Lag-Constancy Infrastructure for ViaKoopman Proof #
This file contains lag-constancy lemmas for the Koopman-based de Finetti proof:
condexp_pullback_factor- CE pullback along factor maps- LagConstancyProof section with permutation lemmas
setIntegral_eq_of_reindex_eq- Set integral equality via reindexingcondExp_ae_eq_of_setIntegral_diff_eq_zero- CE equality from set integral equalitycondexp_lag_constant_from_exchangeability- Main lag-constancy result
All lemmas in this file are proved (no sorries).
Extracted from: Infrastructure.lean (Part 2/3) Status: Complete (no sorries in proofs)
Factor-map pullback for conditional expectation.
If g : Ω' → Ω is a factor map (i.e., map g μ' = μ), then conditional expectation
pulls back correctly: CE[H | 𝒢] ∘ g = CE[H ∘ g | comap g 𝒢] a.e.
This is the key lemma for transporting conditional expectations between spaces.
Lag-Constancy from Exchangeability: The Transposition Argument #
This section proves that exchangeability implies lag-constancy for conditional expectations. The proof uses Kallenberg's transposition argument:
- For k ≥ 1, the transposition τ = swap(k, k+1) fixes index 0
- Exchangeability gives measure invariance under reindex τ
- Shift-invariant sets are preserved by reindex τ (they depend only on tails)
- Therefore CE[f(ω₀)·g(ω_{k+1}) | ℐ] = CE[f(ω₀)·g(ω_k) | ℐ]
Key lemmas:
shift_reindex_swap_eq: For m > k+1, shift^m ∘ reindex τ = shift^mreindex_swap_preimage_shiftInvariant: Shift-invariant sets are τ-invariantcondexp_lag_constant_from_exchangeability: The main result
Preimages of shift-invariant sets under reindex (swap k (k+1)) are the same set.
Proof strategy: A set s is shift-invariant iff membership depends only on tails. Since swap k (k+1) only affects coordinates k and k+1, for any n > k+1, the n-tail of ω equals the n-tail of (reindex τ ω). By shift-invariance, membership in s is determined by any tail, hence ω ∈ s ↔ (reindex τ ω) ∈ s.
Generalized reindex preimage invariance: For any permutation π that is identity beyond some bound M, shift-invariant sets are reindex-invariant.
This generalizes reindex_swap_preimage_shiftInvariant from transpositions to arbitrary
finite-support permutations. The proof uses the same key insight: shift^[M] commutes with
reindex π when π is identity beyond M, so membership in shift-invariant sets is preserved.
Cycle permutation for lag constancy #
A cycle on [L, R] that maps n → n-1 (for L < n ≤ R) and L → R. This is useful for proving lag constancy of cylinder sets: it shifts coordinates down by 1 within the range, wrapping L to R.
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The cycle is identity beyond R.
Disjoint offset swap permutation #
For shifting cylinders from coords {i : i ∈ S} to {offset + i : i ∈ S} while fixing coords outside.
This is used in h_shift_to_N₀ to show CE[φ(ω_k) · 1_B | mSI] = CE[φ(ω_k) · 1_{B_at N₀} | mSI].
Permutation that swaps i ↔ offset+i for all i in a finite set S, where all elements of S are less than offset. This is an involution.
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For exchangeable measures, set integrals are equal for functions that agree on reindexing. This is a key step in proving lag-constancy: ∫_s F = ∫_s G when F ∘ reindex τ = G and the set s is shift-invariant (hence also reindex-invariant).
If ∫_s (F - G) = 0 for all s in sub-σ-algebra, then CE[F|m] = CE[G|m] a.e.
Lag-constancy from exchangeability via transpositions (Kallenberg's approach).
For EXCHANGEABLE measures μ on path space, the conditional expectation CE[f(ω₀)·g(ω_{k+1}) | ℐ] equals CE[f(ω₀)·g(ω_k) | ℐ] for k ≥ 1.
Key insight: This uses EXCHANGEABILITY (not just stationarity). The proof is:
- Let τ be the transposition swapping indices k and k+1
- Exchangeability gives: Measure.map (reindex τ) μ = μ
- Since k ≥ 1, τ fixes 0: τ(0) = 0
- Therefore: CE[f(ω₀)·g(ω_{k+1}) | ℐ] = CE[(f∘τ)(ω₀)·(g∘τ)(ω_{k+1}) | ℐ] = CE[f(ω₀)·g(ω_k) | ℐ]
Why k ≥ 1 is required (CRITICAL):
- When k=0, τ = swap(0, 1) does NOT fix 0 (τ sends 0 ↦ 1)
- So (f∘τ)(ω₀) = f(ω₁) ≠ f(ω₀), breaking the argument
- Counterexample for k=0: i.i.d. Bernoulli(1/2):
- CE[ω₀·ω₁ | ℐ] = E[ω₀]·E[ω₁] = 1/4
- CE[ω₀² | ℐ] = E[ω₀²] = 1/2 (since ω₀ ∈ {0,1})
- These are NOT equal!
Why stationarity alone is NOT enough: Stationary non-exchangeable processes (Markov chains, AR processes) can have lag-dependent conditional correlations. The transposition trick requires the FULL permutation invariance of exchangeability.