prompt: land the MGE lane-death task and the frozen-lane-counter record

active.md

@@ -1,5 +1,23 @@
 # Active Tasks
 
+## mge-lane-death
+- issue: https://github.com/PyAutoLabs/autolens_profiling/issues/128
+- prompt: active/mge_lane_death.md
+- status: CAUSE FOUND 2026-08-15 (cloud CPU session) — written up on autolens_profiling#128. Remaining: GPU/float64/multi-seed confirmation, and the two follow-ups below.
+- worktree: ~/Code/PyAutoLabs-wt/mge-lane-death (not yet created)
+- repos:
+  - autolens_profiling: research/mge-lane-death (not yet created)
+- CAUSE: the deaths are in the PRIOR term, not the likelihood. The objective is `fom = -2 * (log_likelihood + sum(log_prior_list))` (`Fitness(fom_is_log_likelihood=False)`); a `UniformPrior` is `-inf` outside its box; `MultiStartGradient` steps in PHYSICAL space with no projection back onto that box. A lane crossing a hard prior edge reads as non-finite, and `resurrect=False` never redraws it, so it stays dead for every remaining step — that accumulation IS the 62%. **The likelihood never went non-finite in ~7200 lane-steps across three arms.**
+- evidence: per-lane autopsy at the death vectors — 11/14 have finite likelihood at every pipeline stage and `sum(log_prior) = -inf` with 1-2 params outside a `UniformPrior`; 2/14 have NaN params (the gradient path); 1/14 unexplained. Decisive arm: neutering `log_prior_list_from_vector` -> zeros drops value-NaN 1446 -> 215 (60.25% -> 8.96%) and survivors 2 -> 13, with all 3 residual deaths being NaN-params. A narrower hypothesis (widen the shear box, which was 10 of the 11 exits) was REFUTED — deaths moved later and got marginally worse, because widening one box only moves the wall.
+- reproduction: 16x150 cloud CPU gave 1446/18/0/0 and `alive 2/16` against the filed 1498/9/0/0 and the same 2/16. The survival identity is exact: `sum(150 - k_i) = 14*150 - 654 = 1446` = `n_value_nan_lane_steps`.
+- COUNTER-FINDING, corrects the framing: the `ell_comps` plateau was MASKED, not cleared. The baseline's `n_constrained_lane_steps = 0` was a correctly-measured zero (the positive control was sound) but it meant "nothing got that far" — lanes died of prior-exit first. With the prior deaths removed the constrained count is 667 (27.79%). #1475's trapped-lane counter is measuring a live failure mode on this cell, hidden behind a larger one. Lanes stop being dead and start being STUCK.
+- follow-ups owed (both out of this task's boundary): (1) PyAutoFit — bounded stepping (projection/clipping onto prior support) or soft-walled priors; `resurrect=True` is NOT the fix, it redraws a lane that then walks out again. (2) the ell_comps trapping at 27.79%, now that it is visible.
+- caveat: one baseline death (lane 9, step 39) re-evaluates finite in every term with all params inside their boxes — the jitted/vmapped float32 path differs from the eager recompute there, unexplained. Single seed per arm, CPU, x64 off.
+- reading the number: 62% is a survival integral, not a hazard rate — a frozen lane keeps counting every subsequent step, so the same death curve reports ~75% at 300 steps. Inverting it gives a mean death step of ~43 of 150 (mid-descent, not bad initial draws). Grade any re-run on the alive-versus-step CURVE, not on recovering the scalar.
+- ordering (deliberate, do not revert): cause-finding FIRST on the existing ~6-min CPU run, then the `resurrect=True` budget-recovery measurement, then the production/GPU/seed confirmation. Do not queue for a GPU before the cause step has been attempted.
+- boundary: investigation only. Changing the `resurrect` default is a separate PyAutoFit task — it would shift every existing multi-start benchmark.
+- upstream: PyAutoFit#1475 (`004f798`) + PyAutoGalaxy#572 (`695b27c`) shipped the trapped-lane counter; record in `complete/2026/08/frozen-lane-counter.md`.
+
 ## pix-prodigy-gpu-compat
 - issue: https://github.com/PyAutoLabs/autolens_workspace_developer/issues/125
 - prompt: active/pixelized_prodigy_laptop_gpu_phase_1_compatibility.md