Plain-English statement
- Box-level signed-face divergence theorem wrapper for ASTIS coordinate divergence. Mathlib's Bochner divergence theorem is stated on `Fin (n + 1) → ℝ`; ASTIS finite Euclidean pointwise calculations use `EuclideanSpace ℝ (Fin (n + 1))`. This theorem only bridges those interfaces under an explicit a.e. equality `hdiv_ae` between the ASTIS coordinate-divergence integrand and Mathlib's trace summand. The conclusion is exactly Mathlib's signed face-term formula. It does not derive `hdiv_ae`, prove box integrability, take a whole-space limit, prove boundary cancellation, perform weighted integration by parts, establish generator domains, or prove invariant/reversible Gibbs laws.
Read the mathematics first, then descend into Lean
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Proof architecture
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How to read the exact Lean declaration
Read a Lean theorem left-to-right exactly as you would unpack a mathematical sentence: name → ambient types → automatically inferred structures → explicit hypotheses → conclusion → proof. Then read the proof top-to-bottom as transformations of the current goal.
- NameWhat reusable mathematical fact is being created?
- ParametersWhich symbols are arbitrary, and which structures are inferred by typeclass search?
- PropositionAfter the colon, translate the Lean expression back into a paper statement.
- Proof actionsAfter
by, ask what each tactic does to the mathematical goal—not only what syntax it uses.
Syntax used on this page
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Source voice and ASTIS voice stay separate
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Lean statement
theorem integral_coordinateDivergence_toPi_box_of_hasFDerivAt_off_countable
{n : ℕ}
(a b : Fin (n + 1) → ℝ) (hle : a ≤ b)
(F : (Fin (n + 1) → ℝ) → Fin (n + 1) → ℝ)
(F' : (Fin (n + 1) → ℝ) →
(Fin (n + 1) → ℝ) →L[ℝ] (Fin (n + 1) → ℝ))
(s : Set (Fin (n + 1) → ℝ)) (hs : s.Countable)
(Hc : ContinuousOn F (Set.Icc a b))
(Hd : ∀ x ∈ (Set.univ.pi fun i => Set.Ioo (a i) (b i)) \ s,
HasFDerivAt F (F' x) x)
(hdiv_ae :
(fun x => coordinateDivergence
(fun y : EuclideanSpace ℝ (Fin (n + 1)) =>
(WithLp.toLp 2 (F (WithLp.ofLp y)) :
EuclideanSpace ℝ (Fin (n + 1))))
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))
=ᵐ[volume.restrict (Set.Icc a b)]
fun x => ∑ i, F' x (Pi.single i (1 : ℝ)) i)
(Hi : IntegrableOn
(fun x => coordinateDivergence
(fun y : EuclideanSpace ℝ (Fin (n + 1)) =>
(WithLp.toLp 2 (F (WithLp.ofLp y)) :
EuclideanSpace ℝ (Fin (n + 1))))
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))
(Set.Icc a b) volume) :
∫ x in Set.Icc a b, coordinateDivergence
(fun y : EuclideanSpace ℝ (Fin (n + 1)) =>
(WithLp.toLp 2 (F (WithLp.ofLp y)) :
EuclideanSpace ℝ (Fin (n + 1))))
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))) =
∑ i : Fin (n + 1),
((∫ x in Set.Icc (a ∘ i.succAbove) (b ∘ i.succAbove),
F (i.insertNth (b i) x) i) -
∫ x in Set.Icc (a ∘ i.succAbove) (b ∘ i.succAbove),
F (i.insertNth (a i) x) i) := by
have Hi_trace : IntegrableOn (fun x => ∑ i, F' x (Pi.single i (1 : ℝ)) i)
(Set.Icc a b) volume :=
Hi.congr_fun_ae hdiv_ae
calc
(∫ x in Set.Icc a b, coordinateDivergence
(fun y : EuclideanSpace ℝ (Fin (n + 1)) =>
(WithLp.toLp 2 (F (WithLp.ofLp y)) :
EuclideanSpace ℝ (Fin (n + 1))))
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1)))) =
∫ x in Set.Icc a b, ∑ i, F' x (Pi.single i (1 : ℝ)) i := by
exact MeasureTheory.integral_congr_ae hdiv_ae
_ = ∑ i : Fin (n + 1),
((∫ x in Set.Icc (a ∘ i.succAbove) (b ∘ i.succAbove),
F (i.insertNth (b i) x) i) -
∫ x in Set.Icc (a ∘ i.succAbove) (b ∘ i.succAbove),
F (i.insertNth (a i) x) i) := by
exact MeasureTheory.integral_divergence_of_hasFDerivAt_off_countable
(a := a) (b := b) hle F F' s hs Hc Hd Hi_trace
/-- Box-level signed-face divergence theorem wrapper for ASTIS coordinate
divergence, using Mathlib's trace-integrability hypothesis directly.
Compared with `integral_coordinateDivergence_toPi_box_of_hasFDerivAt_off_countable`,
this version no longer asks callers to provide the `hdiv_ae` representation
bridge or coordinate-divergence integrability. Both are derived from the
open-box/off-countable derivative hypothesis and the explicit trace-integrability
assumption.
It still proves only the finite-box signed face-term formula. It does not
prove trace integrability for a concrete vector field, whole-space/no-boundary
limits, weighted IBP, generator domains, invariant Gibbs law, reversibility,
stationarity, or KL/FI dissipation. -/
Open AutoSamplingTheory/TechnicalLemmas/Analysis/Calculus/Divergence.lean:584published source at 7bcd37294df1
Proof architecture
Chewi Ch.1 calculus root: integrate ASTIS coordinateDivergence over a finite Mathlib box and obtain only the signed face-term formula, assuming the a.e. bridge to Mathlib's trace integrand and box integrability explicitly
Lean proof walkthrough
- Read the quantified variables and typeclass brackets as part of the mathematical statement; inferred arguments are not missing assumptions.
- `have` creates a named intermediate mathematical fact.
- `calc` records an equality or inequality chain matching a paper calculation.
- `exact` closes the current goal with an already typed term.
Why the statement has this shape
The declaration is kept at the reusable level recorded by its Registry tags and direct consumers. Explicit measures, spaces, wrappers, and regularity hypotheses expose interfaces that paper notation often infers. A theorem card explains those interfaces but never widens the compiled statement.
Hidden assumptions and non-claims
- Measurability is represented explicitly or must be supplied by a dependency.
- Integrability is an input or proved output; a displayed integral alone does not supply it.
- Totalized `fderiv` values must not be read as a differentiability theorem.
- Genuine differentiability is localized to the hypotheses shown in the Lean statement.
- Almost-everywhere hypotheses depend on the stated measure and representative.
- A Gibbs expression is not automatically a probability law or an invariant law.
- A formal generator display does not establish a closed operator domain.