Symmetry of the iterated carré du champ
AutoSamplingTheory.TechnicalLemmas.StochasticProcesses.CarreDuChamp.iteratedCarreDuChamp_comm · theorem · Teaching coverage
Statement
For any type X, real-linear L on real-valued functions, and arbitrary f,g, the functions Γ₂,L(f,g) and Γ₂,L(g,f) agree at every state.
All objects and hypotheses
- X is an arbitrary type, with no measurable-space, topological-space, normed-space, or finiteness hypothesis.
- L:(X→ℝ)→ₗ[ℝ](X→ℝ) is a real-linear operator on all real-valued functions on X. No Markov semigroup or invariant law is supplied.
- f,g:X→ℝ are arbitrary. No measure, topology, or curvature premise.
Mathematical proof
1. Keep the first term fixed using Γ symmetry
The earlier theorem identifies Γ(f,g) and Γ(g,f), so their images under L agree.
Corresponding Lean step
CarreDuChamp.carreDuChamp_comm
2. Swap the remaining terms
After unfolding Γ₂, the other two terms appear in opposite order. Rearranging the subtraction proves the equality pointwise, hence as functions.
Corresponding Lean step
funext x; simp only [iteratedCarreDuChamp, carreDuChamp_comm]; ring
Lean statement · iteratedCarreDuChamp_comm
This is symmetry in the two observable slots, not an integral or spectral symmetry statement.
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 iteratedCarreDuChamp_comm
(generator : (X → ℝ) →ₗ[ℝ] (X → ℝ))
(f g : X → ℝ) :
iteratedCarreDuChamp generator f g =
iteratedCarreDuChamp generator g fLean proof · iteratedCarreDuChamp_comm
The proof unfolds the iterate, reuses symmetry of Γ for its operator input, and rearranges the two real cross terms.
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 iteratedCarreDuChamp_comm
(generator : (X → ℝ) →ₗ[ℝ] (X → ℝ))
(f g : X → ℝ) :
iteratedCarreDuChamp generator f g =
iteratedCarreDuChamp generator g f := by
funext x
simp only [iteratedCarreDuChamp, carreDuChamp_comm]
ring
/-- Chewi Definition 1.2.29: the curvature-dimension condition
`CD(alpha, infinity)`, including the source requirement `alpha > 0`. -/Scope and omitted-condition boundaries
- No global invariant-law, stationarity for every observable, reversibility, semigroup construction, or concrete diffusion identity is inferred from this declaration.
- No curvature or integrated nonnegativity follows merely from this argument symmetry.
Source and reuse
ASTIS parents called
AutoSamplingTheory.TechnicalLemmas.StochasticProcesses.CarreDuChamp.iteratedCarreDuChampAutoSamplingTheory.TechnicalLemmas.StochasticProcesses.CarreDuChamp.carreDuChamp_comm
Mathlib API called (external library)
No direct Mathlib call recorded; see the ASTIS parents.
Mathematical sources
- Exact existing ASTIS declaration — Current statement and body; renderer extracts exact Lean rather than duplicating it in this packet.
ASTIS prose is not a quotation or a source-equivalence certificate. Definitions and aliases are explained as constructions, not counted as new mathematical proofs.