Plain-English statement
- Finite-box trace integrability for the explicit Gibbs-weighted Langevin trace display, assuming the displayed scalar RHS is continuous on the box. This closes the integrability handoff only under explicit regularity data: the Pi-space vector field has the supplied derivative on the closed box, the pointwise differentiability hypotheses needed by the Langevin display hold on the closed box, and the scalar display `exp (-V) * (Δ f - <∇V, ∇f>)` is continuous on that box. The theorem does not prove those regularity hypotheses, does not prove whole-space integrability, does not cancel finite-box face terms, and does not prove weighted IBP, invariant law, reversibility, stationarity, or KL/FI dissipation.
Read the mathematics first, then descend into Lean
You do not need to know Lean before opening this panel. The page keeps the paper-level theorem, rigorous proof obligations, exact Lean declaration, and proof dependencies as separate layers so a first-time reader can move down one layer at a time.
Proof architecture
Start with the tree when learning: prerequisites sit below the theorem and downstream results sit above it. Switch to the network when you want to understand where this declaration lives in the local formal library. Every mapped node is clickable.
Graph rule: only dependencies found by the ASTIS source scan are drawn. Missing tactic indirection is treated as an under-approximation; the site never invents an edge just to make a prettier graph.
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
This glossary is filtered to syntax that actually occurs in the declaration above. Open a symbol only when you meet it, rather than memorizing Lean grammar in advance.
Source voice and ASTIS voice stay separate
When Samplinglib shows a short quotation from Chewi, it is labeled as a source excerpt and linked to the canonical book page. Intuition, expanded proof steps, hidden regularity assumptions, and Lean explanations are ASTIS-authored commentary. A quotation never substitutes for a formal proof, and an ASTIS explanation is never attributed to the textbook author.
Lean statement
theorem integrableOn_trace_expNeg_fderivCoordinateField_of_continuousOn
{n : ℕ}
(a b : Fin (n + 1) → ℝ)
(V f : EuclideanSpace ℝ (Fin (n + 1)) → ℝ)
(F' : (Fin (n + 1) → ℝ) →
(Fin (n + 1) → ℝ) →L[ℝ] (Fin (n + 1) → ℝ))
(hF : ∀ x ∈ Set.Icc a b,
HasFDerivAt
(fun z : Fin (n + 1) → ℝ => fun i =>
Real.exp (-V (WithLp.toLp 2 z : EuclideanSpace ℝ (Fin (n + 1)))) *
fderiv ℝ f (WithLp.toLp 2 z : EuclideanSpace ℝ (Fin (n + 1)))
(EuclideanSpace.single i (1 : ℝ))) (F' x) x)
(hV : ∀ x ∈ Set.Icc a b,
DifferentiableAt ℝ V
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))
(hfderiv : ∀ x ∈ Set.Icc a b,
DifferentiableAt ℝ
(fun y : EuclideanSpace ℝ (Fin (n + 1)) => fderiv ℝ f y)
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))
(hf : ∀ x ∈ Set.Icc a b,
DifferentiableAt ℝ f
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))
(hcont : ContinuousOn
(fun x : Fin (n + 1) → ℝ =>
Real.exp (-V (WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1)))) *
(Laplacian.laplacian f
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))) -
inner ℝ
(gradient V (WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))
(gradient f (WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))))
(Set.Icc a b)) :
IntegrableOn (fun x => ∑ i, F' x (Pi.single i (1 : ℝ)) i)
(Set.Icc a b) volume := by
have h_exp : IntegrableOn
(fun x : Fin (n + 1) → ℝ =>
Real.exp (-V (WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1)))) *
(Laplacian.laplacian f
(WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))) -
inner ℝ
(gradient V (WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))
(gradient f (WithLp.toLp 2 x : EuclideanSpace ℝ (Fin (n + 1))))))
(Set.Icc a b) volume :=
hcont.integrableOn_compact isCompact_Icc
refine (integrableOn_congr_fun ?_ measurableSet_Icc).mp h_exp
intro x hx
exact (trace_expNeg_fderivCoordinateField_langevinGenerator_display_of_hasFDerivAt
(V := V) (f := f) (x := x) (F' := F' x)
(hF x hx) (hV x hx) (hfderiv x hx) (hf x hx)).symm
/-- Finite-box trace integrability for the explicit Gibbs-weighted Langevin
trace display from component continuity.
This is a convenience wrapper around
`integrableOn_trace_expNeg_fderivCoordinateField_of_continuousOn`. It replaces
the single scalar `ContinuousOn` hypothesis by separate continuity hypotheses
for `V`, `Laplacian.laplacian f`, `gradient V`, and `gradient f`, all after the
`WithLp.toLp 2` coordinate bridge.
It still assumes the explicit Pi-space vector field has the supplied Frechet
derivative on the closed box and that the pointwise differentiability
hypotheses needed by the trace/display equality hold there. It does not derive
those assumptions from a concrete test-function class, does not cancel face
terms, and does not prove weighted IBP, generator domains, invariant laws,
reversibility, stationarity, or KL/FI dissipation. -/
Open AutoSamplingTheory/TechnicalLemmas/StochasticProcesses/Langevin.lean:804published source at 7bcd37294df1
Proof architecture
Chewi Ch.1 Langevin root: finite closed-box handoff proving Mathlib trace-summand `IntegrableOn` for the explicit Gibbs-weighted fderiv-coordinate field when the scalar Langevin display is already continuous on the box
Lean proof walkthrough
- Read the quantified variables and typeclass brackets as part of the mathematical statement; inferred arguments are not missing assumptions.
- `intro` introduces quantified hypotheses into the local proof context.
- `have` creates a named intermediate mathematical fact.
- `refine` instantiates a reusable theorem while leaving explicit subgoals.
- `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.
- A Gibbs expression is not automatically a probability law or an invariant law.
- A formal generator display does not establish a closed operator domain.