Phase 1: deterministic execution diagnostics
Frozen before first scientific run: configs/phase1.json (2026-09-16-v1).
CPU only, one numerical-library thread; no GPU and no package installation.
The existing project environment reuses base Conda site packages; each run
records actual package versions and source/config SHA256 hashes.
Questions and interpretation
- E1: Can a shrinking coherent model error coexist with increasing error of the all-A/all-B execution? Evaluate actual KL and model joint TV, output TV, and the bound on uniform head TV. No claim of optimal-policy performance.
- E2: How does an actual self-generated pilot change the posterior and output? Compare a single alternative, the two-level manuscript ladder, and a single alternative matched in initial drift. Same w/Delta does not match KL or drift. Show actual model statistics and retain every grid point. No expected direction of improvement is an acceptance test.
- E3: What does the best randomized adaptive policy attain at small n for a fixed oracle? Compare to predefined schedules, keeping R fixed across K. This does not optimize the outer KL neighborhood and is not an exact proof.
Numerical safeguards
- Pre-round conditional heads are frozen within each batch. No shared latent mixture component is sampled during execution.
- E2 uses M ~ Bin(c, p0), not target prefixes. Its pilot set is selected uniformly using private randomness and is not part of the delivered output; this symmetry is essential for count TV to equal full TV.
- E3 must pass an independent literal-coordinate LP check and the n=1 private randomization regression. Flow, objective, recovered-policy and dual residuals are reported. Solver output remains a floating-point diagnostic.
- Main calculations are deterministic finite sums, not histogram TV estimates; floating-point and normalization checks are reported, not mislabeled exact arithmetic. There are no Monte Carlo confidence bands in this phase.
- No neural-language-model or practical-context-length claims follow.
- Resource caps: 120 s per LP solve, 250,000 state-actions per case; whole study 45 min timeout, 8 GiB address-space cap. Stop/report failures rather than omit.
- This phase does not include the optional biased model or large-n stress tests.
Plotting
Visual style reference, accessed 2026-09-16: https://github.com/ChenLiu-1996/figures4papers/ Use blue #0F4D92, red #B64342, teal #42949E, violet #9A4D8E; sans-serif labels, frameless legends, no upper/right spines, redundant line styles, white background, vector PDF and 300-dpi PNG. Scientific calculations and plotting implementations are independent of the reference repository. Do not use decorative uncertainty bands for deterministic calculations.
Outputs and versioning
Each invocation creates a new results/run-* directory. Do not overwrite earlier
results. status.json gives actual completion/failure; source hashes identify
the implementation. Results are exploratory finite diagnostics, not a
preregistration or a claim that this is the final paper-ready experiment set.
The manuscript is not modified by this runner.