Samplinglib
Lean gate passed 2026-08-19T06:04:36.257124+00:00 · 77184245109a
11.3 · Book p. 276 · PDF p. 288

Applications of Fisher Information Bounds

Applies Fisher-information guarantees to concrete nonconvex sampling and statistical tasks.

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Place in the proof route

The chapter uses this material in the route toward Small Fisher information provides a meaningful stationarity certificate for non-log-concave targets. The declaration-level source map is intentionally left inside the formalization layer until exact theorem anchors have been audited.

Why is this valid?

Chapter-level validity conditions

  • Relative Fisher information needs an absolutely continuous law and a chosen score representative.
  • Entropy dissipation must be justified for the actual process and function domain, not only calculated formally.
  • Randomized-time output requires measurability of the time-indexed law and Fisher-information integrand.
  • Finite-time discretization and score-error bounds must specify the law under which every squared error is integrated.
  • Small Fisher information is a stationarity certificate, not automatically small total variation or rapid multimodal mixing.
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No declaration-level mapping has been accepted for this section. This is a route status, not a failed Lean declaration.