diff --git a/dashboard.html b/dashboard.html index 7480ecd..0472560 100644 --- a/dashboard.html +++ b/dashboard.html @@ -399,7 +399,7 @@

ic50_workspace — EP against the graphical joint fit on IC50 dose-response

autolens_inference — Do the PyAutoLens inference backends agree on the HST SLaM posterior

-

active · both · autolens_inference#4 · projects/autolens_inference.md · local /home/jammy/Code/PyAutoLabs/autolens_inference · RAL /mnt/ral/jnightin/autolens_inference

+

active · both · autolens_inference#4 · projects/autolens_inference.md · local /home/jammy/Code/PyAutoLabs/lens/autolens_inference · RAL /mnt/ral/jnightin/autolens_inference

Now

The four A100 base legs are done (dense and sparse, seeds 0-1, all five stages): sparse costs 1.5x dense and buys nothing measurable, and at the same seed the two routes agree to 0.0-0.6 sigma while seeds of the SAME leg disagree by up to 0.9 sigma and ~3 nats — so the slam_hst_base witness bands (2 nats, 0.2 sigma) are tighter than Nautilus's own seed reproducibility on this cell, which is a finding about the bands. Running now: the same chain with a 1250-vertex Hilbert/Delaunay source (343143 dense, 343145 sparse, seeds 0-1) on the A100. Next: pull both, compare seed-paired against slam_base, and decide whether the parity bands need rewriting before the four CPU legs are submitted.

Runs

@@ -416,7 +416,7 @@

autolens_inference — Do the PyAutoLens inference backends agree on the HST
  • 2026-09-14 — run — 342799_[0-1] finished — wall 0:48: slam_hst_base: A100 leg, dense inversion, seeds 0-1, hpc/batch_gpu/submit_slam_hst_jax_gpu_dense (config hpc_a100_jax_gpu_dense_fp64); the 09-12 ask: one hardware type first, GPU; rate-probe 342695 tree m…
  • full log

    -

    resume autolens_inference

    +

    resume autolens_inference

    euclid_sersics — Why does the lens-light Sersic index pile up at the n=5 prior edge

    diff --git a/dashboard.md b/dashboard.md index f667419..522f7d1 100644 --- a/dashboard.md +++ b/dashboard.md @@ -270,7 +270,7 @@ Next: pull the ladder and see where EP's cost and hill_coef width go as N grows; ### autolens_inference — Do the PyAutoLens inference backends agree on the HST SLaM posterior -active · both · [autolens_inference#4](https://github.com/PyAutoLabs/autolens_inference/issues/4) · [projects/autolens_inference.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autolens_inference.md) · local `/home/jammy/Code/PyAutoLabs/autolens_inference` · RAL `/mnt/ral/jnightin/autolens_inference` +active · both · [autolens_inference#4](https://github.com/PyAutoLabs/autolens_inference/issues/4) · [projects/autolens_inference.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autolens_inference.md) · local `/home/jammy/Code/PyAutoLabs/lens/autolens_inference` · RAL `/mnt/ral/jnightin/autolens_inference` **Now** @@ -294,7 +294,7 @@ The four A100 base legs are done (dense and sparse, seeds 0-1, all five stages):
    📋 resume autolens_inference ``` -/cortex — resume autolens_inference: read PyAutoCortex projects/autolens_inference.md (Now, Runs, Log) and then /home/jammy/Code/PyAutoLabs/autolens_inference/wiki/project/state.md and the assistant autolens_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say. +/cortex — resume autolens_inference: read PyAutoCortex projects/autolens_inference.md (Now, Runs, Log) and then /home/jammy/Code/PyAutoLabs/lens/autolens_inference/wiki/project/state.md and the assistant autolens_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say. ```
    diff --git a/projects.yaml b/projects.yaml index fae91a5..1f54d62 100644 --- a/projects.yaml +++ b/projects.yaml @@ -47,7 +47,7 @@ # --------------------------------------------------------------------------- # inference_programme: remote: PyAutoLabs/autolens_profiling - local_path: /home/jammy/Code/PyAutoLabs/autolens_profiling + local_path: /home/jammy/Code/PyAutoLabs/lens/autolens_profiling ral_root: /mnt/ral/jnightin/autolens_profiling mirror: /mnt/c/Users/Jammy/Science/inference_programme sync_cli: hpc/sync @@ -263,7 +263,7 @@ ic50_workspace: autolens_inference: remote: PyAutoLabs/autolens_inference - local_path: /home/jammy/Code/PyAutoLabs/autolens_inference + local_path: /home/jammy/Code/PyAutoLabs/lens/autolens_inference ral_root: /mnt/ral/jnightin/autolens_inference mirror: none sync_cli: hpc/sync @@ -437,7 +437,7 @@ ic50_workspace: autolens_inference: remote: PyAutoLabs/autolens_inference - local_path: /home/jammy/Code/PyAutoLabs/autolens_inference + local_path: /home/jammy/Code/PyAutoLabs/lens/autolens_inference ral_root: /mnt/ral/jnightin/autolens_inference mirror: none sync_cli: hpc/sync @@ -597,7 +597,7 @@ ic50_workspace: autolens_inference: remote: PyAutoLabs/autolens_inference - local_path: /home/jammy/Code/PyAutoLabs/autolens_inference + local_path: /home/jammy/Code/PyAutoLabs/lens/autolens_inference ral_root: /mnt/ral/jnightin/autolens_inference mirror: none sync_cli: hpc/sync