Samplinglib
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ASTIS mathematical exposition

A guarded finite Fisher value using the shared energy

AutoSamplingTheory.TechnicalLemmas.InformationTheory.CanonicalRelativeFisher.information · def · Teaching coverage

Statement

Given arbitrary measures μ and π on finite-dimensional Euclidean space and a proof h of the smooth finite score domain, define their canonical relative Fisher value by evaluating the existing RelativeFisher energy with base measure μ, constant weight one, and the selected log-ratio r. Thus the guarded value is the finite integral of the squared classical score of that representative.

\[I_h(\mu\Vert\pi):=\operatorname{RelativeFisher}(\mu,1,r)=\int_E 1\cdot\|\nabla r(x)\|^2\,d\mu(x),\qquad h:\mathcal D(\mu,\pi).\]

All objects and hypotheses

  • ι is a finite index type (Fintype ι), and E = EuclideanSpace ℝ ι has its standard real inner product, norm, topology and Borel measurable structure. Empty ι is allowed; no Nonempty ι assumption is made.
  • μ and π are arbitrary measures on E. No probability, finite-total-mass, or normalization hypothesis is present.
  • Use the exact selected functions ρ(x) = (μ.rnDeriv π x).toReal and r(x) = RNLogRatio.logRatio μ π x = MeasureTheory.llr μ π x = Real.log(ρ(x)); put q(x) = ‖gradient r x‖². These are fixed by the original ordered pair (μ,π), not arbitrary versions.
  • The supplied witness h (or hscore) proves all three conditions: μ ≪ π; r is classically Fréchet differentiable over ℝ at μ-almost every x; and q is μ-integrable (including its a.e. strong measurability and finite integral of its norm).

Construction and meaning

1. Use the explicit domain certificate

The input certificate guarantees a classical score μ-a.e. and integrability of its squared norm. No certificate is inferred from the measures alone.

\[h:\mathcal D(\mu,\pi)\ \Longrightarrow\ q\in L^1(\mu).\]
Corresponding Lean step

_h : SmoothFiniteScoreDomain mu pi

2. Choose the shared energy's three inputs

Set its base measure to μ, its multiplier to the constant function one, and its log-ratio argument to the selected r. Since μ itself is the integration measure, no additional density factor is needed here.

\[(\mathrm{base},\mathrm{weight},\mathrm{logRatio})=(\mu,1,r).\]
Corresponding Lean step

RelativeFisher.information mu (fun _ => 1) (RNLogRatio.logRatio mu pi)

3. Read the constructed value

The shared energy integrates its pointwise weight times squared gradient. The domain's integrability field makes this a genuine finite real integral, not an infinite-energy extension.

\[I_h(\mu\Vert\pi)=\int 1\cdot q\,d\mu=\int q\,d\mu.\]
Corresponding Lean step

RelativeFisher.information; RelativeFisher.densityEnergy

Lean statement · information

The last input is a proof that the pair lies in the stated domain. Although this proof is not used to compute the real-valued expression, requiring it at the interface prevents callers from presenting an unqualified totalized integral as the guarded Fisher value.

Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.

noncomputable def information
    (mu pi : Measure (State (ι := ι)))
    (_h : SmoothFiniteScoreDomain mu pi) : ℝ

Exact module and namespace context

Lean construction · information

This is a definition, not a new integral theorem. It calls the already-existing RelativeFisher functional with μ as the base measure and unit weight. The proof certificate controls admissibility; the numerical expression does not depend on how that certificate was established.

Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.

noncomputable def information
    (mu pi : Measure (State (ι := ι)))
    (_h : SmoothFiniteScoreDomain mu pi) : ℝ :=
  RelativeFisher.information mu (fun _ => 1) (RNLogRatio.logRatio mu pi)

/-- The canonical guarded definition is definitionally the shared
`RelativeFisher` object. -/

Exact module and namespace context

Scope and omitted-condition boundaries

  • This is the selected RN/log-ratio and its totalized classical gradient, not a representative-free Sobolev score. Equality of log-ratios merely a.e. does not by itself identify their gradients. Mathlib sets gradient to zero at nondifferentiable points; the score-domain witness excludes those points only μ-a.e.
  • No existence of the smooth score domain is proved. No weak derivative, Sobolev-domain membership, lower-semicontinuous or extended-valued Fisher extension, or square-root-density identity 4∫‖∇√ρ‖² dπ is established.
  • No second independent Fisher hierarchy is constructed. The codomain is ℝ, and inputs outside the explicit domain have no value through this guarded interface.
  • The domain certificate contains no probability assumption and no finite-entropy assumption; this definition alone gives neither.

Source and reuse

ASTIS parents called

Mathlib API called (external library)

No direct Mathlib call recorded; see the ASTIS parents.

Mathematical sources

ASTIS prose is not a quotation or a source-equivalence certificate. Definitions and aliases are explained as constructions, not counted as new mathematical proofs.