openAI-math-dataset / lean /OAI /Probability /FreeIsing /Stochastic /PlantedBrownianLinearCombination.lean
roseking's picture
Add lean source and binary files (part 122)
b317718 verified
Raw History Blame Contribute Delete
3.89 kB
import OAI.Probability.FreeIsing.Brownian.ArrayMoments
import OAI.Probability.FreeIsing.Brownian.LinearCombination
namespace OAI
noncomputable section
open MeasureTheory ProbabilityTheory
open scoped NNReal
namespace Problem367
lemma iIndepFun_comp_measurePreserving
{ι Ω Ω' E : Type*} [MeasurableSpace Ω] [MeasurableSpace Ω'] [MeasurableSpace E]
{μ : Measure Ω} {ν : Measure Ω'} [IsProbabilityMeasure μ] [IsProbabilityMeasure ν]
{r : Ω → Ω'} (hr : MeasurePreserving r μ ν)
{f : ι → Ω' → E} (hf : ∀ i, Measurable (f i)) (hind : iIndepFun f ν) :
iIndepFun (fun i => f i ∘ r) μ := by
apply (iIndepFun_iff_map_fun_eq_infinitePi_map
(fun i => (hf i).comp hr.measurable)).2
have h := hind.map_fun_eq_infinitePi_map hf
rw [← hr.map_eq] at h
simpa only [Measure.map_map (Measurable.of_eval hf) hr.measurable,
Measure.map_map (hf _) hr.measurable, Function.comp_def] using h
theorem planted_coordinate_paths_iIndepFun
{ι S Ω : Type*} [MeasurableSpace S] [MeasurableSpace Ω]
(ν : Measure S) (μ : ι → Measure Ω) [IsProbabilityMeasure ν]
[∀ i, IsProbabilityMeasure (μ i)]
{B : ι → ℝ≥0 → Ω → ℝ} (hmB : ∀ i t, Measurable (B i t)) :
iIndepFun (fun i (q : S × (ι → Ω)) t => B i t (q.2 i))
(ν.prod (Measure.infinitePi μ)) := by
have hm (i : ι) : Measurable (fun ω t => B i t ω) :=
Measurable.of_eval (hmB i)
exact iIndepFun_comp_measurePreserving measurePreserving_snd
(fun i => (hm i).comp (measurable_pi_apply i)) (iIndepFun_infinitePi hm)
theorem planted_finite_projection_preBrownian
{ι S Ω : Type*} [MeasurableSpace S] [MeasurableSpace Ω]
(ν : Measure S) (μ : ι → Measure Ω) [IsProbabilityMeasure ν]
{B : ι → ℝ≥0 → Ω → ℝ} (hB : ∀ i, IsPreBrownianReal (B i) (μ i))
(hmB : ∀ i t, Measurable (B i t)) (I : Finset ι) (a : ι → ℝ)
(ha : ∑ i ∈ I, a i ^ 2 = 1) :
IsPreBrownianReal (fun t (q : S × (ι → Ω)) => ∑ i ∈ I, a i * B i t (q.2 i))
(ν.prod (Measure.infinitePi μ)) := by
classical
have (i : ι) : IsProbabilityMeasure (μ i) :=
(hB i).isGaussianProcess.isProbabilityMeasure
have hind := (planted_coordinate_paths_iIndepFun ν μ hmB).precomp
(show Function.Injective (fun i : I => (i : ι)) from Subtype.val_injective)
have h := BrownianLinearCombination.isPreBrownianReal_sum
(fun i : I => planted_coordinate_preBrownian ν μ hB i) hind
(fun i : I => a i) (by rw [Finset.sum_coe_sort I (fun i => a i ^ 2)]; exact ha)
convert h using 1
funext t q
exact (Finset.sum_coe_sort I (fun i => a i * B i t (q.2 i))).symm
theorem planted_finite_projection_normalized_preBrownian
{ι S Ω : Type*} [MeasurableSpace S] [MeasurableSpace Ω]
(ν : Measure S) (μ : ι → Measure Ω) [IsProbabilityMeasure ν]
{B : ι → ℝ≥0 → Ω → ℝ} (hB : ∀ i, IsPreBrownianReal (B i) (μ i))
(hmB : ∀ i t, Measurable (B i t)) (I : Finset ι) (a : ι → ℝ)
(ha : 0 < ∑ i ∈ I, a i ^ 2) :
IsPreBrownianReal (fun t (q : S × (ι → Ω)) =>
(Real.sqrt (∑ i ∈ I, a i ^ 2))⁻¹ * ∑ i ∈ I, a i * B i t (q.2 i))
(ν.prod (Measure.infinitePi μ)) := by
classical
have (i : ι) : IsProbabilityMeasure (μ i) :=
(hB i).isGaussianProcess.isProbabilityMeasure
have hind := (planted_coordinate_paths_iIndepFun ν μ hmB).precomp
(show Function.Injective (fun i : I => (i : ι)) from Subtype.val_injective)
have h := BrownianLinearCombination.isPreBrownianReal_normalized_sum
(fun i : I => planted_coordinate_preBrownian ν μ hB i) hind
(fun i : I => a i) (by rw [Finset.sum_coe_sort I (fun i => a i ^ 2)]; exact ha)
convert h using 1
funext t q
rw [Finset.sum_coe_sort I (fun i => a i ^ 2),
Finset.sum_coe_sort I (fun i => a i * B i t (q.2 i))]
end Problem367
end
end OAI