campaigns.yaml

version: 1
last_checkin: '2026-10-17T11:18:53Z'
last_checkin_report: checkins/2026-10-17T111853Z.md
campaigns:
- id: slam-hst-base
  title: HST SLaM base backend parity
  status: superseded
  updated: '2026-10-17'
  next: 'Superseded 2026-10-17 by hst-imaging-mass-samplers (human: clean slate). The 2026-09-24 re-run rows
    stay as history in autolens_inference PR #23; no further run under these campaigns.'
  recent_progress: 'The 2026-09-24 slam_base re-runs landed as 6 rows (A100 jax_gpu dense and sparse, numba_cpu
    sparse; seeds 0-1) in autolens_inference PR #23, pending merge. A100 walls are clean single-attempt; the numba_cpu
    sparse rows carry a resumed source_pix[1] stage.'
  blockers: The three CPU legs jax_cpu dense, jax_cpu sparse and numba_cpu dense have not run; numba_cpu sparse
    chain walls are multi-attempt.
  job_status: 'All 2026-09-24 re-runs COMPLETED 0:0 per sacct queried 2026-10-17T11:10Z: 350674 and 350675 (gpu),
    350682 (ral).'
  evidence: https://github.com/PyAutoLabs/autolens_inference/pull/23
  project: autolens_inference
  checkin_report: checkins/2026-10-17T111853Z.md
- id: slam-hst-delaunay
  title: HST SLaM Delaunay variant
  status: superseded
  updated: '2026-10-17'
  next: 'Superseded 2026-10-17 by hst-imaging-mass-samplers (human: clean slate). The 2026-09-24 re-run rows
    stay as history in autolens_inference PR #23; no further run under these campaigns.'
  recent_progress: 'The 2026-09-24 delaunay_1250 re-runs landed as 6 rows (A100 jax_gpu dense and sparse, numba_cpu
    sparse; seeds 0-1) in autolens_inference PR #23, pending merge. A100 walls are clean single-attempt; the numba_cpu
    sparse rows carry a resumed mass_total[1] stage.'
  blockers: The seed-0 mass_total[1] offset (5.98, 5.12 and 6.62 sigma on dense, sparse and numba_cpu) reproduces
    on three backends; human reading pending in Cortex. Do not merge the Delaunay target with rectangular comparisons.
  job_status: 'All 2026-09-24 re-runs COMPLETED 0:0 per sacct queried 2026-10-17T11:10Z: 350678 and 350679 (gpu),
    350684 (ral).'
  evidence: https://github.com/PyAutoLabs/autolens_inference/pull/23
  project: autolens_inference
  checkin_report: checkins/2026-10-17T111853Z.md
- id: hst-imaging-mass-samplers
  title: 'HST imaging, clean slate: Nautilus base on A100 and jax_cpu at a pinned release, mass stage with linear
    lens light and with it fixed, then other samplers on the mass stage'
  status: needs-slicing
  updated: '2026-10-17'
  next: 'Phase 1 via Mind start_dev: lens-light mode as a run variant (--lens-light linear|fixed|both, fixed = ordinary
    profiles with intensities from the light[1] fit), both rows from one chain, --export-prepared for both modes,
    library revisions and SLURM job id recorded in every row, submit scripts for A100 dense/sparse and ral jax_cpu
    dense/sparse against a private pinned checkout; then phase 2 compute by separate authorisation.'
  recent_progress: 'Opened 2026-10-17 as a fresh start by human decision: the base is re-measured from scratch on
    PyAuto release 2026.10.17.1 (PyAutoLens tag v2026.10.17.1, released 2026-10-17) in fresh output trees; the
    2026-09-24 rows and both earlier campaigns are superseded history.'
  blockers: Phase 1 runner change not started (Mind start_dev pending); no pinned private checkout exists on RAL
    yet; compute not authorised until phase 1 ships.
  job_status: none submitted
  evidence: https://github.com/PyAutoLabs/autolens_inference/pull/23
  project: autolens_inference
  checkin_report: checkins/2026-10-17T111853Z.md
- id: point-source-admission
  title: Point-source sampler admission
  status: needs-decision
  updated: '2026-10-04'
  next: Assess a bounded gradient-sampler admission proposal with the human; no new job is authorized.
  recent_progress: 2 October project record reports five Nautilus seeds; no gradient-sampler admission measurement.
  blockers: Gradient cost share and sampler admission remain unmeasured; Pulse owns likelihood optimisation.
  job_status: unknown — live scheduler not queried; historical ledger states are not current job evidence
  evidence: https://github.com/PyAutoLabs/autolens_inference/blob/146a84346eaa51eda158634cae520d677f3e6213/wiki/project/state.md
  project: autolens_inference
- id: graphical-ep
  title: Graphical and EP inference coordination
  status: needs-slicing
  updated: '2026-10-04'
  next: Reconcile current Cortex observations and shipped fixes, then select one bounded phase.
  recent_progress: Mind campaign map and two scoping contracts preserved verbatim; implementation work remains
    in Mind.
  blockers: Old scoping contains completed phases and decision gates; not a bulk runnable queue.
  job_status: unknown — live scheduler not queried; historical ledger states are not current job evidence
  evidence: https://github.com/PyAutoLabs/PyAutoMind/blob/8dd1edc7e04c960daae3663513c61395823eddb0/draft/research/graphical_ep/ep_campaign.md
  project: graphical_ep
- id: analytic-gaussian
  title: Analytic Gaussian ensemble and control calibration
  status: blocked
  updated: '2026-10-04'
  next: Use Cortex planned diagnostic on passing, edge and worst seeds; retain the human conclusion there.
  recent_progress: Cortex records accepted wave-1 baseline and 30 September independent-review caveats.
  blockers: N=25 stays unsubmitted until control/threshold diagnostic is resolved.
  job_status: unknown — live scheduler not queried; historical ledger states are not current job evidence
  evidence: https://github.com/PyAutoLabs/PyAutoCortex/blob/d45f198804615c090e6b6694cf725ddb0be2354e/projects/analytic_gaussian.md
  project: analytic_gaussian
- id: ep-toy-gaussian
  title: N=50 NUTS versus three EP repeats
  status: needs-decision
  updated: '2026-10-04'
  next: Present the existing wave-2 proposal with current dependency evidence for decision.
  recent_progress: Cortex records failed wave 1 (EMFILE/OOM), wave-2 preparation and no submission.
  blockers: Explicit human go; sample entry/export and resource settings must be verified.
  job_status: unknown — live scheduler not queried; historical ledger states are not current job evidence
  evidence: https://github.com/PyAutoLabs/PyAutoCortex/blob/d45f198804615c090e6b6694cf725ddb0be2354e/projects/ep_toy_gaussian.md
  project: ep_toy_gaussian
- id: slope-hierarchy-scale
  title: Hierarchical slope recovery at scale
  status: blocked
  updated: '2026-10-04'
  next: Verify the moments fix release and project mirror; recover missing summaries from existing samples
    before a proposed rerun.
  recent_progress: Cortex retains graphical baseline, post-processing OOM and stale EP hierarchical factor;
    Mind records later moments fix.
  blockers: Summary/sample retrieval and release/RAL mirror reconciliation outstanding; no reclassification
    from stale prose.
  job_status: unknown — live scheduler not queried; historical ledger states are not current job evidence
  evidence: https://github.com/PyAutoLabs/PyAutoCortex/blob/d45f198804615c090e6b6694cf725ddb0be2354e/projects/slope_hierarchy_scale.md
  project: slope_hierarchy_scale
- id: ic50-scale
  title: IC50 EP and graphical scale ladder
  status: blocked
  updated: '2026-10-04'
  next: Check implementation close-outs, then propose a seeded ladder with appropriate output and mean-field
    diagnostics.
  recent_progress: Cortex records N=5/10/25 results, failed N=50 EP rung and width-interpretation caveat.
  blockers: Projection fix and mean-field width reporting require reconciliation before scientific comparison.
  job_status: unknown — live scheduler not queried; historical ledger states are not current job evidence
  evidence: https://github.com/PyAutoLabs/PyAutoCortex/blob/d45f198804615c090e6b6694cf725ddb0be2354e/projects/ic50_workspace.md
  project: ic50_workspace
- id: gaussian-x3-search-benchmark
  title: PyAutoFit search benchmark on gaussian_x3 (autofit_inference)
  status: running
  updated: '2026-10-16'
  next: 'B5c-2b (draft/research/autofit_inference/search_ext_b5c2b_scored_wave_submit.md): realisations 2-3 and
    their exact references, the correlated_nd@2 scored-wave manifest (83 cells x 50 seeds x 3 realisations,
    12 450 runs) and its probe for 8 probe-first cells, then the submit on RAL --partition=ral from a private
    pinned copy with the A2 memory requests; correlated_nd@2 is frozen (autofit_inference 44c5e77f1fb0); the
    family is catalogued apart from gaussian_x3 and ranks nothing across families.'
  recent_progress: Wave 2 closed (B5b-2, 2026-10-15, autofit_inference#12) — RAL 409930 pulled, 12,750 rows
    admitted at the pin df6d218f10cd with 0 missing; NSS 50-step leads both evidence rankings; the catalogue
    ranks only legs with success rate >= 50 % over >= 20 attempts (post-hoc presentation convention); fit
    records published as inference-summary@3 (101 record shards).
  blockers: none recorded; the fit snapshot stays the committed @1 capture until the first @3 refresh.
  job_status: unknown — live scheduler not queried; the Cortex ledger records 409930 COMPLETED (all 20
    tasks, 2026-10-15)
  evidence: https://github.com/PyAutoLabs/autofit_inference/issues/12
  project: autofit_inference
tasks:
- id: drop_1e3_prior_centring_after_631
  campaign: slam-hst-base
  title: Drop the 1e-3 prior centring for shear / multipole / ell_comps in the benchmark
  status: blocked
  priority: normal
  path: tasks/drop_1e3_prior_centring_after_631.md
  updated: '2026-10-04'
  next: Verify the release containing Galaxy#634 and Lens#754 before changing priors; retain zero-centre gradient
    witness. Carried into hst-imaging-mass-samplers phase 1 as a prior-identity question for the frozen model.
  evidence: https://github.com/PyAutoLabs/PyAutoMind/blob/8dd1edc7e04c960daae3663513c61395823eddb0/draft/feature/autolens_inference/drop_1e3_prior_centring_after_631.md
- id: reconcile_cortex_ledger_references
  campaign: slam-hst-base
  title: Reconcile inference documentation with the current Cortex ledger contract
  status: complete
  priority: normal
  path: tasks/reconcile_cortex_ledger_references.md
  updated: '2026-10-04'
  next: 'Completed in autolens_inference PR #18; original migration text remains immutable evidence.'
  evidence: https://github.com/PyAutoLabs/PyAutoMind/blob/8dd1edc7e04c960daae3663513c61395823eddb0/draft/docs/autolens_inference/reconcile_cortex_ledger_references.md
  completion_evidence: https://github.com/PyAutoLabs/autolens_inference/pull/18
  completion_commit: 26778b158538711a5a79acbadb0699a103446bd7
- id: ep_campaign
  campaign: graphical-ep
  title: EP campaign — phase map for the 2026 Q3 graphical/EP push
  status: needs-decision
  priority: high
  path: tasks/ep_campaign.md
  updated: '2026-10-04'
  next: Reconcile current Cortex records and human gates; this campaign map is never issued or bulk scheduled.
  evidence: https://github.com/PyAutoLabs/PyAutoMind/blob/8dd1edc7e04c960daae3663513c61395823eddb0/draft/research/graphical_ep/ep_campaign.md
- id: ep_scoping
  campaign: graphical-ep
  title: Expectation Propagation Scale-Up — Scoping
  status: needs-slicing
  priority: high
  path: tasks/ep_scoping.md
  updated: '2026-10-04'
  next: Reconcile completed wrapper work and Pulse profiling ownership before selecting a bounded remaining
    inference phase.
  evidence: https://github.com/PyAutoLabs/PyAutoMind/blob/8dd1edc7e04c960daae3663513c61395823eddb0/draft/research/graphical_ep/ep_scoping.md
- id: graphical_scoping
  campaign: graphical-ep
  title: Graphical Model Scale-Up — Scoping
  status: needs-slicing
  priority: high
  path: tasks/graphical_scoping.md
  updated: '2026-10-04'
  next: Reconcile current Cortex scale results and library dependencies; select one bounded inference phase
    with a witness.
  evidence: https://github.com/PyAutoLabs/PyAutoMind/blob/8dd1edc7e04c960daae3663513c61395823eddb0/draft/research/graphical_ep/graphical_scoping.md
- id: gradient_sampler_validated_likelihoods
  campaign: point-source-admission
  title: NUTS/HMC trial on validated likelihoods
  status: needs-decision
  priority: normal
  path: tasks/gradient_sampler_validated_likelihoods.md
  updated: '2026-10-04'
  next: 'An unscoped idea, not permission to submit: reconcile point-source admission with imaging and weak-lensing
    candidate targets.'
  evidence: https://github.com/PyAutoLabs/PyAutoMind/blob/8dd1edc7e04c960daae3663513c61395823eddb0/ideas.md
- id: gaussian_x3_search_wave1
  campaign: gaussian-x3-search-benchmark
  title: gaussian_x3 search benchmark — wave 1 (the pilot)
  status: blocked
  priority: normal
  path: tasks/gaussian_x3_search_wave1.md
  updated: '2026-10-14'
  next: Pilot stopped at 223 of 520 runs and is not restarted; freeze gaussian_x3@2 from its 17-row calibration
    before any scored run; the deferred cells move to scored wave 2 (after A2 and A4).
  evidence: https://github.com/PyAutoLabs/autofit_inference/issues/4
- id: correlated_nd_pilot
  campaign: gaussian-x3-search-benchmark
  title: correlated_nd search benchmark — the pilot (wave 1, second model family)
  status: complete
  priority: normal
  path: tasks/correlated_nd_pilot.md
  updated: '2026-10-16'
  next: Done (B5c-2a, autofit_inference#17) — pilot judged under correlated_nd@1 (1040 expected = 749 rows +
    177 failed + 4 oom + 0 missing + 110 deferred; 307 accepted); correlated_nd@2 frozen in 44c5e77f1fb0 from
    results/calibration/correlated_nd_wave1.json; the scored wave is B5c-2b.
  evidence: https://github.com/PyAutoLabs/autofit_inference/issues/17
- id: gaussian_x3_search_wave2
  campaign: gaussian-x3-search-benchmark
  title: gaussian_x3 search benchmark — wave 2 (scored)
  status: running
  priority: high
  path: tasks/gaussian_x3_search_wave2.md
  updated: '2026-10-15'
  next: Wave 2 is closed and judged (B5b-2); the fit snapshot is captured from main under inference-summary@3
    after the B5b-2 PRs merge.
  evidence: https://github.com/PyAutoLabs/autofit_inference/issues/12
- id: hst_mass_base_light_modes
  campaign: hst-imaging-mass-samplers
  title: 'HST imaging mass stage, clean slate: Nautilus base on A100 and jax_cpu at release 2026.10.17.1, linear
    and fixed lens light'
  status: needs-slicing
  priority: high
  path: tasks/hst_mass_base_light_modes.md
  updated: '2026-10-17'
  next: 'Phase 1 via Mind start_dev: --lens-light linear|fixed|both, both rows from one chain, --export-prepared
    for both modes, library revisions and SLURM job id in every row, A100 and ral jax_cpu submit scripts against
    a private pinned checkout; no compute until phase 1 ships and phase 2 is authorised.'
  evidence: https://github.com/PyAutoLabs/autolens_inference/pull/23
- id: hst_mass_samplers_wave1
  campaign: hst-imaging-mass-samplers
  title: 'HST imaging mass stage: sampler comparison, wave 1'
  status: needs-slicing
  priority: normal
  path: tasks/hst_mass_samplers_wave1.md
  updated: '2026-10-17'
  next: Depends on the frozen mass_total[1] problems (both light modes, A100 and jax_cpu) from the pinned base
    in hst_mass_base_light_modes; candidate samplers from the experiments runner (nautilus, emcee, nuts, smc) and
    the promoted PyAutoFit catalogue (NSS, DynestyStatic/Dynamic, Zeus) are not yet sliced.
  evidence: https://github.com/PyAutoLabs/autolens_inference/pull/23