Samplinglib
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ASTIS mathematical exposition

Measurability of the selected real density

AutoSamplingTheory.TechnicalLemmas.InformationTheory.RNLogRatio.measurable_density · theorem · Teaching coverage

Statement

For arbitrary measures μ and π on any measurable space α, the selected real RN function ρ is measurable as a map to ℝ with its Borel measurable structure.

\[\rho:\alpha\to\mathbb R\quad\text{is measurable}.\]

All objects and hypotheses

  • α is any measurable space; no topology, standard-Borel, countability, or nonempty-space hypothesis is imposed.
  • μ and π are arbitrary measures on α unless further conditions are stated; no probability or finite-mass assumption is implicit.
  • Write a(x)=μ.rnDeriv π x∈[0,∞], ρ(x)=a(x).toReal, and r=RNLogRatio.logRatio μ π=MeasureTheory.llr μ π=Real.log ρ. All names refer to the same selected functions for the original pair (μ,π).
  • No absolute-continuity or σ-finiteness assumption is required.

Mathematical proof

1. Use measurability of the selected RN function

Mathlib guarantees measurability even in the fallback case, where the selected function is zero.

\[a:\alpha\to[0,\infty]\quad\text{is measurable}.\]
Corresponding Lean step

MeasureTheory.Measure.measurable_rnDeriv

2. Compose with real conversion

The measurable real conversion of an extended-nonnegative measurable function remains measurable.

\[\rho=\operatorname{toReal}\circ a\quad\text{is measurable}.\]
Corresponding Lean step

Measurable.ennreal_toReal

Lean statement · measurable_density

The conclusion is ordinary measurability of the exact selected function, not an a.e.-measurability claim or a statement about every representative.

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.

theorem measurable_density (mu pi : Measure α) :
    Measurable (density mu pi)

Exact module and namespace context

Lean proof · measurable_density

The proof starts with Mathlib's RN measurability theorem and applies the rule preserving measurability under real conversion.

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.

theorem measurable_density (mu pi : Measure α) :
    Measurable (density mu pi) := by
  exact (Measure.measurable_rnDeriv mu pi).ennreal_toReal

@[fun_prop]

Exact module and namespace context

Scope and omitted-condition boundaries

  • Mathlib's RN derivative is a selected measurable extended-nonnegative function, and defaults to zero if no Lebesgue decomposition exists. ENNReal.toReal sends ∞ to 0; Real.log 0=0. Unconditional naming or measurability is not a reconstruction or positivity theorem.
  • Measurability does not imply integrability, finite entropy, positivity or differentiability.

Source and reuse

ASTIS parents called

Mathlib API called (external library)

  • MeasureTheory.Measure.measurable_rnDeriv
  • Measurable.ennreal_toReal

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.