Additivity of the Brownian Itô Integral
ProvedLevyStochCalc.Brownian.Ito.stochasticIntegralBrownian_add_readableThis statement establishes additivity of the L² Brownian Itô integral in its integrand. Let be a probability space, let be a Brownian motion under , and let be a filtration for which is Brownian. Let be jointly measurable and progressively measurable. Assume that, for every , the squared-energy integrals of , , and are finite in .
For every , the integral of the pointwise sum agrees -almost everywhere with the sum of the two integrals:
Here each displayed energy is an iterated ENNReal integral of the squared nnnorm, and all measurability, progressive-measurability, and finiteness hypotheses are explicit. The result is the basic linearity lemma used to obtain finite-sum and scalar-multiplication identities.
Original Lean declaration header
Within namespace LevyStochCalc.Brownian.Ito. Shown in its original module context. Proof omitted.
theorem stochasticIntegralBrownian_add {H₁ H₂ : Ω → ℝ → ℝ}
(hm₁ : Measurable (Function.uncurry H₁)) (hm₂ : Measurable (Function.uncurry H₂))
(hp₁ : Probability.ProgressivelyMeasurable ℱ H₁)
(hp₂ : Probability.ProgressivelyMeasurable ℱ H₂)
(hq₁ : ∀ T, 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
(‖H₁ ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
(hq₂ : ∀ T, 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
(‖H₂ ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
(hma : Measurable (Function.uncurry fun ω s => H₁ ω s + H₂ ω s))
(hpa : Probability.ProgressivelyMeasurable ℱ fun ω s => H₁ ω s + H₂ ω s)
(hqa : ∀ T, 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
(‖H₁ ω s + H₂ ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
{T : ℝ} (hT : 0 < T) :
stochasticIntegralBrownian W ℱ hℱ (fun ω s => H₁ ω s + H₂ ω s) hma hpa hqa T
=ᵐ[P] fun ω => stochasticIntegralBrownian W ℱ hℱ H₁ hm₁ hp₁ hq₁ T ω
+ stochasticIntegralBrownian W ℱ hℱ H₂ hm₂ hp₂ hq₂ T ω
Module navigation
Module: LevyStochCalc/Brownian/ItoLinear.
Definition modules: LevyStochCalc/Brownian/ItoL2CompletionMaster, LevyStochCalc/Brownian/Filtered, LevyStochCalc/Brownian/Construction, LevyStochCalc/Probability/Progressive.
Supporting theorems: ae_eq_add_of_sq_distances, lintegral_energy_lt_top_of_bound, lintegral_energy_parallelogram.
Previous: ae_eq_add_of_sq_distances · Next: ae_eq_const_mul_of_sq_distances.
Source excerpt, lines 257–272 · Frozen source 408915f.
import Definitions.Def_KLSModular_LevyStochCalc_Brownian_ItoLinear
/-
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/ItoLinear.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]
variable (W : LevyStochCalc.Brownian.BrownianMotion P)
(ℱ : MeasureTheory.Filtration ℝ ‹MeasurableSpace Ω›) (hℱ : LevyStochCalc.Brownian.IsBrownianFiltration W ℱ)
include hℱ
theorem LevyStochCalc.Brownian.Ito.stochasticIntegralBrownian_add_readable {H₁ H₂ : Ω → ℝ → ℝ}
(hm₁ : Measurable (Function.uncurry H₁)) (hm₂ : Measurable (Function.uncurry H₂))
(hp₁ : Probability.ProgressivelyMeasurable ℱ H₁)
(hp₂ : Probability.ProgressivelyMeasurable ℱ H₂)
(hq₁ : ∀ T, 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
(‖H₁ ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
(hq₂ : ∀ T, 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
(‖H₂ ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
(hma : Measurable (Function.uncurry fun ω s => H₁ ω s + H₂ ω s))
(hpa : Probability.ProgressivelyMeasurable ℱ fun ω s => H₁ ω s + H₂ ω s)
(hqa : ∀ T, 0 < T → ∫⁻ ω, ∫⁻ s in Set.Icc (0 : ℝ) T,
(‖H₁ ω s + H₂ ω s‖₊ : ℝ≥0∞) ^ 2 ∂volume ∂P < ⊤)
{T : ℝ} (hT : 0 < T) :
stochasticIntegralBrownian W ℱ hℱ (fun ω s => H₁ ω s + H₂ ω s) hma hpa hqa T
=ᵐ[P] fun ω => stochasticIntegralBrownian W ℱ hℱ H₁ hm₁ hp₁ hq₁ T ω
+ stochasticIntegralBrownian W ℱ hℱ H₂ hm₂ hp₂ hq₂ T ω := by sorry