Continuous Adapted Modification of the Itô Integral
ProvedLevyStochCalc.Brownian.Ito.exists_continuousAdapted_modification_readableThis theorem constructs a continuous adapted version of the bounded-integrand Itô integral. In addition to the Brownian, filtration, measurability, progressive-measurability, energy, and bound hypotheses, assume that for and that every -null measurable set is measurable in . Then there exists such that
and for every , equals the stochastic integral of up to almost surely. The null-set assumptions are part of the statement.
Original Lean declaration header
Within namespace LevyStochCalc.Brownian.Ito. Shown in its original module context. Proof omitted.
theorem exists_continuousAdapted_modification
(hℱ0 : ∀ t : ℝ, t ≤ 0 → ℱ 0 ≤ ℱ t)
(hnull : ∀ s : Set Ω, MeasurableSet s → P s = 0 → MeasurableSet[ℱ 0] s) :
∃ Y : ℝ → Ω → ℝ, (∀ ω : Ω, Continuous fun t => Y t ω)
∧ (∀ u : ℝ, Measurable[ℱ u] (Y u))
∧ ∀ t : ℝ, 0 ≤ t → Y t =ᵐ[P] stochasticIntegralBrownian W ℱ hℱ H hm hp hq t
Module navigation
Module: LevyStochCalc/Brownian/ItoVersionExists.
Definition modules: LevyStochCalc/Brownian/ItoL2CompletionMaster, LevyStochCalc/Brownian/Filtered, LevyStochCalc/Brownian/Construction, LevyStochCalc/Probability/Progressive.
Supporting theorems: exists_continuous_modification_stochasticIntegralBrownian.
Source excerpt, lines 119–124 · Frozen source 408915f.
import Definitions.Def_KLSModular_LevyStochCalc_Brownian_ItoVersionExists
/-
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/ItoVersionExists.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]
variable {P : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure P] (W : LevyStochCalc.Brownian.BrownianMotion P)
(ℱ : MeasureTheory.Filtration ℝ ‹MeasurableSpace Ω›) (hℱ : LevyStochCalc.Brownian.IsBrownianFiltration W ℱ)
(H : Ω → ℝ → ℝ) (hm : Measurable (Function.uncurry H))
(hp : LevyStochCalc.Probability.ProgressivelyMeasurable ℱ H)
(hq : ∀ T, 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
(‖H ω s‖₊ : ℝ≥0∞) ^ 2 ∂MeasureTheory.MeasureSpace.volume ∂P < ⊤)
{C : ℝ} (hC0 : 0 ≤ C) (hCH : ∀ ω s, |H ω s| ≤ C)
include hℱ hC0 hCH
theorem LevyStochCalc.Brownian.Ito.exists_continuousAdapted_modification_readable
(hℱ0 : ∀ t : ℝ, t ≤ 0 → ℱ 0 ≤ ℱ t)
(hnull : ∀ s : Set Ω, MeasurableSet s → P s = 0 → MeasurableSet[ℱ 0] s) :
∃ Y : ℝ → Ω → ℝ, (∀ ω : Ω, Continuous fun t => Y t ω)
∧ (∀ u : ℝ, Measurable[ℱ u] (Y u))
∧ ∀ t : ℝ, 0 ≤ t → Y t =ᵐ[P] stochasticIntegralBrownian W ℱ hℱ H hm hp hq t := by sorry