openAI-math-dataset / lean /OAI /Probability /FreeIsing /Conditioning /CopyCompensatedSquare.lean
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import OAI.Probability.FreeIsing.Brownian.RowComparisonConstruction
import OAI.Probability.FreeIsing.Brownian.SpatialPrimitive
import OAI.Probability.FreeIsing.Stochastic.StoppedIntegralAssociativity
namespace OAI
noncomputable section
open MeasureTheory ProbabilityTheory Filter
open scoped NNReal Topology
namespace Problem367.BrownianArrayFiltration
variable {Ω ι : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
theorem compensatedSquare_of_spatial_integral_limits
[Countable ι] [IsProbabilityMeasure P]
{F : Filtration ℝ≥0 mΩ} {B H I : ι → ℝ≥0 → Ω → ℝ}
{Y : ℝ≥0 → Ω → ℝ}
(hB : ∀ a, IsPreBrownianReal (B a) P)
(hAd : ∀ a, StronglyAdapted F (B a))
(hpast : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap
(fun ω a => B a t ω - B a s ω) inferInstance) (F s) P)
(hind : ∀ s t, s ≤ t → Pairwise fun a b =>
IndepFun (fun ω => B a t ω - B a s ω)
(fun ω => B b t ω - B b s ω) P)
(hBc : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => B a t ω))
(hH : ∀ a, IsStronglyProgressive F (H a))
(hc : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => H a t ω))
{C : ι → ℝ} (hC : ∀ a, 0 ≤ C a)
(hb : ∀ a, ∀ᵐ ω ∂P, ∀ t, |H a t ω| ≤ C a)
(henergy : ∀ N : ℕ, Summable (fun a =>
∫ s in (0 : ℝ)..(N : ℝ), ∫ ω, H a s.toNNReal ω ^ 2 ∂P))
(hI2 : ∀ a t, MemLp (I a t) 2 P)
(hYad : StronglyAdapted F Y) (hY2 : ∀ t, MemLp (Y t) 2 P)
(hlim : ∀ a (N : ℕ), 0 < N → ∀ t ≤ (N : ℝ≥0),
Tendsto (fun n => ∫ ω,
(BrownianIntegralProcess.stoppedUniformSum (B a) (H a) N n t ω -
I a t ω) ^ 2 ∂P) atTop (𝓝 0))
(hsum : ∀ t, HasSum (fun a => (hI2 a t).toLp (I a t))
((hY2 t).toLp (Y t))) :
Martingale Y F P ∧
Martingale (fun t ω => Y t ω ^ 2 -
nnrealTimePrimitive (spatialSquareDensity H) t ω) F P := by
obtain ⟨J, Z, hJ2, hZ2, hJ, hJlim, hZp, hZM, hZc, hZ0,
hZiso, hZsum, hZmax, hZQ, hZA, hZseries⟩ :=
exists_global_continuous_spatial_integral_compensatedSquare
hB hAd hpast hind hBc (fun a => (hH a).stronglyAdapted)
hc hC hb henergy
have hIJ (a : ι) (t : ℝ≥0) : I a t =ᵐ[P] J a t := by
obtain ⟨N, htN⟩ := exists_nat_gt (t : ℝ)
have hN : 0 < N := by exact_mod_cast (t.coe_nonneg.trans_lt htN)
have htN' : t ≤ (N : ℝ≥0) := by exact_mod_cast htN.le
apply BrownianGrid.ae_eq_of_mean_square_limits
(fun n => StoppedIntegralAssociativity.stoppedUniformSum_memLp
(fun s => (hB a).isGaussianProcess.hasGaussianLaw_eval s |>.memLp_two)
(hH a).stronglyAdapted (hb a) (N : ℝ≥0) n t)
(hI2 a t) (hJ2 a t)
· exact hlim a N hN t htN'
· exact hJlim a N hN t htN'
have hYZ (t : ℝ≥0) : Y t =ᵐ[P] Z t := by
have heq : (fun a => (hI2 a t).toLp (I a t)) =
(fun a => (hJ2 a t).toLp (J a t)) :=
funext (fun a => MemLp.toLp_congr (hI2 a t) (hJ2 a t) (hIJ a t))
have hs := hsum t
rw [heq] at hs
exact (MemLp.toLp_eq_toLp_iff (hY2 t) (hZ2 t)).mp (hs.unique (hZsum t))
have hQ := compensatedSquare_spatial_primitive hH hc
(fun N => hZseries (N : ℝ≥0)) hZM.stronglyAdapted hZQ
refine ⟨hZM.congr hYad (fun t => (hYZ t).symm), ?_⟩
apply hQ.congr (fun t => ((hYad t).pow 2).sub
(stronglyAdapted_nnrealTimePrimitive (spatialSquareDensity_isStronglyProgressive hH) t))
intro t
filter_upwards [hYZ t] with ω hω
exact congrArg (fun z => z ^ 2 - nnrealTimePrimitive (spatialSquareDensity H) t ω) hω.symm
theorem difference_compensatedSquare_of_spatial_integral_limits
[Countable ι] [IsProbabilityMeasure P]
{F : Filtration ℝ≥0 mΩ} {B H K I J : ι → ℝ≥0 → Ω → ℝ}
{Y Z : ℝ≥0 → Ω → ℝ}
(hB : ∀ a, IsPreBrownianReal (B a) P)
(hAd : ∀ a, StronglyAdapted F (B a))
(hpast : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap
(fun ω a => B a t ω - B a s ω) inferInstance) (F s) P)
(hind : ∀ s t, s ≤ t → Pairwise fun a b =>
IndepFun (fun ω => B a t ω - B a s ω)
(fun ω => B b t ω - B b s ω) P)
(hBc : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => B a t ω))
(hH : ∀ a, IsStronglyProgressive F (H a))
(hK : ∀ a, IsStronglyProgressive F (K a))
(hcH : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => H a t ω))
(hcK : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => K a t ω))
{C D : ι → ℝ} (hC : ∀ a, 0 ≤ C a) (hD : ∀ a, 0 ≤ D a)
(hbH : ∀ a, ∀ᵐ ω ∂P, ∀ t, |H a t ω| ≤ C a)
(hbK : ∀ a, ∀ᵐ ω ∂P, ∀ t, |K a t ω| ≤ D a)
(heH : ∀ N : ℕ, Summable (fun a =>
∫ s in (0 : ℝ)..(N : ℝ), ∫ ω, H a s.toNNReal ω ^ 2 ∂P))
(heK : ∀ N : ℕ, Summable (fun a =>
∫ s in (0 : ℝ)..(N : ℝ), ∫ ω, K a s.toNNReal ω ^ 2 ∂P))
(hI2 : ∀ a t, MemLp (I a t) 2 P) (hJ2 : ∀ a t, MemLp (J a t) 2 P)
(hYad : StronglyAdapted F Y) (hZad : StronglyAdapted F Z)
(hY2 : ∀ t, MemLp (Y t) 2 P) (hZ2 : ∀ t, MemLp (Z t) 2 P)
(hlimI : ∀ a (N : ℕ), 0 < N → ∀ t ≤ (N : ℝ≥0),
Tendsto (fun n => ∫ ω,
(BrownianIntegralProcess.stoppedUniformSum (B a) (H a) N n t ω -
I a t ω) ^ 2 ∂P) atTop (𝓝 0))
(hlimJ : ∀ a (N : ℕ), 0 < N → ∀ t ≤ (N : ℝ≥0),
Tendsto (fun n => ∫ ω,
(BrownianIntegralProcess.stoppedUniformSum (B a) (K a) N n t ω -
J a t ω) ^ 2 ∂P) atTop (𝓝 0))
(hsY : ∀ t, HasSum (fun a => (hI2 a t).toLp (I a t))
((hY2 t).toLp (Y t)))
(hsZ : ∀ t, HasSum (fun a => (hJ2 a t).toLp (J a t))
((hZ2 t).toLp (Z t))) :
Martingale (fun t ω => Y t ω - Z t ω) F P ∧
Martingale (fun t ω => (Y t ω - Z t ω) ^ 2 -
nnrealTimePrimitive
(spatialSquareDensity (fun a t ω => H a t ω - K a t ω)) t ω) F P := by
have hc (a : ι) : ∀ᵐ ω ∂P, Continuous (fun t => H a t ω - K a t ω) := by
filter_upwards [hcH a, hcK a] with ω hω kω
exact hω.sub kω
have hb (a : ι) : ∀ᵐ ω ∂P, ∀ t, |H a t ω - K a t ω| ≤ C a + D a := by
filter_upwards [hbH a, hbK a] with ω hω kω
exact fun t => (abs_sub _ _).trans (add_le_add (hω t) (kω t))
have he (N : ℕ) : Summable (fun a => ∫ s in (0 : ℝ)..(N : ℝ),
∫ ω, (H a s.toNNReal ω - K a s.toNNReal ω) ^ 2 ∂P) := by
by_cases hN : 0 < N
· apply summable_difference_energy_of_row_energies hB hAd hpast H K
(fun a => (hH a).stronglyAdapted) (fun a => (hK a).stronglyAdapted)
hcH hcK C D hC hD hbH hbK (N : ℝ≥0) (heH N) (heK N)
(fun a => hI2 a N) (fun a => hJ2 a N)
· intro a
simpa only [BrownianIntegralProcess.stoppedUniformSum_terminal] using
hlimI a N hN N le_rfl
· intro a
simpa only [BrownianIntegralProcess.stoppedUniformSum_terminal] using
hlimJ a N hN N le_rfl
· have hn : N = 0 := Nat.eq_zero_of_not_pos hN
simp only [hn, Nat.cast_zero, intervalIntegral.integral_same]
exact summable_zero
apply compensatedSquare_of_spatial_integral_limits hB hAd hpast hind hBc
(fun a t => (hH a t).sub (hK a t)) hc (fun a => add_nonneg (hC a) (hD a)) hb he
(fun a t => (hI2 a t).sub (hJ2 a t))
(fun t => (hYad t).sub (hZad t)) (fun t => (hY2 t).sub (hZ2 t))
· intro a N hN t htN
have hM2 (s : ℝ≥0) := (hB a).isGaussianProcess.hasGaussianLaw_eval s |>.memLp_two
have h := SimpleIntegral.meanSquare_limit_sub
(fun n => StoppedIntegralAssociativity.stoppedUniformSum_memLp
hM2 (hH a).stronglyAdapted (hbH a) N n t)
(fun n => StoppedIntegralAssociativity.stoppedUniformSum_memLp
hM2 (hK a).stronglyAdapted (hbK a) N n t)
(hI2 a t) (hJ2 a t) (hlimI a N hN t htN) (hlimJ a N hN t htN)
have heq (n : ℕ) (ω : Ω) :
BrownianIntegralProcess.stoppedUniformSum (B a)
(fun s ω => H a s ω - K a s ω) N n t ω =
BrownianIntegralProcess.stoppedUniformSum (B a) (H a) N n t ω -
BrownianIntegralProcess.stoppedUniformSum (B a) (K a) N n t ω := by
simp only [BrownianIntegralProcess.stoppedUniformSum,
StoppedSimpleIntegral.intervalSum, sub_mul, Finset.sum_sub_distrib]
simpa only [heq, Pi.sub_apply] using h
· intro t
exact (hsY t).sub (hsZ t)
end Problem367.BrownianArrayFiltration
end
end OAI