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L¹ Defect Bound for Vector Itô Formula

Proved
LevyStochCalc.Brownian.Ito.IsVectorItoVersion.integral_abs_vectorItoFormula_le_readable

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

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

This theorem bounds the L¹ defect of the vector Itô formula on a uniform grid. Let (Ω, P) be a probability space, W a d-dimensional Brownian motion, ℱ a filtration, H a progressively measurable diffusion coefficient with the stated coordinatewise ENNReal square-energy conditions, and X a vector Itô version with initial value X₀ and drift bdrift. Assume H is bounded by C ≥ 0, the initial value and drift are measurable, and the drift is bounded by B ≥ 0. Let f : (Fin n → ℝ) → ℝ have everywhere-defined first and second Fréchet derivatives f′ and f″; assume ‖f′(z)‖ ≤ K₁, 0 ≤ K₂, ‖f″(z)‖ ≤ K₂, f″ is continuous, and ‖f″(z) − f″(w)‖ ≤ A + K‖z − w‖ with A, K ≥ 0. Assume the products involving coordDeriv f′ and H are measurable, progressively measurable, and have finite ENNReal square energy. For T > 0 and m ≠ 0, the Itô defect is integrable and

∫ ⁣∣f(XT)−f(X0)−(DT+MT+12QT)∣dP≤vectorItoGridError⁡(n,d,B,C,T,A,K,K2,T/m),\int\!\left|f(X_T)-f(X_0)-\left(D_T+M_T+\tfrac12 Q_T\right)\right|dP\le \operatorname{vectorItoGridError}(n,d,B,C,T,A,K,K_2,T/m),∫​f(XT​)−f(X0​)−(DT​+MT​+21​QT​)​dP≤vectorItoGridError(n,d,B,C,T,A,K,K2​,T/m),

where D_T, M_T, and Q_T are respectively the drift integral, stochastic-integral term, and quadratic-variation term displayed in the declaration. This is the quantitative finite-grid statement used to pass from the grid decomposition to vector Itô’s formula.

Original Lean conclusion excerpt

Within namespace LevyStochCalc.Brownian.Ito. Shown in its original module context. Earlier hypotheses and the proof are omitted from this excerpt; the complete verified statement remains below.

          + 1 / 2 * ∑ p : Fin n, ∑ q : Fin n, ∫ s in Set.Ioc (0 : ℝ) T,
              coordDeriv₂ f'' p q (X s ω) * ∑ k : Fin d, H p k ω s * H q k ω s ∂volume)) P
      ∧ ∫ ω, |f (X T ω) - f (X 0 ω)
          - ((∑ p : Fin n, ∫ s in Set.Ioc (0 : ℝ) T,
                coordDeriv f' p (X s ω) * bdrift p ω s ∂volume)
            + (∑ p : Fin n, ∑ k : Fin d, stochasticIntegralBrownian (W.W k) ℱ (hcoord k)
                (fun ω s => coordDeriv f' p (X s ω) * H p k ω s)
                (hmg p k) (hpg p k) (hqg p k) T ω)
            + 1 / 2 * ∑ p : Fin n, ∑ q : Fin n, ∫ s in Set.Ioc (0 : ℝ) T,
                coordDeriv₂ f'' p q (X s ω)
                  * ∑ k : Fin d, H p k ω s * H q k ω s ∂volume)| ∂P
        ≤ vectorItoGridError (n : ℝ) (d : ℝ) B C T A K K₂ (T / (m : ℝ))

Module navigation

Module: LevyStochCalc/Brownian/VectorItoFormula.

Definition modules: LevyStochCalc/Brownian/ItoL2CompletionMaster, LevyStochCalc/Brownian/Filtered, LevyStochCalc/Brownian/Multidim, LevyStochCalc/Brownian/CoordDerivative, LevyStochCalc/Probability/Progressive, LevyStochCalc/Brownian/VectorItoProcessVersion.

Selected supporting theorems: IsVectorItoVersion.integral_abs_frozenRiemann_sub_le, IsVectorItoVersion.integral_abs_quadVarRiemann_sub_le, IsVectorItoVersion.lintegral_sq_martingaleRiemann_sub_le, IsVectorItoVersion.vectorItoFormula_decomp_ae, integral_abs_le_sqrt_of_lintegral_sq_le.

Next: IsVectorItoVersion.itoFormula.

Source excerpt, lines 137–148 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_LevyStochCalc_Brownian_VectorItoFormula

/-
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/VectorItoFormula.lean; Apache-2.0; provenance in formalization/vendor/vendor-lock.json of the KLS repository)
open MeasureTheory ProbabilityTheory
open scoped NNReal ENNReal Topology
universe u
variable {Ω : Type u} [MeasurableSpace Ω] {P : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure P]
  {n d : ℕ} {W : LevyStochCalc.Brownian.Multidim.MultidimBrownianMotion P d}
  {ℱ : MeasureTheory.Filtration ℝ ‹MeasurableSpace Ω›}
  {hcoord : ∀ k : Fin d, LevyStochCalc.Brownian.IsBrownianFiltration (W.W k) ℱ}
  {H : Fin n → Fin d → Ω → ℝ → ℝ}
  {hHm : ∀ p k, Measurable (Function.uncurry (H p k))}
  {hHp : ∀ p k, LevyStochCalc.Probability.ProgressivelyMeasurable ℱ (H p k)}
  {hHs : ∀ (p : Fin n) (k : Fin d) (T : ℝ), 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
    (‖H p k ω s‖₊ : ℝ≥0∞) ^ 2 ∂MeasureTheory.MeasureSpace.volume ∂P < ⊤}
  {X₀ : Ω → Fin n → ℝ} {bdrift : Fin n → Ω → ℝ → ℝ} {X : ℝ → Ω → Fin n → ℝ}
  {C : ℝ} (hC0 : 0 ≤ C)
  (hCH : ∀ (p : Fin n) (k : Fin d) (ω : Ω) (s : ℝ), |H p k ω s| ≤ C)
include hC0 hCH
Formal statement

theorem LevyStochCalc.Brownian.Ito.IsVectorItoVersion.integral_abs_vectorItoFormula_le_readable
    (h : IsVectorItoVersion W ℱ hcoord H hHm hHp hHs X₀ bdrift X)
    (hX₀ : ∀ p : Fin n, Measurable fun ω => X₀ ω p)
    (hbm : ∀ p, Measurable (Function.uncurry (bdrift p))) {B : ℝ} (hB0 : 0 ≤ B)
    (hB : ∀ (p : Fin n) (ω : Ω) (s : ℝ), |bdrift p ω s| ≤ B)
    (hma : ∀ (p q : Fin n) (k : Fin d),
      Measurable (Function.uncurry fun ω s => H p k ω s + H q k ω s))
    (hpa : ∀ (p q : Fin n) (k : Fin d),
      Probability.ProgressivelyMeasurable ℱ fun ω s => H p k ω s + H q k ω s)
    (hqa : ∀ (p q : Fin n) (k : Fin d) (T' : ℝ), 0 < T' → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T',
      (‖H p k ω s + H q k ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
    {f : (Fin n → ℝ) → ℝ} {f' : (Fin n → ℝ) → (Fin n → ℝ) →L[ℝ] ℝ}
    {f'' : (Fin n → ℝ) → (Fin n → ℝ) →L[ℝ] (Fin n → ℝ) →L[ℝ] ℝ}
    (hf : ∀ z, HasFDerivAt f (f' z) z) (hf' : ∀ z, HasFDerivAt f' (f'' z) z)
    {K₁ : ℝ} (hf'bd : ∀ z, ‖f' z‖ ≤ K₁)
    {K₂ : ℝ} (hK₂0 : 0 ≤ K₂) (hf''bd : ∀ z, ‖f'' z‖ ≤ K₂)
    {A K : ℝ} (hA0 : 0 ≤ A) (hK0 : 0 ≤ K) (hf''c : Continuous f'')
    (hf''aff : ∀ z w, ‖f'' z - f'' w‖ ≤ A + K * ‖z - w‖)
    (hmg : ∀ (p : Fin n) (k : Fin d),
      Measurable (Function.uncurry fun ω s => coordDeriv f' p (X s ω) * H p k ω s))
    (hpg : ∀ (p : Fin n) (k : Fin d), Probability.ProgressivelyMeasurable ℱ
      fun ω s => coordDeriv f' p (X s ω) * H p k ω s)
    (hqg : ∀ (p : Fin n) (k : Fin d) (T' : ℝ), 0 < T' → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T',
      (‖coordDeriv f' p (X s ω) * H p k ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
    {T : ℝ} (hT : 0 < T) {m : ℕ} (hm0 : m ≠ 0) :
    Integrable (fun ω : Ω => f (X T ω) - f (X 0 ω)
        - ((∑ p : Fin n, ∫ s in Set.Ioc (0 : ℝ) T,
              coordDeriv f' p (X s ω) * bdrift p ω s ∂volume)
          + (∑ p : Fin n, ∑ k : Fin d, stochasticIntegralBrownian (W.W k) ℱ (hcoord k)
              (fun ω s => coordDeriv f' p (X s ω) * H p k ω s)
              (hmg p k) (hpg p k) (hqg p k) T ω)
          + 1 / 2 * ∑ p : Fin n, ∑ q : Fin n, ∫ s in Set.Ioc (0 : ℝ) T,
              coordDeriv₂ f'' p q (X s ω) * ∑ k : Fin d, H p k ω s * H q k ω s ∂volume)) P
      ∧ ∫ ω, |f (X T ω) - f (X 0 ω)
          - ((∑ p : Fin n, ∫ s in Set.Ioc (0 : ℝ) T,
                coordDeriv f' p (X s ω) * bdrift p ω s ∂volume)
            + (∑ p : Fin n, ∑ k : Fin d, stochasticIntegralBrownian (W.W k) ℱ (hcoord k)
                (fun ω s => coordDeriv f' p (X s ω) * H p k ω s)
                (hmg p k) (hpg p k) (hqg p k) T ω)
            + 1 / 2 * ∑ p : Fin n, ∑ q : Fin n, ∫ s in Set.Ioc (0 : ℝ) T,
                coordDeriv₂ f'' p q (X s ω)
                  * ∑ k : Fin d, H p k ω s * H q k ω s ∂volume)| ∂P
        ≤ vectorItoGridError (n : ℝ) (d : ℝ) B C T A K K₂ (T / (m : ℝ)) := by sorry
Source
Lean source: https://github.com/cgarryZA/LevyStochCalc/blob/984dbf0b790031eac05d56fe5a84b65e15e1e932/LevyStochCalc/Brownian/VectorItoFormula.lean#L104-L354 (repository human-ai-mathematics/kls-lean, commit 408915f, module `LevyStochCalc.Brownian.VectorItoFormula`, declaration `LevyStochCalc.Brownian.Ito.IsVectorItoVersion.integral_abs_vectorItoFormula_le`; 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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