PositionsLH penalty has a C0 hinge at the threshold crossing"},{"description":"The configured 1.0e-03 diagonal add ranges from dominant to negligible as synthetic curvature scale changes. Detection needs no dataset; judging scientific relevance does.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/matrix.curvature.absolute-diagonal-floor","path":"results/hazards/hazards_index.json"},"id":"matrix.curvature.absolute-diagonal-floor","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"matrix","subject_name":"curvature_matrix","title":"Absolute curvature-diagonal floor is scale dependent"}],"valid_until":null,"version":2},"instance":"lens","label":"PyAutoLens","repo":"https://github.com/PyAutoLabs/autolens_profiling","commit":"766f82029b2a10984f3f15e4be2f82a40b099c0e","shard_base":"https://raw.githubusercontent.com/PyAutoLabs/autolens_profiling/766f82029b2a10984f3f15e4be2f82a40b099c0e/dashboard/","local":false,"remote_shards":true}</script><p data-id="load-status" role="status" aria-live="polite"></p><div data-id="navigation"></div><section data-id="results" aria-label="Selected setup" hidden></section><noscript><details><summary>Original setup evidence (JavaScript disabled)</summary><ul><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_breakdown_v2026.7.23.1.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_breakdown_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_breakdown_v2026.7.6.649.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_breakdown_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_hpc_ral_cpu_fp64.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/image_plane_local_cpu_fp64.json">cluster / image_plane / unspecified — results/breakdown/cluster/image_plane_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/source_plane_breakdown_v2026.7.23.1.json">cluster / source_plane / unspecified — results/breakdown/cluster/source_plane_breakdown_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/cluster/source_plane_breakdown_v2026.7.6.649.json">cluster / source_plane / unspecified — results/breakdown/cluster/source_plane_breakdown_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/datacube/delaunay_hpc_a100_fp64.json">datacube / delaunay / alma_high — results/breakdown/datacube/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/datacube/delaunay_hpc_a100_mp.json">datacube / delaunay / alma_high — results/breakdown/datacube/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.5.29.4_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.7.6.649_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_breakdown_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_autotune4.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_autotune4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split_2026_09_05.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_constant_split_2026_09_05.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_control_2026_09_07.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_control_2026_09_07.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1_control.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_lever1_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n12000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n5000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_n8000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_recon_split.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_sparse.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_hpc_a100_fp64_walk_early_exit.json">imaging 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href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly_control.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_assembly_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk1024.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk1024.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk2048.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk2048.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk4096.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk4096.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk512.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_chunk512.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_control_2026_09_07.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_control_2026_09_07.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_control.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_launch_latency_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000_sparse.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n3000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000_sparse.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_n5000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_recon_split.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_sparse.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_vmap64.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_vmap64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_walk_early_exit.json">imaging / delaunay_nn / hst — results/breakdown/imaging/delaunay_nn_hpc_a100_fp64_walk_early_exit.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_numba_breakdown_euclid_v2026.8.17.1.json">imaging / delaunay / euclid — results/breakdown/imaging/delaunay_numba_breakdown_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/delaunay_numba_breakdown_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/breakdown/imaging/delaunay_numba_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2_control.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever2_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3_control.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_hpc_a100_fp64_fixed_light_lever3_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1000_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n1500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n2500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n3000_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n3000_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n4000_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_hpc_a100_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_local_cpu_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_fp64_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_mp_fixed_light.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_delaunay_n500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_delaunay_nn_hpc_a100_fp64_fixed_light.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_delaunay_nn_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n1250_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n2500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / euclid — results/breakdown/imaging/fixed_light_library_delaunay_euclid_n500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_hpc_a100_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_hpc_a100_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_t1.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_t1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_tall.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_cpu_fp64_fixed_light_library_tall.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n1250_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n2500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n500_local_cpu_fp64_fixed_light_library_t8.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n500_local_cpu_fp64_fixed_light_library_t8.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay / hst — results/breakdown/imaging/fixed_light_library_delaunay_n500_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_hpc_a100_fp64_fixed_light_library.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_hpc_a100_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_t1.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_t1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_tall.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_cpu_fp64_fixed_light_library_tall.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_fp64_fixed_light_library.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_mp_fixed_light_library.json">imaging / delaunay_nn / hst — results/breakdown/imaging/fixed_light_library_delaunay_nn_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_euclid_n1225_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / euclid — results/breakdown/imaging/fixed_light_library_rectangular_euclid_n1225_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / euclid — results/breakdown/imaging/fixed_light_library_rectangular_euclid_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_euclid_n484_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / euclid — results/breakdown/imaging/fixed_light_library_rectangular_euclid_n484_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_t1.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_t1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_tall.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_cpu_fp64_fixed_light_library_tall.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library_vmap2.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_fp64_fixed_light_library_vmap2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_mp_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_local_rtx2060_mp_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_n1225_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_n1225_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_n2500_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_n2500_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_library_rectangular_n484_local_rtx2060_fp64_fixed_light_library.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_library_rectangular_n484_local_rtx2060_fp64_fixed_light_library.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1024_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n1521_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n2500_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3025_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3025_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n3969_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_hpc_a100_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_hpc_a100_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_local_cpu_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_local_cpu_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_fp64_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_fp64_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_mp_fixed_light.json">imaging / rectangular / hst — results/breakdown/imaging/fixed_light_rectangular_n484_local_rtx2060_mp_fixed_light.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n12000.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n3000.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n5000.json">imaging / delaunay / hst — results/breakdown/imaging/matrix_free_delaunay_hpc_a100_fp64_matrix_free_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_delaunay_nn_hpc_a100_fp64_matrix_free.json">imaging / delaunay_nn / hst — results/breakdown/imaging/matrix_free_delaunay_nn_hpc_a100_fp64_matrix_free.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n12000.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n3000.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n5000.json">imaging / rectangular / hst — results/breakdown/imaging/matrix_free_rectangular_hpc_a100_fp64_matrix_free_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_breakdown_hst_v2026.5.29.4.json">imaging / mge / hst — results/breakdown/imaging/mge_breakdown_hst_v2026.5.29.4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_breakdown_hst_v2026.7.6.649.json">imaging / mge / hst — results/breakdown/imaging/mge_breakdown_hst_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_breakdown_hst_v2026.8.17.1.json">imaging / mge / hst — results/breakdown/imaging/mge_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/mge_hpc_a100_fp64.json">imaging / mge / hst — results/breakdown/imaging/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.5.29.4_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.7.6.649_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1_rtu.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_breakdown_hst_v2026.8.17.1_rtu.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n12000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n3000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n5000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_n8000_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_recon_split.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_fp64_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_mp.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_hpc_a100_mp_sparse.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_hpc_a100_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_numba_breakdown_euclid_v2026.8.17.1.json">imaging / rectangular / euclid — results/breakdown/imaging/pixelization_numba_breakdown_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1_rtu.json">imaging / rectangular / hst — results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1_rtu.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r2.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r5.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_a100_mp.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / delaunay / alma_high — results/breakdown/interferometer/alma_high/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64.json">interferometer / mge / alma_high — results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64_sparse.json">interferometer / mge / alma_high — results/breakdown/interferometer/alma_high/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/mge_hpc_a100_mp.json">interferometer / mge / alma_high — results/breakdown/interferometer/alma_high/mge_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r2.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r5.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_a100_mp.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / rectangular / alma_high — results/breakdown/interferometer/alma_high/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay / sma — results/breakdown/interferometer/delaunay_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64_constant_split.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64_r2.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_fp64_r5.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_a100_mp.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay / sma — results/breakdown/interferometer/delaunay_numba_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / alma — results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_direct_conv_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_levers.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_levers.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r4.25.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r4.25.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r6.0.json">interferometer / delaunay / alma — results/breakdown/interferometer/delaunay_numba_hpc_ral_cpu_fp64_r6.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_jax_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / alma — results/breakdown/interferometer/delaunay_numba_jax_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_jax_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_jax_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_reference_breakdown_alma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / alma — results/breakdown/interferometer/delaunay_numba_reference_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_reference_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_reference_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_source_loop_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_source_loop_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_symmetric_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_symmetric_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/delaunay_numba_two_stage_breakdown_sma_v2026.8.17.1.json">interferometer / delaunay_hilbert_1500 / sma — results/breakdown/interferometer/delaunay_numba_two_stage_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/delaunay_hpc_a100_fp64.json">interferometer / delaunay / jvla — results/breakdown/interferometer/jvla/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/delaunay_hpc_a100_mp.json">interferometer / delaunay / jvla — results/breakdown/interferometer/jvla/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/mge_hpc_a100_fp64.json">interferometer / mge / jvla — results/breakdown/interferometer/jvla/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/mge_hpc_a100_fp64_sparse.json">interferometer / mge / jvla — results/breakdown/interferometer/jvla/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/mge_hpc_a100_mp.json">interferometer / mge / jvla — results/breakdown/interferometer/jvla/mge_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/pixelization_hpc_a100_fp64.json">interferometer / rectangular / jvla — results/breakdown/interferometer/jvla/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/jvla/pixelization_hpc_a100_mp.json">interferometer / rectangular / jvla — results/breakdown/interferometer/jvla/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_alma_high_v2026.8.17.1.json">interferometer / mge / alma_high — results/breakdown/interferometer/mge_breakdown_alma_high_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1.json">interferometer / mge / alma — results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1_sparse.json">interferometer / mge / alma — results/breakdown/interferometer/mge_breakdown_alma_v2026.8.17.1_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1.json">interferometer / mge / sma — results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1_sparse.json">interferometer / mge / sma — results/breakdown/interferometer/mge_breakdown_sma_v2026.8.17.1_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_dft_breakdown_sma_v2026.8.17.1.json">interferometer / mge / sma — results/breakdown/interferometer/mge_dft_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_hpc_a100_fp64.json">interferometer / mge / alma — results/breakdown/interferometer/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/mge_hpc_a100_fp64_sparse.json">interferometer / mge / alma — results/breakdown/interferometer/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n1000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n1000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n2500.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n4000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_hpc_a100_fp64_n4000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n1000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n1000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n2500.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n4000.json">interferometer / delaunay / alma — results/breakdown/interferometer/n_sweep/delaunay_numba_hpc_ral_cpu_fp64_n4000.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n1024.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n1024.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n2500.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n4096.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_hpc_a100_fp64_n4096.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n1024.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n1024.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n2500.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n2500.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n4096.json">interferometer / rectangular / alma — results/breakdown/interferometer/n_sweep/pixelization_numba_hpc_ral_cpu_fp64_n4096.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular / sma — results/breakdown/interferometer/pixelization_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_fp64.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_fp64_r2.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_fp64_r5.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_a100_mp.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular / sma — results/breakdown/interferometer/pixelization_numba_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / alma — results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / sma — results/breakdown/interferometer/pixelization_numba_direct_conv_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_levers.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_levers.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r4.25.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r4.25.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r6.0.json">interferometer / rectangular / alma — results/breakdown/interferometer/pixelization_numba_hpc_ral_cpu_fp64_r6.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_jax_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / alma — results/breakdown/interferometer/pixelization_numba_jax_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_jax_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / sma — results/breakdown/interferometer/pixelization_numba_jax_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_reference_breakdown_alma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / alma — results/breakdown/interferometer/pixelization_numba_reference_breakdown_alma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/pixelization_numba_reference_breakdown_sma_v2026.8.17.1.json">interferometer / rectangular_adapt_image_32x32 / sma — results/breakdown/interferometer/pixelization_numba_reference_breakdown_sma_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/delaunay_hpc_a100_fp64.json">interferometer / delaunay / sdp81 — results/breakdown/interferometer/sdp81/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / sdp81 — results/breakdown/interferometer/sdp81/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64.json">interferometer / mge / sdp81 — results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64_sparse.json">interferometer / mge / sdp81 — results/breakdown/interferometer/sdp81/mge_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/pixelization_hpc_a100_fp64.json">interferometer / rectangular / sdp81 — results/breakdown/interferometer/sdp81/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sdp81/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / sdp81 — results/breakdown/interferometer/sdp81/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r2.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r5.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_a100_mp.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_hpc_ral_cpu_fp64.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / delaunay / sma — results/breakdown/interferometer/sma/delaunay_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/mge_hpc_a100_fp64.json">interferometer / mge / sma — results/breakdown/interferometer/sma/mge_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter.json">interferometer / mge / sma — results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter_main_control.json">interferometer / mge / sma — results/breakdown/interferometer/sma/mge_hpc_a100_fp64_real_scatter_main_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r2.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r5.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_a100_mp.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_a100_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_hpc_ral_cpu_fp64.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r2.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json">interferometer / rectangular / sma — results/breakdown/interferometer/sma/pixelization_numba_hpc_ral_cpu_fp64_r5.0.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64.json">point_source_image / image_plane / simple — results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64_p4.json">point_source_image / image_plane / simple — results/breakdown/point_source_image/image_plane_hpc_ral_cpu_fp64_p4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_image/image_plane_local_cpu_fp64.json">point_source_image / image_plane / simple — results/breakdown/point_source_image/image_plane_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_source/source_plane_hpc_a100_fp64.json">point_source_source / source_plane / simple — results/breakdown/point_source_source/source_plane_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_source/source_plane_hpc_ral_cpu_fp64.json">point_source_source / source_plane / simple — results/breakdown/point_source_source/source_plane_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/breakdown/point_source_source/source_plane_local_cpu_fp64.json">point_source_source / source_plane / simple — results/breakdown/point_source_source/source_plane_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_constant_split.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_control_2026_09_07.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_control_2026_09_07.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_sparse.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_walk_early_exit.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_walk_early_exit.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/delaunay_likelihood_summary_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/delaunay_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/comparison.json">imaging / other / hst — results/runtime/imaging/delaunay/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64_sparse.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp_sparse.json">imaging / delaunay / hst — results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/delaunay/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64_sparse.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp_sparse.json">imaging / delaunay / jwst — results/runtime/imaging/delaunay/jwst/delaunay_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly_control.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_assembly_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_autotune4.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_autotune4.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_constant_split_2026_09_05.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_chunk256.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_control.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_launch_latency_control.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_sparse.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_nn/delaunay_nn_likelihood_summary_hst_v2026.8.17.1.json">imaging / delaunay_nn / hst — results/runtime/imaging/delaunay_nn/delaunay_nn_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_euclid_v2026.8.17.1.json">imaging / delaunay / euclid — results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_hst_v2026.8.17.1.json">imaging / delaunay / hst — results/runtime/imaging/delaunay_numba/delaunay_numba_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/comparison.json">imaging / other / ao — results/runtime/imaging/mge/ao/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/comparison.json">imaging / other / ao — results/runtime/imaging/mge/ao/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/mge_local_cpu_fp64.json">imaging / mge / ao — results/runtime/imaging/mge/ao/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/ao/mge_local_cpu_mp.json">imaging / mge / ao — results/runtime/imaging/mge/ao/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/comparison.json">imaging / other / hst — results/runtime/imaging/mge/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_fp64.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_fp64_sparse.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_mp.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/hst/mge_local_cpu_mp_sparse.json">imaging / mge / hst — results/runtime/imaging/mge/hst/mge_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/mge/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_fp64.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_fp64_sparse.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_mp.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/jwst/mge_local_cpu_mp_sparse.json">imaging / mge / jwst — results/runtime/imaging/mge/jwst/mge_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge/mge_likelihood_summary_hst_v2026.8.17.1.json">imaging / mge / hst — results/runtime/imaging/mge/mge_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/mge_mass_jax/mge_mass_jax_likelihood_summary_hst_v2026.8.17.1.json">imaging / mge / hst — results/runtime/imaging/mge_mass_jax/mge_mass_jax_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/comparison.json">imaging / other / hst — results/runtime/imaging/pixelization/hst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64_sparse.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp_sparse.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/hst/pixelization_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/comparison.json">imaging / other / jwst — results/runtime/imaging/pixelization/jwst/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64_sparse.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp_sparse.json">imaging / rectangular / jwst — results/runtime/imaging/pixelization/jwst/pixelization_local_cpu_mp_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_recon_split.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_recon_split.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_sparse.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_hpc_a100_fp64_sparse.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1_rtu.json">imaging / rectangular / hst — results/runtime/imaging/pixelization/pixelization_likelihood_summary_hst_v2026.8.17.1_rtu.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_euclid_v2026.8.17.1.json">imaging / rectangular / euclid — results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_euclid_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/runtime/imaging/pixelization_numba/pixelization_numba_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/imaging/pixelization_numba_mge_mass/pixelization_numba_mge_mass_likelihood_summary_hst_v2026.8.17.1.json">imaging / rectangular / hst — results/runtime/imaging/pixelization_numba_mge_mass/pixelization_numba_mge_mass_likelihood_summary_hst_v2026.8.17.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/alma/comparison.json">interferometer / delaunay / alma — results/runtime/interferometer/delaunay/alma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/alma/delaunay_local_cpu_mp.json">interferometer / delaunay / alma — results/runtime/interferometer/delaunay/alma/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/comparison.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/comparison.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_fp64.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_mp.json">interferometer / delaunay / sma — results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/comparison.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/comparison.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/mge_local_cpu_fp64.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/mge_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/mge/sma/mge_local_cpu_mp.json">interferometer / mge / sma — results/runtime/interferometer/mge/sma/mge_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/comparison.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/comparison.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_fp64.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_mp.json">interferometer / rectangular / sma — results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_mp.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_image/image_plane_solved/image_plane_solved_summary_v2026.7.23.1.json">point_source_image / image_plane / unspecified — results/runtime/point_source_image/image_plane_solved/image_plane_solved_summary_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/comparison.json">point_source_source / other / unspecified — results/runtime/point_source_source/source_plane_solved/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/comparison.json">point_source_source / other / unspecified — results/runtime/point_source_source/source_plane_solved/comparison.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_a100_fp64.json">point_source_source / source_plane / unspecified — results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_a100_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_ral_cpu_fp64.json">point_source_source / source_plane / unspecified — results/runtime/point_source_source/source_plane_solved/source_plane_solved_hpc_ral_cpu_fp64.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/runtime/point_source_source/source_plane_solved/source_plane_solved_summary_v2026.7.23.1.json">point_source_source / source_plane / unspecified — results/runtime/point_source_source/source_plane_solved/source_plane_solved_summary_v2026.7.23.1.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/accumulate_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1%2B2.json">interferometer / streaming / unspecified — results/streaming_scaling/in_memory_local_cpu_v2026.10.4.1+2.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json">imaging / delaunay_matern / hst — scripts/misc/jax_compile/results/local_cpu/delaunay_matern.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/export_probe.json">experiments / mge / unspecified — scripts/misc/jax_compile/results/local_cpu/export_probe.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/export_probe.json">experiments / mge / unspecified — scripts/misc/jax_compile/results/local_cpu/export_probe.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/knn.json">imaging / knn / hst — scripts/misc/jax_compile/results/local_cpu/knn.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">experiments / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">experiments / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_cpu/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_cpu/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_cpu/trace_profile.json">experiments / mge / unspecified — scripts/misc/jax_compile/results/local_cpu/trace_profile.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/mge.json">imaging / mge / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json">imaging / rectangular / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_A100_80GB_PCIe/pixelization.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json</a></li><li><a href="https://github.com/PyAutoLabs/autolens_profiling/blob/766f82029b2a10984f3f15e4be2f82a40b099c0e/scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json">multi_dataset / mge / hst — scripts/misc/jax_compile/results/local_gpu_NVIDIA_GeForce_RTX_2060_with_Max-Q_Design/mge.json</a></li></ul></details></noscript></section><!-- decision-history:8f1840916151d6a62b1cb1cd473edede0a3647c198fe8ef2371ce31a66c873a5 --></div></details><details class="board-section"><summary><h2>Decision History</h2></summary><div class="board-section-body"><section id="decision-history"><a class="model-choice" href="https://github.com/PyAutoLabs/PyAutoPulse/blob/main/decisions/linear-solver-mapper-default-jacobi.md" target="_blank" rel="noopener" title="Opens in a new tab">Keep Jacobi PDIP as the Mapper default and raw+polish as the MGE-only default</a></section></div></details></main><script>const MAX_PROMPT_CHARS = 50000;
 function promptFits(text){
   let count=0;for(const character of text){if(++count>MAX_PROMPT_CHARS)return false;}
   return true;
diff --git a/dashboard.md b/dashboard.md
index 0d6df04..c94503c 100644
--- a/dashboard.md
+++ b/dashboard.md
@@ -1,6 +1,6 @@
 # PyAutoPulse — profiling dashboard
 
-<!-- pulse-campaigns:5561dbba1d4ce4ed1c8800f397a77dd99346300db80e0872771e47492295f923 -->
+<!-- pulse-campaigns:bce1ae813dcdc2d614bbd30393760ee6b5dc2cff55b2444b1c3e62ef817fefb9 -->
 ## Profiling Check In
 
 <details><summary>Full check-in prompt</summary>
@@ -108,13 +108,12 @@ Reviewed 2026-10-07. Decision matrix complete: last cell merged (autolens_profil
 
 <details><summary>Linear-solver accuracy and cost — active</summary>
 
-Reviewed 2026-10-08. Phase 4a MERGED 2026-10-08 (autolens_profiling#398, fe9ca472; issue #397 closed; A100 job 399050): the A100-only jacobi batched/unbatched difference is deterministic batch-shape-dependent Cholesky rounding (cho_factor/cho_solve differ on 50/50 lanes from initialize at ~1e-15), amplified to order one within 1-2 iterations on the 24 Jacobi-unstable lanes (all 20 of the 3a divergence set); not nondeterminism (deterministic-ops flag bit-identical), not a vmap defect; controls pdip_raw &lt;= 1.3e-13, certified &lt;= 3.4e-12. Wiki wiki/research/jacobi_a100_batched_divergence.md with the decision table (B ruled out, C unlikely, A or D need a Mapper corpus). Human chose option 2 (bounded evidence step): phase 5 Mapper corpus ISSUED as #399 (delaunay_hst, rectangular_hst, slam_mixed_hst, optional interferometer_delaunay; accuracy, timing and divergence cells; one authorized A100 job). Phase 5 delivered (PR #400, A100 job 399225): Jacobi converged 24/24 Mapper/mixed systems, 0 batch-sensitive lanes; raw+polish 1.05-1.62x Jacobi cost. DECISION 2026-10-08 (decisions/linear-solver-mapper-default-jacobi.md): keep Jacobi as the Mapper default, raw+polish for MGE-only, no library change. Next: /prm on the re-landed phase-5 PR (corpus out of git, human choice); then close the programme in the task.
+Reviewed 2026-10-08. Programme question CLOSED by decision 2026-10-08 (decisions/linear-solver-mapper-default-jacobi.md): keep Jacobi as the Mapper default, raw+polish for MGE-only, no library change. Phase 5 merged as autolens_profiling#401 (766f8202; #400 superseded, corpus files out of git with sha256 + regenerate in the manifest, copies on RAL and the laptop); phases 3a/3b/4a merged earlier (#394, #396, #398). Open evidence gaps, not tasks: wide-prior Mapper vectors, an interferometer corpus, the n~1500 CPU batched/unbatched 4e-13 difference, rectangular criterion-2 failures. Campaign stays active for the release re-runs of the solver cells; nothing issued.
 
-[Campaign evidence](https://github.com/PyAutoLabs/autolens_profiling/blob/fe9ca472/wiki/research/jacobi_a100_batched_divergence.md)
+[Campaign evidence](https://github.com/PyAutoLabs/PyAutoPulse/blob/main/decisions/linear-solver-mapper-default-jacobi.md)
 
 ### Active tasks
 
-- [Linear-solver programme phase 3: GPU/vmap/A100 timing and parity rows for the solver corpus](https://github.com/PyAutoLabs/PyAutoPulse/blob/main/tasks/mge_nnls_fix_pyautoarray_571_slam_60.md) — active: Phases 3a/3b/4a merged (#394, #396, #398; Mind records complete/2026/10/linear-solver-p3a-a100-parity.md, linear-solver-p3b-gpu-timing.md, linear-solver-p4a-jacobi-a100-divergence.md). Phase 5 Mapper corpus issued as #399 (Mind active/linear_solver_phase5_mapper_corpus.md, worktree linear-solver-p5-mapper-corpus, Opus executing). Task stays active until the re-landed phase-5 PR is merged. Decision taken 2026-10-08: keep Jacobi for Mapper, raw+polish for MGE-only (decisions/linear-solver-mapper-default-jacobi.md).
 
 </details>
 
diff --git a/tasks/mge_nnls_fix_pyautoarray_571_slam_60.md b/tasks/mge_nnls_fix_pyautoarray_571_slam_60.md
index 17493ba..f1f6629 100644
--- a/tasks/mge_nnls_fix_pyautoarray_571_slam_60.md
+++ b/tasks/mge_nnls_fix_pyautoarray_571_slam_60.md
@@ -65,6 +65,12 @@ The original task below is retained verbatim. Current scheduling state lives in
 - Human decision: keep Jacobi as the Mapper default and raw+polish for MGE-only; no library change. Canonical record `decisions/linear-solver-mapper-default-jacobi.md` (indexed in `decisions.yaml`, Decision History on the board).
 - Human decision (engineering, not a Pulse decision record): the three 50–56 MB corpus files stay out of git — external copies on RAL and the laptop, sha256 + regenerate command in the manifest; PR #400 to be re-landed from a fresh branch, never by rewriting the pushed one.
 
+
+### Complete 2026-10-08
+
+- Phase 5 merged as [autolens_profiling#401](https://github.com/PyAutoLabs/autolens_profiling/pull/401) (`766f8202`, lint green; #400 closed as superseded and its branch deleted on the human's instruction); issue #399 closed; Mind record `complete/2026/10/linear-solver-p5-mapper-corpus.md` (d77a7dea); worktree removed. Corpus copies verified by sha256 on RAL `/mnt/ral/jnightin/autolens_profiling_corpus/` and the laptop canonical checkout.
+- Task status → complete. The programme's open question is closed by the decision record; the solver cells re-run on each release as the standing `scripts/lens/solver/` section.
+
 ---
 
 # Linear-solver programme phase 3: GPU/vmap/A100 timing and parity rows for the solver corpus