import OAI.Probability.FreeIsing.Brownian.ContinuousExistence import OAI.Probability.FreeIsing.Estimates.UniformSampler import OAI.Probability.FreeIsing.Factors.Transfer namespace OAI noncomputable section open MeasureTheory ProbabilityTheory Filter open scoped NNReal Topology namespace Problem367.WienerSampler abbrev Path := C(ℝ≥0, ℝ) instance pathMeasurableSpace : MeasurableSpace Path := borel Path instance pathBorelSpace : BorelSpace Path := ⟨rfl⟩ theorem measurableEmbedding_denseEval : MeasurableEmbedding (fun f : Path => fun n : ℕ => f (TopologicalSpace.denseSeq ℝ≥0 n)) := by apply Measurable.measurableEmbedding · exact Measurable.of_eval fun index => (continuous_eval_const _).measurable · intro f g h apply ContinuousMap.coe_injective exact (TopologicalSpace.denseRange_denseSeq ℝ≥0).equalizer f.continuous g.continuous h theorem measurable_path_of_eval {Ω : Type*} [MeasurableSpace Ω] {F : Ω → Path} (hF : ∀ t, Measurable (fun ω => F ω t)) : Measurable F := by apply measurableEmbedding_denseEval.measurable_comp_iff.mp exact Measurable.of_eval fun index => hF _ theorem exists_measurable_path_version {Ω : Type*} [MeasurableSpace Ω] (μ : Measure Ω) (B : ℝ≥0 → Ω → ℝ) (hm : ∀ t, Measurable (B t)) (hc : ∀ᵐ ω ∂μ, Continuous (fun t => B t ω)) : ∃ F : Ω → Path, Measurable F ∧ ∀ᵐ ω ∂μ, ∀ t, F ω t = B t ω := by classical obtain ⟨N, hNsub, hNm, hNzero⟩ := exists_measurable_superset_of_null (ae_iff.mp hc) have hcont (ω : Ω) (hω : ω ∉ N) : Continuous (fun t => B t ω) := by by_contra h exact hω (hNsub h) let F : Ω → Path := fun ω => if hω : ω ∈ N then 0 else ⟨fun t => B t ω, hcont ω hω⟩ refine ⟨F, ?_, ?_⟩ · apply measurable_path_of_eval intro t have heq : (fun ω => F ω t) = N.piecewise (fun _ => 0) (B t) := by funext ω by_cases hω : ω ∈ N <;> simp [F, hω, Set.piecewise] rw [heq] exact measurable_const.piecewise hNm (hm t) · have hgood : ∀ᵐ ω ∂μ, ω ∉ N := by simpa only [ae_iff, not_not, Set.ofPred_mem_eq] using hNzero filter_upwards [hgood] with ω hω t simp [F, hω] theorem measurable_brownian_version (t : ℝ≥0) : Measurable (BrownianContinuousExistence.version (fun s (ω : ℝ≥0 → ℝ) => ω s) t) := by exact (StronglyMeasurable.limUnder (fun n => (measurable_pi_apply (Real.toNNReal (ContinuousModification.dyadicLeft t n))).stronglyMeasurable)).measurable theorem isBrownian_eval_map {Ω : Type*} [MeasurableSpace Ω] {μ : Measure Ω} {B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B μ) {F : Ω → Path} (hF : Measurable F) (heq : ∀ᵐ ω ∂μ, ∀ t, F ω t = B t ω) : IsBrownianReal (fun t (f : Path) => f t) (μ.map F) where hasLaw I := by have hI : Measurable (fun f : Path => I.restrict (fun t => f t)) := Measurable.of_eval fun index => (continuous_eval_const index.1).measurable refine ⟨hI.aemeasurable, ?_⟩ rw [Measure.map_map hI hF] have he : (fun ω => I.restrict (fun t => F ω t)) =ᵐ[μ] (fun ω => I.restrict (fun t => B t ω)) := by filter_upwards [heq] with ω hω exact funext (fun i => hω i.1) exact (Measure.map_congr he).trans (hB.hasLaw I).map_eq cont := Filter.Eventually.of_forall (fun f => f.continuous) theorem exists_wienerMeasure : ∃ ν : Measure Path, IsProbabilityMeasure ν ∧ IsBrownianReal (fun t (f : Path) => f t) ν := by let B := BrownianContinuousExistence.version (fun t (ω : ℝ≥0 → ℝ) => ω t) have hB : IsBrownianReal B BrownianExistence.preWienerMeasure := BrownianContinuousExistence.isBrownianReal_version BrownianExistence.coordinate_isPreBrownianReal obtain ⟨F, hF, heq⟩ := exists_measurable_path_version BrownianExistence.preWienerMeasure B measurable_brownian_version hB.cont exact ⟨BrownianExistence.preWienerMeasure.map F, inferInstance, isBrownian_eval_map hB.toIsPreBrownianReal hF heq⟩ def wienerMeasure : Measure Path := Classical.choose exists_wienerMeasure instance wienerProbability : IsProbabilityMeasure wienerMeasure := (Classical.choose_spec exists_wienerMeasure).1 theorem coordinate_isBrownianReal : IsBrownianReal (fun t (f : Path) => f t) wienerMeasure := (Classical.choose_spec exists_wienerMeasure).2 theorem exists_uniform01_wiener_sampler : ∃ ξ : ℝ → Path, Measurable ξ ∧ Measure.map ξ uniform01 = wienerMeasure := exists_uniform01_sampler wienerMeasure theorem isBrownianReal_of_sampler {ξ : ℝ → Path} (hξ : Measurable ξ) (hξlaw : Measure.map ξ uniform01 = wienerMeasure) : IsBrownianReal (fun t u => ξ u t) uniform01 where hasLaw I := (coordinate_isBrownianReal.hasLaw I).comp ⟨hξ.aemeasurable, hξlaw⟩ cont := Filter.Eventually.of_forall (fun u => (ξ u).continuous) def sample : ℝ → Path := Classical.choose exists_uniform01_wiener_sampler theorem measurable_sample : Measurable sample := (Classical.choose_spec exists_uniform01_wiener_sampler).1 theorem map_sample : Measure.map sample uniform01 = wienerMeasure := (Classical.choose_spec exists_uniform01_wiener_sampler).2 theorem sample_isBrownianReal : IsBrownianReal (fun t u => sample u t) uniform01 := isBrownianReal_of_sampler measurable_sample map_sample theorem measurable_sample_eval : Measurable (fun p : ℝ≥0 × ℝ => sample p.2 p.1) := by exact continuous_eval.measurable.comp ((measurable_sample.comp measurable_snd).prodMk measurable_fst) theorem wiener_starts_zero : ∀ᵐ f ∂wienerMeasure, f 0 = 0 := coordinate_isBrownianReal.toIsPreBrownianReal.eval_zero_ae_eq_zero def array (d : ℕ) : (TreeVertex d → ℝ) → (TreeVertex d → Path) := vertexSampler sample theorem measurable_array (d : ℕ) : Measurable (array d) := measurable_vertexSampler measurable_sample theorem map_array (d : ℕ) : Measure.map (array d) (labelMeasure d) = Measure.infinitePi (fun _ : TreeVertex d => wienerMeasure) := by rw [array, map_vertexSampler_labelMeasure measurable_sample, map_sample] theorem array_relabel {d : ℕ} (g : TreeAut d) (u : TreeVertex d → ℝ) : array d (relabel g u) = relabel g (array d u) := rfl theorem array_iIndepFun (d : ℕ) : iIndepFun (fun v (u : TreeVertex d → ℝ) => array d u v) (labelMeasure d) := by exact iIndepFun_infinitePi (fun _ => measurable_sample) theorem array_isBrownianReal {d : ℕ} (v : TreeVertex d) : IsBrownianReal (fun t u => array d u v t) (labelMeasure d) where hasLaw I := by apply (sample_isBrownianReal.hasLaw I).comp exact ⟨(measurable_pi_apply v).aemeasurable, Measure.infinitePi_map_eval (fun _ : TreeVertex d => uniform01) v⟩ cont := Filter.Eventually.of_forall (fun u => (array d u v).continuous) end Problem367.WienerSampler end end OAI