Regression artifact, evidence, and execution status

The embedded program checks:

1. exact interval-overlap boundaries;

2. independently assembled matched quadratic generators in a synthetic seven-label protocol;

3. the matched total heating coefficient;

4. constant and quadratic nuisance cancellation;

5. the rational $-5041/81920$ sphere contrast;

6. the exact-rational uniform small-smearing lower certificate;

7. separation-error and visibility-to-log interval propagation;

8. a bounded common event gap for complete synthetic histograms;

9. negative controls: quadratic gravity, free preparation offsets, and a flat detector.

The default spectral integrations are floating-point diagnostics. They are not labelled validated continuum computations. The optional –validated calculation encloses $b(1/2)$ using exact rational nodal intervals and Proposition prop:quadrature. Its printed decimal endpoints are presentations of the enclosing rational numbers recorded in the manifest.

The staged matrix model is synthetic. Its Hamiltonians, units, packet, instruments, and efficiencies are not the reference apparatus. The survival of exact matching in this regression illustrates the written theorem but is not its proof.

Optional Matplotlib output includes:

1. regularized contrast diagnostics with the analytic certified small-width region;

2. the quadratic overlap surface versus strength and regularization;

3. complete synthetic histograms;

4. a hypothetical log-contrast sample budget versus calibration width.

A successful local invocation writes the SHA-256, environment, execution time, and results in En01-B-run.json. No invocation or compilation is claimed here.