PyAutoLabs · Jammy2211 · Aug 18, 2026 · Aug 18, 2026
diff --git a/active/jax_native_posterior_sampler_wave.md b/active/jax_native_posterior_sampler_wave.md
diff --git a/complete/archive/shelved/jax_native_posterior_sampler_wave.md b/complete/archive/shelved/jax_native_posterior_sampler_wave.md
@@ -0,0 +1,40 @@
+# JAX-native posterior sampler wave — ranked shortlist from the 2026-07-16 deep-research session — SUPERSEDED 2026-08-18
+
+> **SUPERSEDED / SHELVED 2026-08-18.** Removed from the registry (was
+> `parked.md :: blackjax-smc-gradient-kernel`, issue
+> [autolens_workspace_developer#113](https://github.com/PyAutoLabs/autolens_workspace_developer/issues/113))
+> — the wave as scoped here is superseded by the 2026-08-17 human-approved
+> inference programme (`active/inference_programme_ledger.md`, autolens_profiling#134),
+> which owns sampler direction going forward. Stage (a) shipped its findings;
+> stages (b) ChEES-HMC, (c) MCLMC+harmonic, (d) flowMC, (e) jaxns were never
+> issued and are not carried forward as-is.
+>
+> **Preserved parked context (from the deleted `parked.md` entry):** stage (a)
+> POSITIVE — warm-started gradient SMC SAMPLES (acc 0.80->0.17 across tempering,
+> `einstein_radius` 1.5998 vs truth 1.6, max logL ~31781 vs Prodigy MLE
+> 31787.93). Parked 2026-07-24 to clear the deck for the autolens_profiling
+> refactor. All work PRESERVED on pushed branch
+> `feature/blackjax-smc-gradient-kernel` (origin autolens_workspace_developer,
+> tip `6867762`); local worktree removed. Full write-up:
+> `searches_minimal/smc_gradient_findings.md` on that branch. Science memory:
+> `project_gradient_smc_warm_start_sampler_wave`. Gradient path certified
+> OK_HMC_VIABLE (`probe_grad.py`); baseline `nss_grad` row = logZ -31.47. Open
+> resume threads at park time: RAL job 331058
+> (`/mnt/ral/jnightin/smc_grad_logs/smc_warm_ok-331058.out`, 3 warm arms @128p);
+> logZ (~31690-31798) vs Nautilus comparison row; A100 rep-timing;
+> `warm_start.json` is a regenerable cache (re-`--refresh` if it predates the
+> `cov` field). MGE only; pix deferred.
+
+
+Type: research
+Target: autolens_workspace_developer
+Repos:
+- autolens_workspace_developer
+Difficulty: large
+Autonomy: supervised
+Priority: normal
+Status: formalised
+
+Research: JAX-native posterior sampler wave — implement and benchmark the ranked sampler shortlist from the 2026-07-16 deep-research session on the standard searches_minimal problem in @autolens_workspace_developer, via the sampler_pipeline ingest-prototype-profile-promote flow. Ranked stages: (a) blackjax adaptive tempered SMC upgraded to a gradient inner kernel (MALA/HMC + inner_kernel_tuning; extends the existing blackjax_smc.py RWM smoke script; gives logZ from tempering increments), (b) ChEES-HMC many-chain adaptation (cheapest first-class addition; vmap-friendly fixed-length trajectories vs NUTS variable-length trees), (c) MCLMC + adjusted MCLMC warm-started from the multi-start Adam basin, paired with harmonic (learned harmonic mean) for evidence, (d) flowMC (normalizing-flow global jumps; multimodality insurance), (e) jaxns cameo (independent GPU-native nested-sampling cross-check vs Nautilus; inversion-heavy vmap OOM caution applies, NSS history). Constraints from prior campaigns: reverse-mode-only gradients, NaN-gradient degenerate points need masking, vmap fan-out needs lax.map batch_size tiling (Fit#1374 lever), RAL A100 float32. Deliverable per stage: findings doc + benchmark vs Nautilus baseline. Issue stages one at a time as predecessors ship — do not bulk-issue.
+
+<!-- formalised by the Intake (Conception) Agent on 2026-07-16 from user-intake -->
diff --git a/dashboard.md b/dashboard.md
@@ -8,8 +8,8 @@ Tasks only — the organism's health lives with the Heart (`/health`), not here.
 
 | Where | Count |
 |-------|------:|
-| [In flight](#in-flight) (`active/`) | 10 |
-| [Parked](#parked) (`parked.md`) | 4 |
+| [In flight](#in-flight) (`active/`) | 9 |
+| [Parked](#parked) (`parked.md`) | 3 |
 | [Planned](#planned) (`planned.md`) | 7 |
 | [Backlog](#backlog) (`draft/`) | 139 |
 
@@ -49,7 +49,6 @@ Live on GitHub: [open issues](https://github.com/search?q=org%3APyAutoLabs+is%3A
 Issued — each has an open GitHub issue and usually a branch. The full record for each is in [`active.md`](active.md).
 
 - [Commit the inference-methods programme plan + knowledge ledger into autolens_profiling](active/inference_programme_ledger.md) — [issue #134](https://github.com/PyAutoLabs/autolens_profiling/issues/134) — pr-open (https://github.com/PyAutoLabs/autolens_profiling/pull/135)
-- [JAX-native posterior sampler wave — ranked shortlist from the 2026-07-16](active/jax_native_posterior_sampler_wave.md) — [issue #113](https://github.com/PyAutoLabs/autolens_workspace_developer/issues/113) — PARKED 2026-07-24 — stage (a) POSITIVE: warm-started gradient SMC SAMPLES (acc 0.80->0.17 across tempering, einstein_radius…
 - [Remove standalone matplotlib-inline comments](active/matplotlib_inline_standalones.md)
 - [Find what kills MGE multi-start lanes — it is not](active/mge_lane_death.md) — [issue #128](https://github.com/PyAutoLabs/autolens_profiling/issues/128) — CAUSE FOUND 2026-08-15 (cloud CPU session) — written up on autolens_profiling#128. Remaining: GPU/float64/multi-seed…
 - [PositionsLH penalty accumulation returns 2x the LAST penalty, discarding the](active/positions_lh_penalty_accumulation_bug.md) — [issue #699](https://github.com/PyAutoLabs/PyAutoLens/issues/699) — pr-open (https://github.com/PyAutoLabs/PyAutoLens/pull/700)
@@ -64,9 +63,8 @@ Issued — each has an open GitHub issue and usually a branch. The full record f
 Started or scoped, not currently in flight — resume by moving the row back to `active.md`. Full detail in [`parked.md`](parked.md).
 
 <details>
-<summary><b>4</b> task(s)</summary>
+<summary><b>3</b> task(s)</summary>
 
-- **blackjax-smc-gradient-kernel** — [issue #113](https://github.com/PyAutoLabs/autolens_workspace_developer/issues/113) — PARKED 2026-07-24 — stage (a) POSITIVE: warm-started gradient SMC SAMPLES (acc 0.80->0.17 across tempering, einstein_radius…
 - **group4-mge-search-benchmark** — [issue #82](https://github.com/PyAutoLabs/autolens_profiling/issues/82)
 - **matplotlib-inline-standalones**
 - **pyautoreduce-slacs1430-acs-comparison**

diff --git a/...t/maintenance/autolens_workspace_developer/rectangular_experiments_gut_stash.md b/...t/maintenance/autolens_workspace_developer/rectangular_experiments_gut_stash.md
@@ -43,8 +43,9 @@ clean.
 
 ## Constraints
 
-- Wait for the `blackjax-smc-gradient-kernel` claim to release; verify the repo
-  is clean before starting (it had 23 dirty files at wrap-up).
+- The `blackjax-smc-gradient-kernel` claim is RELEASED (worktree removed 2026-07-24;
+  the parked task was shelved as superseded 2026-08-18), so this is no longer
+  blocked — but verify the repo is clean before starting (23 dirty files at wrap-up).
 - Developer repo (doc-light, not CI-gated like the workspaces); still verify
   renamed scripts import cleanly against merged main.
 - Copy any gitignored products out before any worktree teardown.
diff --git a/ideas.md b/ideas.md
@@ -29,7 +29,7 @@
 - [formalised -> feature/pyautogut/repo_skeleton.md] [from: research pyautogut-organ-decision · research/pyautobrain/pyautogut_organ_decision.md] Stand up the PyAutoGut repo skeleton — the new peer organ repo owning condemned self-material: the attic remote, the `refs/archive/condemned/<name>` archive-ref convention (stays out of `git branch -a`), and the `condemned.md` Mind manifest schema (type/locator/confidence/reason/merged?/condemned/sweep-after/breaks-if-wrong/archive-ref+SHA). Work-type feature/pyautogut; also adds PyAutoGut to repos.yaml + ORGANISM.md as a peer organ.
 - [formalised -> feature/pyautobrain/hygiene_pyautogut_drive_seam.md] [from: research pyautogut-organ-decision · research/pyautobrain/pyautogut_organ_decision.md] Add the hygiene→PyAutoGut drive seam in the Brain — a PyAutoGut-aware hygiene `tidy` mode that files condemned candidates into `condemned.md` async (no synchronous per-item gate, replacing the mid-sweep repo_cleanup interrogation), plus a batch `sweep` mode that runs the existing repo_cleanup safety gates against the manifest at a user-chosen time. Mirrors the Heart↔vitals template: the organ holds+voids, the conductor drives. Work-type feature/pyautobrain.
 - [formalised -> research/autofit/multi_band_factorgraph_compile_deeper_dig.md] [from: research multiband-compile · Experiment A · jax_compile/README.md multi-band section + project_multiband_factorgraph_compile_cliff memory] Multi-band FactorGraphModel value_and_grad compile — deeper dig + productize the fix. Experiment A (autolens_profiling branch research/multiband-compile-ab) proved the heterogeneous-per-band-shape cold compile is a 5.9× superlinear XLA-fusion cliff (homogeneous 4-band == single-band 120s; two distinct shapes = 704s CPU), that trace/eval are unchanged, and that the persistent cache rescues both arms (warm 2–7s). Follow-up, ONE task, profiling/research: (1) sub-investigation B — does a per-factor jit boundary inside PyAutoFit FactorGraphModel.log_likelihood_function bound cold to N×single-band + a linear combine, removing the superlinearity WITHOUT padding (the potential source lever, touches PyAutoFit); (2) sub-investigation C — add A100 multi-band vag rows (datacube_img / datacube_img_hetero) to the jax_compile census, quantify the far-lower absolute A100 cliff, and ship the final N-band verdict; (3) productize the immediate user workaround — pad short-wavelength bands to a common grid so all factors share one fused kernel — as a documented recipe and/or helper. Does NOT re-open the #71 single-band settings verdict. Repos: PyAutoFit, autolens_profiling. Difficulty large, supervised.
-- [from: research wsdev#117 pix-prodigy-cpu · pix_prodigy_findings.md] Warm-started sampler wave on meshes — revive the parked jax_native_posterior_sampler_wave with the MultiStartProdigy endpoint population (16 basin-labelled points) as initializer; mesh↔kernel mapping: ChEES-HMC/MCLMC on kernel-CDF+knn, tempered SMC (logZ) on delaunay.
+- [from: research wsdev#117 pix-prodigy-cpu · pix_prodigy_findings.md] Warm-started sampler wave on meshes — revive the shelved jax_native_posterior_sampler_wave shortlist (complete/archive/shelved/, superseded 2026-08-18) with the MultiStartProdigy endpoint population (16 basin-labelled points) as initializer; mesh↔kernel mapping: ChEES-HMC/MCLMC on kernel-CDF+knn, tempered SMC (logZ) on delaunay.
 - [from: research wsdev#117 · resurrection diagnostics] Validate resurrection-rate → HMC-divergence-rate prediction per mesh — cheap; would give a principled mesh/kernel selection rule for Hamiltonian sampling on pixelized sources.
 - [from: research wsdev#117 · thin-baseline caveat] Heavier-settings Nautilus reference runs (n_live >= 500) on the knn/delaunay pix objectives — the n_live=100 baselines missed the truth basin; needed to claim "Prodigy matches a CONVERGED sampler" and to quantify the prior-volume search the gradient stage saves.
 - [from: research wsdev#117 · matern arm] Matérn kernel regularization as a production option — does its evidence ranking track AdaptSplit across real datasets? If yes the gradient-safe scheme can be the SLaM default, not just the search-time choice.

diff --git a/parked.md b/parked.md
@@ -6,16 +6,6 @@ unindexed worktrees or stashes. Move an entry back to `active.md` (or to
 `planned.md` if re-scoping is needed) when work resumes; on shipping,
 write the dated `complete/<YYYY>/<MM>/<slug>.md` record instead.
 
-## blackjax-smc-gradient-kernel
-- issue: https://github.com/PyAutoLabs/autolens_workspace_developer/issues/113
-- status: PARKED 2026-07-24 — stage (a) POSITIVE: warm-started gradient SMC SAMPLES (acc 0.80->0.17 across tempering, einstein_radius 1.5998 vs truth 1.6, max logL ~31781 vs Prodigy MLE 31787.93). Parked to clear the deck for the autolens_profiling refactor (scripts live in autolens_workspace_developer/searches_minimal/, which the refactor churns). All work PRESERVED on pushed branch feature/blackjax-smc-gradient-kernel (origin autolens_workspace_developer, tip 6867762); local worktree removed. Full write-up: searches_minimal/smc_gradient_findings.md on that branch. Science memory: project_gradient_smc_warm_start_sampler_wave. RESUME AFTER REFACTOR: (1) check RAL job 331058 (/mnt/ral/jnightin/smc_grad_logs/smc_warm_ok-331058.out) — 3 warm arms @128p (MALA auto-step, MALA+--tune, HMC): does --tune HOLD acceptance ~0.57 as lambda->1 (fixed step decays 0.80->0.17)? does HMC beat MALA? (2) compare logZ (~31690-31798) vs Nautilus, write comparison.txt row; (3) A100 rep-timing (GPUs full at park); (4) stage (b) ChEES-HMC reusing _warm_start. warm_start.json is a regenerable cache — re-`--refresh` if it predates the cov field (else silent diagonal fallback). MGE only; pix deferred.
-- worktree: none (pushed to origin; local worktree removed 2026-07-24)
-- autonomy: supervised
-- prompt: active/jax_native_posterior_sampler_wave.md
-- note: WAVE TRACKER — this parks the whole JAX-native posterior sampler wave (stages b ChEES-HMC, c MCLMC+harmonic, d flowMC, e jaxns still remain). Do NOT move the prompt to complete/ — stage (a) shipped its findings but the wave continues as a separate run after the refactor. Gradient path certified OK_HMC_VIABLE (probe_grad.py); baseline nss_grad row = logZ -31.47.
-- repos:
-  - autolens_workspace_developer: feature/blackjax-smc-gradient-kernel (pushed, tip 6867762)
-
 ## group4-mge-search-benchmark
 - issue: https://github.com/PyAutoLabs/autolens_profiling/issues/82
 - prompt: active/research_profiling_experiment_in_the_autolens_pr.md