Rename simulation scripts to descriptive names

README.md

@@ -51,8 +51,8 @@ key results): [docs/EXPERIMENTS.md](docs/EXPERIMENTS.md).**
 | Adaptation across fading families | `experiments/e7_meta.py` | `experiments/data/e7_meta.json` |
 | End-to-end training with anti-collapse | `experiments/e8_e2e.py` | `experiments/data/e8_e2e.json` |
 | Online top-k acquisition and timing | `experiments/e9_topk_online.py` | `experiments/data/e9_topk_online.json` |
-| beta sweep, attention maps, ablations | `simulation/revision_*.py`, `simulation/plot_figures.py` | `simulation/results/` |
-| Real-data validation (Fig. 5) | `simulation/revision_realdata_train.py`, `simulation/revision_realdata_plot.py` | `simulation/results/` |
+| beta sweep, attention maps, ablations | `simulation/betasweep.py etc.`, `simulation/plot_figures.py` | `simulation/results/` |
+| Real-data validation (Fig. 5) | `simulation/realdata_train.py`, `simulation/realdata_plot.py` | `simulation/results/` |
 
 ## Running
 

docs/EXPERIMENTS.md

@@ -227,14 +227,14 @@ evaluation uses 150-200 Monte Carlo batches of 64 per point.
   `simulation/semantic_correlation_sim.py` with the trained decoder-only
   overlay from `simulation/maml_semantic.py --decoder_only`; threshold
   sweep tau in [0.30,0.50] and the mean-cosine comparison in
-  `simulation/revision_experiments.py`.
-- **beta sweep** (monotone gain law): `simulation/revision_betasweep.py`
+  `simulation/threshold_phase_study.py`.
+- **beta sweep** (monotone gain law): `simulation/betasweep.py`
   (figure `fig/fig4_beta_sweep.pdf`).
 - **Attention heatmaps**: `simulation/plot_figures.py`
   (figure `fig/fig6_hlm.pdf`).
 - **Hyperparameter studies** (S, lambda, d, H, K):
-  `simulation/revision_ablation.py`, `simulation/revision_dsweep.py`,
-  `simulation/revision_e2e.py`.
+  `simulation/ablation_hks.py`, `simulation/dsweep.py`,
+  `simulation/e2e_check.py`.
 - **Real-data study** (manuscript Fig. 5): UCI optical-recognition digits
-  (8x8=64 dimensions), `simulation/revision_realdata_train.py` +
-  `simulation/revision_realdata_plot.py`.
+  (8x8=64 dimensions), `simulation/realdata_train.py` +
+  `simulation/realdata_plot.py`.