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Orthogonality of Itô Integrals on Distinct Brownian Coordinates

Proved
LevyStochCalc.Brownian.Multidim.MultidimBrownianMotion.integral_stochasticIntegral_mul_eq_zero_readable

by Lazyfill · Oct 26, 2026 · Mathlib 0df444a (Lean v4.33.1)

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concavevendored-levystochcalc

This is the orthogonality identity for Itô integrals driven by distinct coordinates of a multidimensional Brownian motion.

Let WWW be a ddd-dimensional Brownian motion, let i≠ji\ne ji=j, and let F\mathcal FF be a common Brownian filtration. Let HHH and KKK be measurable and progressively measurable integrands whose integrated squared norms are finite in ENNReal\mathrm{ENNReal}ENNReal on every positive interval. For t≥0t\ge0t≥0, the corresponding scalar Itô integrals satisfy

∫Iti(ω)Itj(ω) dP=0,\int I^i_t(\omega)I^j_t(\omega)\,dP=0,∫Iti​(ω)Itj​(ω)dP=0,

where Iti=stochasticIntegral(Wi,F,H,t)I^i_t=\texttt{stochasticIntegral}(W^i,\mathcal F,H,t)Iti​=stochasticIntegral(Wi,F,H,t) and Itj=stochasticIntegral(Wj,F,K,t)I^j_t=\texttt{stochasticIntegral}(W^j,\mathcal F,K,t)Itj​=stochasticIntegral(Wj,F,K,t).

The statement is the general orthogonality result obtained from elementary-integrand orthogonality and L2L^2L2 convergence.

Formalization Note The square-integrability hypotheses are expressed through MemLp in the supporting declarations, while the integrand assumptions use ENNReal\mathrm{ENNReal}ENNReal lower integrals.

Original Lean declaration header

Within namespace LevyStochCalc.Brownian.Multidim.MultidimBrownianMotion. Shown in its original module context. Proof omitted.

theorem integral_stochasticIntegral_mul_eq_zero (W : MultidimBrownianMotion P d)
    {ℱ : Filtration ℝ ‹MeasurableSpace Ω›} {i j : Fin d} (hij : i ≠ j)
    (hcoord : ∀ k : Fin d, IsBrownianFiltration (W.W k) ℱ)
    {H K : Ω → ℝ → ℝ} (hHm : Measurable (Function.uncurry H))
    (hHp : Probability.ProgressivelyMeasurable ℱ H)
    (hHs : ∀ T : ℝ, 0 < T →
      ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T, (‖H ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
    (hKm : Measurable (Function.uncurry K))
    (hKp : Probability.ProgressivelyMeasurable ℱ K)
    (hKs : ∀ T : ℝ, 0 < T →
      ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T, (‖K ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
    {t : ℝ} (ht : 0 ≤ t) :
    ∫ ω, stochasticIntegral (W.W i) ℱ (hcoord i) H hHm hHp hHs t ω
      * stochasticIntegral (W.W j) ℱ (hcoord j) K hKm hKp hKs t ω ∂P = 0

Module navigation

Module: LevyStochCalc/Brownian/CrossOrthogonalityLimit.

Definition modules: LevyStochCalc/Brownian/ItoL2CompletionApi, LevyStochCalc/Brownian/Filtered, LevyStochCalc/Brownian/Multidim, LevyStochCalc/Probability/Progressive.

Supporting theorems: integral_mul_eq_zero_of_tendsto_eLpNorm, integral_simpleIntegral_mul_eq_zero, memLp_simpleIntegral.

Previous: integral_mul_eq_zero_of_tendsto_eLpNorm.

Source excerpt, lines 371–384 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_LevyStochCalc_Brownian_CrossOrthogonalityLimit

/-
Copyright (c) 2026 Christian Garry. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Christian Garry
-/
-- Vendored from https://github.com/cgarryZA/LevyStochCalc at commit 984dbf0b790031eac05d56fe5a84b65e15e1e932 (upstream path LevyStochCalc/Brownian/CrossOrthogonalityLimit.lean; Apache-2.0; provenance in formalization/vendor/vendor-lock.json of the KLS repository)
open MeasureTheory ProbabilityTheory
open scoped NNReal ENNReal
universe u
variable {Ω : Type u} [MeasurableSpace Ω] {P : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure P] {d : ℕ}
open LevyStochCalc.Brownian.Ito
Formal statement

theorem LevyStochCalc.Brownian.Multidim.MultidimBrownianMotion.integral_stochasticIntegral_mul_eq_zero_readable (W : MultidimBrownianMotion P d)
    {ℱ : Filtration ℝ ‹MeasurableSpace Ω›} {i j : Fin d} (hij : i ≠ j)
    (hcoord : ∀ k : Fin d, IsBrownianFiltration (W.W k) ℱ)
    {H K : Ω → ℝ → ℝ} (hHm : Measurable (Function.uncurry H))
    (hHp : Probability.ProgressivelyMeasurable ℱ H)
    (hHs : ∀ T : ℝ, 0 < T →
      ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T, (‖H ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
    (hKm : Measurable (Function.uncurry K))
    (hKp : Probability.ProgressivelyMeasurable ℱ K)
    (hKs : ∀ T : ℝ, 0 < T →
      ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T, (‖K ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
    {t : ℝ} (ht : 0 ≤ t) :
    ∫ ω, stochasticIntegral (W.W i) ℱ (hcoord i) H hHm hHp hHs t ω
      * stochasticIntegral (W.W j) ℱ (hcoord j) K hKm hKp hKs t ω ∂P = 0 := by sorry
Source
Lean source: https://github.com/cgarryZA/LevyStochCalc/blob/984dbf0b790031eac05d56fe5a84b65e15e1e932/LevyStochCalc/Brownian/CrossOrthogonalityLimit.lean#L370-L399 (repository human-ai-mathematics/kls-lean, commit 408915f, module `LevyStochCalc.Brownian.CrossOrthogonalityLimit`, declaration `LevyStochCalc.Brownian.Multidim.MultidimBrownianMotion.integral_stochasticIntegral_mul_eq_zero`; the repository is private at upload time). Vendored from https://github.com/cgarryZA/LevyStochCalc at commit 984dbf0b790031eac05d56fe5a84b65e15e1e932 (Apache-2.0; upstream copyright notice retained in the Lean text).

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