LeanMachineLearning

MeasureTheory.Measure.dirac_compProd🔗

Lemma

No docstring.

Types
  • β : Type u_2mβ : MeasurableSpace βA measurable space is a space equipped with a σ-algebra.
  • Ω : Type u_4mΩ : MeasurableSpace Ω
Given
  • κ : ProbabilityTheory.Kernel β ΩA kernel from a measurable space α to another measurable space β is a measurable function κ : α → Measure β.ProbabilityTheory.IsSFiniteKernel κA kernel is s-finite if it can be written as the sum of countably many finite kernels.
  • b : β
Then
(dirac b).compProd κ = map (Prod.mk b) (κ b)
Code
lemma _root_.MeasureTheory.Measure.dirac_compProd {κ : Kernel β Ω} [IsSFiniteKernel κ] (b : β) :
    Measure.dirac b ⊗ₘ κ = (κ b).map (Prod.mk b)
Proof
by
  ext s hs
  rw [Measure.compProd_apply hs, lintegral_dirac' _ (Kernel.measurable_kernel_prodMk_left hs),
    Measure.map_apply measurable_prodMk_left hs]

Meaning last changed in v4.34.0-rc2-76-g565f652 (2026-09-10).

Self-contained, with its dependencies inlined and proofs replaced by sorry: download the raw file · open it in the Lean web editor.

Dependency graph

Nothing to draw. Its statement rests on no other declaration in this project, and names nothing from a package left unaudited — so the graph is this declaration alone. That is the answer, not a missing picture.

Audit surface: 0 project declarations, 13 external constants

✓ Proved: no sorry anywhere in its closure

This is the tool's own reading of one build's recorded axioms, and it is not robust against an author who wants it to pass. Checking meant to be relied on should go through Comparator, which replays the proof through the kernel from an export against an explicit list of permitted axioms.