import Mathlib import OAI.Probability.JammingConcavity.FamilyPositiveTotal namespace OAI /-! Cascade Path Coordinates. -/ noncomputable section open MeasureTheory ProbabilityTheory Set open scoped NNReal ENNReal open Set Filter open scoped Topology open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators open MeasureTheory Filter Set open scoped ENNReal NNReal BigOperators open MeasureTheory ProbabilityTheory Set Filter open scoped ENNReal NNReal Topology open scoped NNReal ENNReal Topology open scoped NNReal Topology open Set open Set Filter MeasureTheory open scoped BigOperators open scoped Topology NNReal open scoped Topology BigOperators open scoped ENNReal NNReal open MeasureTheory Set open MeasureTheory ProbabilityTheory open scoped ENNReal NNReal BigOperators Classical open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators open Classical namespace MicroscopicJamming def cascadePathIndex : (k : ℕ) → CascadePath k → Fin k → CascadeMarkIndex k | 0, _, j => Fin.elim0 j | k+1, ℓ, j => Fin.cases (ℓ.1.1,ℓ.1.2,none) (fun j => (ℓ.1.1,ℓ.1.2,some (cascadePathIndex k ℓ.2 j))) j lemma cascadePathIndex_depth (k : ℕ) (ℓ : CascadePath k) (j : Fin k) : cascadeMarkDepth k (cascadePathIndex k ℓ j) = j := by induction k with | zero => exact Fin.elim0 j | succ k ih => refine Fin.cases ?_ (fun i => ?_) j · rfl · change cascadeMarkDepth k (cascadePathIndex k ℓ.2 i)+1 = i.val+1 rw [ih] lemma cascadePathIndex_injective (k : ℕ) (ℓ : CascadePath k) : Function.Injective (cascadePathIndex k ℓ) := by intro i j h apply Fin.ext simpa only [cascadePathIndex_depth] using congrArg (cascadeMarkDepth k) h lemma familyPathMark_zip {E : Type} [AddCommMonoid E] (k : ℕ) (x : E) (ω : CascadeTree k) (y : CascadeMarkTree E k) (ℓ : CascadePath k) : familyPathMark k x (zipCascade k (ω,y)) ℓ = x+∑ j : Fin k, cascadeMarkCoordinates k y (cascadePathIndex k ℓ j) := by induction k generalizing x with | zero => simp [familyPathMark] | succ k ih => change familyPathMark k (x+(y ℓ.1.1 ℓ.1.2).1) (zipCascade k (((ω ℓ.1.1).2 ℓ.1.2).2,(y ℓ.1.1 ℓ.1.2).2)) ℓ.2 = _ rw [ih, Fin.sum_univ_succ] simp only [cascadePathIndex] exact add_assoc _ _ _ lemma familyPathMark_coordinates {E : Type} [AddCommMonoid E] (k : ℕ) (x : E) (ω : CascadeTree k) (y : CascadeMarkTree E k) (ℓ : CascadePath k) : familyPathMark k x (zipCascade k (ω,y)) ℓ = x+∑ i ∈ Finset.univ.image (cascadePathIndex k ℓ), cascadeMarkCoordinates k y i := by rw [familyPathMark_zip, Finset.sum_image] exact fun i _ j _ h => cascadePathIndex_injective k ℓ h end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators namespace MicroscopicJamming lemma measurable_familyPathWeight {E : Type} [MeasurableSpace E] (ms : List ℝ) (ℓ : CascadePath ms.length) : Measurable (fun ω => familyPathWeight (E := E) ms ω ℓ) := by induction ms with | nil => exact measurable_const | cons m ms ih => change Measurable (fun ω : PointCloud (E × FamilyCascadeTree E ms.length) => if ℓ.1.2 < (ω ℓ.1.1).1 then ENNReal.ofReal (((ℓ.1.1:ℝ)+((ω ℓ.1.1).2 ℓ.1.2).1)^(-1/m))* familyPathWeight ms ((ω ℓ.1.1).2 ℓ.1.2).2.2 ℓ.2 else 0) have hi := (ih ℓ.2).comp (by fun_prop : Measurable (fun ω : PointCloud (E × FamilyCascadeTree E ms.length) => ((ω ℓ.1.1).2 ℓ.1.2).2.2)) have hc : MeasurableSet {ω : PointCloud (E × FamilyCascadeTree E ms.length) | ℓ.1.2 < (ω ℓ.1.1).1} := measurableSet_lt measurable_const (by fun_prop) have hw : Measurable (fun ω : PointCloud (E × FamilyCascadeTree E ms.length) => ENNReal.ofReal (((ℓ.1.1:ℝ)+((ω ℓ.1.1).2 ℓ.1.2).1)^(-1/m))) := by fun_prop exact Measurable.ite hc (hw.mul hi) measurable_const lemma measurable_familyPathMark {E : Type} [MeasurableSpace E] [Add E] [MeasurableAdd₂ E] (k : ℕ) (ℓ : CascadePath k) : Measurable (fun z : E × FamilyCascadeTree E k => familyPathMark k z.1 z.2 ℓ) := by induction k with | zero => exact measurable_fst | succ k ih => exact (ih ℓ.2).comp (show Measurable (fun z : E × PointCloud (E × FamilyCascadeTree E k) => (z.1+((z.2 ℓ.1.1).2 ℓ.1.2).2.1,((z.2 ℓ.1.1).2 ℓ.1.2).2.2)) from by fun_prop) end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators namespace MicroscopicJamming variable {E : Type} [MeasurableSpace E] [AddMonoid E] [MeasurableAdd₂ E] def normalizedFamilyPathWeight (ms : List ℝ) (ω : FamilyCascadeTree E ms.length) (ℓ : CascadePath ms.length) : ℝ := (familyPathWeight ms ω ℓ/familyUnmarkedTotal ms ω).toReal lemma measurable_normalizedFamilyPathWeight (ms : List ℝ) (ℓ : CascadePath ms.length) : Measurable (fun ω : FamilyCascadeTree E ms.length => normalizedFamilyPathWeight ms ω ℓ) := ((measurable_familyPathWeight ms ℓ).div (measurable_familyUnmarkedTotal ms)).ennreal_toReal omit [MeasurableAdd₂ E] in lemma normalized_familyPath_series [MeasurableAdd₂ E] (ms : List ℝ) (f : E → ℝ≥0∞) (x : E) (ω : FamilyCascadeTree E ms.length) (hu : 0 < familyUnmarkedTotal ms ω) (hf : familyPositiveTotal ms f x ω ≠ ∞) : Summable (fun ℓ => normalizedFamilyPathWeight ms ω ℓ*(f (familyPathMark ms.length x ω ℓ)).toReal) ∧ (∑' ℓ, normalizedFamilyPathWeight ms ω ℓ*(f (familyPathMark ms.length x ω ℓ)).toReal) = (familyPositiveTotal ms f x ω/familyUnmarkedTotal ms ω).toReal := by let a (ℓ : CascadePath ms.length) : ℝ≥0∞ := familyPathWeight ms ω ℓ/familyUnmarkedTotal ms ω*f (familyPathMark ms.length x ω ℓ) have he : (∑' ℓ, a ℓ) = familyPositiveTotal ms f x ω/familyUnmarkedTotal ms ω := by simp only [a, div_eq_mul_inv] simp_rw [mul_right_comm (familyPathWeight ms ω _) _ (f _)] rw [ENNReal.tsum_mul_right, tsum_familyPathWeight_terminal] have ha : (∑' ℓ, a ℓ) ≠ ∞ := by rw [he]; exact ENNReal.div_ne_top hf hu.ne' have hai : ∀ ℓ, a ℓ ≠ ∞ := fun ℓ => ne_top_of_le_ne_top ha (ENNReal.le_tsum ℓ) have hreal : (fun ℓ => (a ℓ).toReal) = (fun ℓ => normalizedFamilyPathWeight ms ω ℓ*(f (familyPathMark ms.length x ω ℓ)).toReal) := by funext ℓ simp only [a, normalizedFamilyPathWeight, ENNReal.toReal_mul] refine ⟨hreal ▸ ENNReal.summable_toReal ha, ?_⟩ rw [← hreal, ← ENNReal.tsum_toReal_eq hai, he] lemma normalized_familyPath_weights (ms : List ℝ) (ω : FamilyCascadeTree E ms.length) (hu : 0 < familyUnmarkedTotal ms ω ∧ familyUnmarkedTotal ms ω < ∞) : Summable (normalizedFamilyPathWeight ms ω) ∧ (∑' ℓ, normalizedFamilyPathWeight ms ω ℓ) = 1 := by have hf : familyPositiveTotal ms (fun _ : E => 1) 0 ω ≠ ∞ := by simpa only [familyPositiveTotal_const, one_mul] using hu.2.ne have H := normalized_familyPath_series ms (fun _ : E => 1) 0 ω hu.1 hf simpa only [ENNReal.toReal_one, mul_one, familyPositiveTotal_const, one_mul, ENNReal.div_self hu.1.ne' hu.2.ne] using H end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators namespace MicroscopicJamming lemma forgetFamilyMarks_zip {E : Type} (k : ℕ) (ω : CascadeTree k) (y : CascadeMarkTree E k) : forgetFamilyMarks k (zipCascade k (ω,y)) = ω := by induction k with | zero => cases ω; rfl | succ k ih => funext n apply Prod.ext · rfl · funext i apply Prod.ext · rfl · exact ih _ _ def normalizedCascadePathWeight (ms : List ℝ) (ω : CascadeTree ms.length) (ℓ : CascadePath ms.length) : ℝ := (cascadePathWeight ms ω ℓ/cascadeTotal ms ω).toReal lemma normalizedFamilyPathWeight_zip {E : Type} [MeasurableSpace E] [AddCommMonoid E] [MeasurableAdd₂ E] (ms : List ℝ) (ω : CascadeTree ms.length) (y : CascadeMarkTree E ms.length) (ℓ : CascadePath ms.length) : normalizedFamilyPathWeight ms (zipCascade ms.length (ω,y)) ℓ = normalizedCascadePathWeight ms ω ℓ := by rw [normalizedFamilyPathWeight, familyPathWeight_zip, familyUnmarkedTotal, forgetFamilyMarks_zip] rfl def rootMarkCoordinates {E : Type} (k : ℕ) (p : E × CascadeMarkTree E k) : Option (CascadeMarkIndex k) → E := fun i => i.elim p.1 (cascadeMarkCoordinates k p.2) lemma measurable_rootMarkCoordinates {E : Type} [MeasurableSpace E] (k : ℕ) : Measurable (rootMarkCoordinates (E := E) k) := by apply Measurable.of_eval intro i cases i with | none => exact measurable_fst | some i => exact (measurable_pi_apply i).comp ((measurable_cascadeMarkCoordinates k).comp measurable_snd) lemma rootMarkCoordinates_law {E : Type} [MeasurableSpace E] (k : ℕ) (μ : Measure E) [IsProbabilityMeasure μ] (ν : ℕ → Measure E) [∀ j, IsProbabilityMeasure (ν j)] : (μ.prod (cascadeMarkLaw k ν)).map (rootMarkCoordinates k) = Measure.infinitePi (fun i : Option (CascadeMarkIndex k) => i.elim μ (fun j => ν (cascadeMarkDepth k j))) := by rw [show rootMarkCoordinates (E := E) k = (fun z i => i.elim z.1 z.2) ∘ Prod.map id (cascadeMarkCoordinates k) from rfl, ← Measure.map_map (by apply Measurable.of_eval intro i cases i <;> simp only [Option.elim_none, Option.elim_some] <;> fun_prop) (measurable_id.prodMap (measurable_cascadeMarkCoordinates k)), ← Measure.map_prod_map _ _ measurable_id (measurable_cascadeMarkCoordinates k), Measure.map_id, cascadeMarkCoordinates_law, infinitePi_option] def rootPathField {E : Type} [AddCommMonoid E] (k : ℕ) (g : Option (CascadeMarkIndex k) → E) (ℓ : CascadePath k) : E := g none+∑ j : Fin k, g (some (cascadePathIndex k ℓ j)) lemma rootPathField_eq {E : Type} [AddCommMonoid E] (k : ℕ) (x : E) (ω : CascadeTree k) (y : CascadeMarkTree E k) (ℓ : CascadePath k) : familyPathMark k x (zipCascade k (ω,y)) ℓ = rootPathField k (rootMarkCoordinates k (x,y)) ℓ := by rw [familyPathMark_zip] rfl def zipRootCascade {E : Type} (k : ℕ) (p : CascadeTree k × (E × CascadeMarkTree E k)) : E × FamilyCascadeTree E k := (p.2.1, zipCascade k (p.1,p.2.2)) lemma measurable_zipRootCascade {E : Type} [MeasurableSpace E] (k : ℕ) : Measurable (zipRootCascade (E := E) k) := (measurable_fst.comp measurable_snd).prodMk ((measurable_zipCascade k).comp (measurable_fst.prodMk (measurable_snd.comp measurable_snd))) lemma zipRootCascade_law {E : Type} [MeasurableSpace E] (ms : List ℝ) (μ : Measure E) [IsProbabilityMeasure μ] (ν : ℕ → Measure E) [∀ j, IsProbabilityMeasure (ν j)] : ((cascadeLaw ms).prod (μ.prod (cascadeMarkLaw ms.length ν))).map (zipRootCascade ms.length) = μ.prod (familyCascadeLaw ms.length ν) := by rw [show zipRootCascade (E := E) ms.length = (Prod.map id (zipCascade ms.length)) ∘ (fun z => (z.2.1,(z.1,z.2.2))) from rfl, ← Measure.map_map (measurable_id.prodMap (measurable_zipCascade ms.length)) (by fun_prop), prod_rotate_map, ← Measure.map_prod_map _ _ measurable_id (measurable_zipCascade ms.length), Measure.map_id, cascade_independent_marks] lemma integral_cascade_coordinates {E : Type} [MeasurableSpace E] [AddCommMonoid E] [MeasurableAdd₂ E] (ms : List ℝ) (μ : Measure E) [IsProbabilityMeasure μ] (ν : ℕ → Measure E) [∀ j, IsProbabilityMeasure (ν j)] {f : E × FamilyCascadeTree E ms.length → ℝ} (hf : Measurable f) {g : CascadeTree ms.length × (Option (CascadeMarkIndex ms.length) → E) → ℝ} (hg : Measurable g) (he : ∀ ω x y, f (x,zipCascade ms.length (ω,y)) = g (ω,rootMarkCoordinates ms.length (x,y))) : (∫ z, f z ∂μ.prod (familyCascadeLaw ms.length ν)) = ∫ z, g z ∂(cascadeLaw ms).prod (Measure.infinitePi (fun i : Option (CascadeMarkIndex ms.length) => i.elim μ (fun j => ν (cascadeMarkDepth ms.length j)))) := by rw [← zipRootCascade_law ms μ ν, integral_map (measurable_zipRootCascade ms.length).aemeasurable hf.aestronglyMeasurable] have hmap := rootMarkCoordinates_law ms.length μ ν rw [← hmap, ← (Measure.map_id (μ := cascadeLaw ms)), Measure.map_prod_map _ _ measurable_id (measurable_rootMarkCoordinates ms.length), integral_map (measurable_id.prodMap (measurable_rootMarkCoordinates ms.length)).aemeasurable hg.aestronglyMeasurable] rw [Measure.map_id] apply integral_congr_ae exact Eventually.of_forall fun z => he z.1 z.2.1 z.2.2 end MicroscopicJamming open MeasureTheory Filter Set open scoped ENNReal NNReal BigOperators open Classical namespace MicroscopicJamming lemma enn_pair_sum_mul {I : Type*} (a : I → ℝ≥0∞) : (∑' i, a i)*(∑' i, a i) = ∑' p : I × I, a p.1*a p.2 := by rw [ENNReal.tsum_prod'] simp_rw [ENNReal.tsum_mul_left] rw [ENNReal.tsum_mul_right] lemma enn_pair_same_block {I L : Type*} (a : I → L → ℝ≥0∞) (R : L → L → Prop) : (∑' p : (I × L) × (I × L), if p.1.1=p.2.1 ∧ R p.1.2 p.2.2 then a p.1.1 p.1.2*a p.2.1 p.2.2 else 0) = ∑' i, ∑' p : L × L, if R p.1 p.2 then a i p.1*a i p.2 else 0 := by rw [ENNReal.tsum_prod'] simp_rw [ENNReal.tsum_prod'] apply tsum_congr intro i rw [ENNReal.tsum_comm] have H (j : I) : (∑' l, ∑' r, if i=j ∧ R l r then a i l*a j r else 0) = if i=j then ∑' l, ∑' r, if R l r then a i l*a j r else 0 else 0 := by by_cases h : i=j <;> simp [h] simp_rw [H] simpa only [eq_comm] using (tsum_ite_eq i (fun j => ∑' l, ∑' r, if R l r then a i l*a j r else 0)) lemma enn_pair_scale {L : Type*} (a : L → ℝ≥0∞) (c : ℝ≥0∞) (R : L → L → Prop) : (∑' p : L × L, if R p.1 p.2 then (c*a p.1)*(c*a p.2) else 0) = c^2*(∑' p : L × L, if R p.1 p.2 then a p.1*a p.2 else 0) := by rw [← ENNReal.tsum_mul_left] apply tsum_congr intro p split_ifs · ring · simp only [mul_zero] end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal BigOperators open Classical namespace MicroscopicJamming def pathAgree : (k : ℕ) → ℕ → CascadePath k → CascadePath k → Prop | 0, _, _, _ => True | _+1, 0, _, _ => True | k+1, j+1, a, b => a.1=b.1 ∧ pathAgree k j a.2 b.2 def familyLeafMass {E : Type} [Add E] (ms : List ℝ) (u : E → ℝ) (x : E) (ω : FamilyCascadeTree E ms.length) (ℓ : CascadePath ms.length) : ℝ≥0∞ := familyPathWeight ms ω ℓ*ENNReal.ofReal (Real.exp (u (familyPathMark ms.length x ω ℓ))) def familyPairSum {E : Type} [Add E] (ms : List ℝ) (j : ℕ) (u : E → ℝ) (x : E) (ω : FamilyCascadeTree E ms.length) : ℝ≥0∞ := ∑' p : CascadePath ms.length × CascadePath ms.length, if pathAgree ms.length j p.1 p.2 then familyLeafMass ms u x ω p.1*familyLeafMass ms u x ω p.2 else 0 lemma tsum_familyLeafMass {E : Type} [MeasurableSpace E] [Add E] [MeasurableAdd₂ E] (ms : List ℝ) (u : E → ℝ) (x : E) (ω : FamilyCascadeTree E ms.length) : (∑' ℓ, familyLeafMass ms u x ω ℓ) = familyLeafTotal ms u x ω := by exact (tsum_familyPathWeight_terminal ms (fun y => ENNReal.ofReal (Real.exp (u y))) x ω).trans (familyPositiveTotal_exp ms u x ω) lemma pathAgree_zero (k : ℕ) (a b : CascadePath k) : pathAgree k 0 a b := by cases k <;> trivial lemma familyPairSum_zero {E : Type} [MeasurableSpace E] [Add E] [MeasurableAdd₂ E] (ms : List ℝ) (u : E → ℝ) (x : E) (ω : FamilyCascadeTree E ms.length) : familyPairSum ms 0 u x ω = (familyLeafTotal ms u x ω)^2 := by simp only [familyPairSum, pathAgree_zero, ite_true] rw [← enn_pair_sum_mul, tsum_familyLeafMass, pow_two] lemma familyLeafMass_cons {E : Type} [Add E] (m : ℝ) (ms : List ℝ) (u : E → ℝ) (x : E) (ω : FamilyCascadeTree E (m::ms).length) (i : ℕ × ℕ) (ℓ : CascadePath ms.length) : familyLeafMass (m::ms) u x ω (i,ℓ) = (if i.2 < (ω i.1).1 then ENNReal.ofReal (((i.1:ℝ)+((ω i.1).2 i.2).1)^(-1/m)) else 0)* familyLeafMass ms u (x+((ω i.1).2 i.2).2.1) ((ω i.1).2 i.2).2.2 ℓ := by by_cases hi : i.2 < (ω i.1).1 · simp only [familyLeafMass, List.length_cons, familyPathWeight, familyPathMark, hi, ite_true, mul_assoc] · simp only [familyLeafMass, familyPathWeight, hi, ite_false, zero_mul] lemma familyPairSum_cons {E : Type} [MeasurableSpace E] [Add E] [MeasurableAdd₂ E] (m : ℝ) (ms : List ℝ) (j : ℕ) (u : E → ℝ) (x : E) (ω : FamilyCascadeTree E (m::ms).length) : familyPairSum (m::ms) (j+1) u x ω = pointCloudFunctional (fun z : ℝ × (E × FamilyCascadeTree E ms.length) => (ENNReal.ofReal (z.1^(-1/m)))^2*familyPairSum ms j u (x+z.2.1) z.2.2) ω := by simp only [familyPairSum, List.length_cons, pathAgree] change (∑' p : ((ℕ × ℕ) × CascadePath ms.length) × ((ℕ × ℕ) × CascadePath ms.length), if p.1.1=p.2.1 ∧ pathAgree ms.length j p.1.2 p.2.2 then familyLeafMass (m::ms) u x ω p.1*familyLeafMass (m::ms) u x ω p.2 else 0) = _ refine Eq.trans ?_ ((enn_pair_same_block (fun i ℓ => familyLeafMass (m::ms) u x ω (i,ℓ)) (pathAgree ms.length j)).trans ?_) · apply tsum_congr rintro ⟨⟨i,ℓ⟩,⟨j,r⟩⟩ split_ifs <;> rfl · simp_rw [familyLeafMass_cons, enn_pair_scale] rw [ENNReal.tsum_prod'] simp only [pointCloudFunctional, poissonBinSum] apply tsum_congr intro n rw [tsum_eq_sum (s := Finset.range (ω n).1) (fun i hi => by simp only [Finset.mem_range, not_lt] at hi simp [not_lt.mpr hi])] apply Finset.sum_congr rfl intro i hi simp only [Finset.mem_range.mp hi, ite_true] end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal BigOperators open Classical namespace MicroscopicJamming lemma cascadePathIndex_eq_iff (k : ℕ) (a b : CascadePath k) (j : Fin k) : cascadePathIndex k a j = cascadePathIndex k b j ↔ pathAgree k (j.val+1) a b := by induction k with | zero => exact Fin.elim0 j | succ k ih => refine Fin.cases ?_ (fun i => ?_) j · change (a.1.1,a.1.2,none) = (b.1.1,b.1.2,(none : Option (CascadeMarkIndex k))) ↔ a.1=b.1 ∧ pathAgree k 0 a.2 b.2 simp [Prod.ext_iff, pathAgree_zero] · change (a.1.1,a.1.2,some (cascadePathIndex k a.2 i)) = (b.1.1,b.1.2,some (cascadePathIndex k b.2 i)) ↔ a.1=b.1 ∧ pathAgree k (i.val+1) a.2 b.2 simp only [Option.some.injEq, ih, Prod.ext_iff] tauto lemma cascadePathIndex_depth_eq {k : ℕ} {a b : CascadePath k} {i j : Fin k} (h : cascadePathIndex k a i = cascadePathIndex k b j) : i = j := by apply Fin.ext simpa only [cascadePathIndex_depth] using congrArg (cascadeMarkDepth k) h def rootPathIndex (k : ℕ) (ℓ : CascadePath k) : Fin (k+1) → Option (CascadeMarkIndex k) := Fin.cases none (fun j => some (cascadePathIndex k ℓ j)) lemma rootPathIndex_injective (k : ℕ) (ℓ : CascadePath k) : Function.Injective (rootPathIndex k ℓ) := by intro i j h cases i using Fin.cases with | zero => cases j using Fin.cases with | zero => rfl | succ j => simp [rootPathIndex] at h | succ i => cases j using Fin.cases with | zero => simp [rootPathIndex] at h | succ j => apply congrArg Fin.succ exact cascadePathIndex_injective k ℓ (Option.some.inj h) lemma rootPathIndex_depth_eq {k : ℕ} {a b : CascadePath k} {i j : Fin (k+1)} (h : rootPathIndex k a i = rootPathIndex k b j) : i = j := by cases i using Fin.cases with | zero => cases j using Fin.cases with | zero => rfl | succ j => simp [rootPathIndex] at h | succ i => cases j using Fin.cases with | zero => simp [rootPathIndex] at h | succ j => exact congrArg Fin.succ (cascadePathIndex_depth_eq (Option.some.inj h)) lemma rootPathIndex_eq_iff (k : ℕ) (a b : CascadePath k) (j : Fin (k+1)) : rootPathIndex k a j = rootPathIndex k b j ↔ pathAgree k j.val a b := by cases j using Fin.cases with | zero => simp [rootPathIndex, pathAgree_zero] | succ j => simpa only [rootPathIndex, Fin.cases_succ, Option.some.injEq, Fin.val_succ] using cascadePathIndex_eq_iff k a b j lemma finite_incidence_covariance {A J : Type*} [Fintype A] [Fintype J] (e f : J → A) (_hf : Function.Injective f) (v : J → ℝ) (hdepth : ∀ i j, e i = f j → i = j) : (∑ a : A, (∑ i : J, if e i=a then v i else 0)*(∑ j : J, if f j=a then v j else 0)) = ∑ i : J, if e i=f i then (v i)^2 else 0 := by simp_rw [Finset.sum_mul, Finset.mul_sum] rw [Finset.sum_comm] apply Finset.sum_congr rfl intro i _ rw [Finset.sum_comm] have he (j : J) : (∑ a : A, (if e i=a then v i else 0)*(if f j=a then v j else 0)) = if e i=f j then v i*v j else 0 := by rw [Finset.sum_eq_single (e i)] · simp only [ite_true] by_cases hh : e i=f j · simp [hh] · simp [hh, Ne.symm hh] · intro a _ ha simp [Ne.symm ha] · simp simp_rw [he] rw [Finset.sum_eq_single i] · simp [pow_two] · intro j _ hj simp only [ite_eq_right (fun hh => hj (hdepth i j hh).symm)] · simp end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators open Classical namespace MicroscopicJamming def cascadeCoordinateSet (k : ℕ) (S : Finset (CascadePath k)) : Finset (Option (CascadeMarkIndex k)) := S.biUnion (fun ℓ => Finset.univ.image (rootPathIndex k ℓ)) lemma rootPathIndex_mem (k : ℕ) (S : Finset (CascadePath k)) (ℓ : S) (j : Fin (k+1)) : rootPathIndex k ℓ.val j ∈ cascadeCoordinateSet k S := by apply Finset.mem_biUnion.mpr exact ⟨ℓ.val,ℓ.property,Finset.mem_image.mpr ⟨j,Finset.mem_univ j,rfl⟩⟩ def finiteRootPathIndex (k : ℕ) (S : Finset (CascadePath k)) (ℓ : S) (j : Fin (k+1)) : cascadeCoordinateSet k S := ⟨rootPathIndex k ℓ.val j,rootPathIndex_mem k S ℓ j⟩ def finiteRootPathField {E : Type} [AddCommMonoid E] (k : ℕ) (S : Finset (CascadePath k)) (z : cascadeCoordinateSet k S → E) (ℓ : S) : E := ∑ j, z (finiteRootPathIndex k S ℓ j) lemma rootPathField_finite {E : Type} [AddCommMonoid E] (k : ℕ) (S : Finset (CascadePath k)) (z : Option (CascadeMarkIndex k) → E) (ℓ : S) : rootPathField k z ℓ.val = finiteRootPathField k S ((cascadeCoordinateSet k S).restrict z) ℓ := by rw [finiteRootPathField, Fin.sum_univ_succ] rfl lemma measurable_finiteRootPathField {E : Type} [MeasurableSpace E] [AddCommMonoid E] [MeasurableAdd₂ E] (k : ℕ) (S : Finset (CascadePath k)) : Measurable (fun z ℓ => finiteRootPathField (E := E) k S z ℓ) := by unfold finiteRootPathField fun_prop lemma integral_cascade_finite_coordinates {E : Type} [MeasurableSpace E] [AddCommMonoid E] [MeasurableAdd₂ E] (ms : List ℝ) (S : Finset (CascadePath ms.length)) (μ : Measure E) [IsProbabilityMeasure μ] (ν : ℕ → Measure E) [∀ j, IsProbabilityMeasure (ν j)] {f : E × FamilyCascadeTree E ms.length → ℝ} (hf : Measurable f) {g : CascadeTree ms.length × (cascadeCoordinateSet ms.length S → E) → ℝ} (hg : Measurable g) (he : ∀ ω x y, f (x,zipCascade ms.length (ω,y)) = g (ω,(cascadeCoordinateSet ms.length S).restrict (rootMarkCoordinates ms.length (x,y)))) : (∫ z, f z ∂μ.prod (familyCascadeLaw ms.length ν)) = ∫ z, g z ∂(cascadeLaw ms).prod (Measure.pi (fun i : cascadeCoordinateSet ms.length S => i.val.elim μ (fun j => ν (cascadeMarkDepth ms.length j)))) := by let C := cascadeCoordinateSet ms.length S let η : Option (CascadeMarkIndex ms.length) → Measure E := fun i => i.elim μ (fun j => ν (cascadeMarkDepth ms.length j)) have hη (i) : IsProbabilityMeasure (η i) := by cases i <;> dsimp [η] <;> infer_instance let := hη have hm : Measurable (Prod.map (id : CascadeTree ms.length → CascadeTree ms.length) (C.restrict : (Option (CascadeMarkIndex ms.length) → E) → (C → E))) := by exact measurable_id.prodMap (Measurable.of_eval fun i => measurable_pi_apply i.val) rw [integral_cascade_coordinates ms μ ν hf (hg.comp hm) he] have hr : Measurable (C.restrict : (Option (CascadeMarkIndex ms.length) → E) → (C → E)) := Measurable.of_eval fun i => measurable_pi_apply i.val change (∫ z, g (Prod.map id C.restrict z) ∂(cascadeLaw ms).prod (Measure.infinitePi η)) = _ rw [← integral_map hm.aemeasurable hg.aestronglyMeasurable, ← Measure.map_prod_map _ _ measurable_id hr, Measure.map_id, Measure.infinitePi_map_restrict] end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators open Classical namespace MicroscopicJamming lemma weighted_incidence_covariance {A J : Type*} [Fintype A] [Fintype J] (e f : J → A) (q : A → ℝ) (hdepth : ∀ i j, e i=f j → i=j) : (∑ a : A, q a*(∑ i : J, if e i=a then (1:ℝ) else 0)*(∑ j : J, if f j=a then (1:ℝ) else 0)) = ∑ i : J, if e i=f i then q (e i) else 0 := by calc _ = ∑ i : J, ∑ a : A, (q a*(if e i=a then (1:ℝ) else 0))* (∑ j : J, if f j=a then (1:ℝ) else 0) := by rw [Finset.sum_comm] apply Finset.sum_congr rfl intro a _ rw [← Finset.sum_mul, ← Finset.mul_sum] _ = ∑ i : J, q (e i)*(∑ j : J, if f j=e i then (1:ℝ) else 0) := by apply Finset.sum_congr rfl intro i _ rw [Finset.sum_eq_single (e i)] · simp · intro a _ ha simp [Ne.symm ha] · simp _ = _ := by apply Finset.sum_congr rfl intro i _ rw [Finset.sum_eq_single i] · by_cases hh : e i=f i <;> simp [hh, Ne.symm] · intro j _ hj exact ite_eq_right (fun hh => hj (hdepth i j hh.symm).symm) · simp def rootCoordinateVariance (k : ℕ) (d : ℕ → ℝ≥0) (p₀ : ℝ≥0) (a : Option (CascadeMarkIndex k)) : ℝ≥0 := a.elim p₀ (fun j => d (cascadeMarkDepth k j)) def pathCovarianceDifference (k : ℕ) (d d' : ℕ → ℝ≥0) (p₀ p₀' : ℝ≥0) (a b : CascadePath k) : ℝ := (p₀:ℝ)-(p₀':ℝ)+∑ j : Fin k, if pathAgree k (j.val+1) a b then (d j:ℝ)-(d' j:ℝ) else 0 lemma rootVariance_path (k : ℕ) (d : ℕ → ℝ≥0) (p₀ : ℝ≥0) (ℓ : CascadePath k) (j : Fin (k+1)) : rootCoordinateVariance k d p₀ (rootPathIndex k ℓ j) = Fin.cases p₀ (fun i => d i) j := by cases j using Fin.cases with | zero => rfl | succ j => change d (cascadeMarkDepth k (cascadePathIndex k ℓ j)) = d j rw [cascadePathIndex_depth] lemma finiteRoot_incidence_covariance (k : ℕ) (S : Finset (CascadePath k)) (d d' : ℕ → ℝ≥0) (p₀ p₀' : ℝ≥0) (ℓ r : S) : (∑ a : cascadeCoordinateSet k S, ((rootCoordinateVariance k d p₀ a:ℝ)-(rootCoordinateVariance k d' p₀' a:ℝ))* (∑ j : Fin (k+1), if finiteRootPathIndex k S ℓ j=a then (1:ℝ) else 0)* (∑ j : Fin (k+1), if finiteRootPathIndex k S r j=a then (1:ℝ) else 0)) = pathCovarianceDifference k d d' p₀ p₀' ℓ.val r.val := by have H := weighted_incidence_covariance (finiteRootPathIndex k S ℓ) (finiteRootPathIndex k S r) (fun a => (rootCoordinateVariance k d p₀ a:ℝ)-(rootCoordinateVariance k d' p₀' a:ℝ)) (fun i j hij => rootPathIndex_depth_eq (congrArg Subtype.val hij)) calc _ = ∑ i : Fin (k+1), if finiteRootPathIndex k S ℓ i=finiteRootPathIndex k S r i then (rootCoordinateVariance k d p₀ (finiteRootPathIndex k S ℓ i):ℝ)- (rootCoordinateVariance k d' p₀' (finiteRootPathIndex k S ℓ i):ℝ) else 0 := by convert H using 1 <;> congr 4 <;> funext a <;> congr 3 <;> funext j <;> split_ifs <;> rfl _ = _ := by rw [Fin.sum_univ_succ] simp only [finiteRootPathIndex, Subtype.mk.injEq, rootPathIndex_eq_iff, rootVariance_path, Fin.cases_zero, Fin.cases_succ, Fin.val_zero, Fin.val_succ, pathAgree_zero, ite_true, pathCovarianceDifference] end MicroscopicJamming open MeasureTheory ProbabilityTheory Set open scoped ENNReal NNReal BigOperators open Classical namespace MicroscopicJamming def rowReplicaCovariance (k r : ℕ) (d : ℕ → ℝ≥0) (p₀ : ℝ≥0) (xs : Fin r → CascadePath k) : Matrix (Fin r) (Fin r) ℝ := fun i j => (p₀:ℝ) + ∑ a : Fin k, if pathAgree k (a.val+1) (xs i) (xs j) then (d a:ℝ) else 0 def rowReplicaGaussianField (k r : ℕ) (xs : Fin r → CascadePath k) (z : Option (CascadeMarkIndex k) → ℝ) : EuclideanSpace ℝ (Fin r) := WithLp.toLp 2 (fun i => rootPathField k z (xs i)) def RowReplicaGaussianStatement : Prop := ∀ (k r : ℕ) (d : ℕ → ℝ≥0) (p₀ : ℝ≥0) (xs : Fin r → CascadePath k), (rowReplicaCovariance k r d p₀ xs).PosSemidef ∧ (Measure.infinitePi (fun a => gaussianReal 0 (rootCoordinateVariance k d p₀ a))).map (rowReplicaGaussianField k r xs) = multivariateGaussian 0 (rowReplicaCovariance k r d p₀ xs) end MicroscopicJamming open MeasureTheory ProbabilityTheory Set open scoped ENNReal NNReal BigOperators open Classical namespace MicroscopicJamming def rowReplicaResidualCovariance (k r : ℕ) (d : ℕ → ℝ≥0) (p₀ Δ : ℝ≥0) (xs : Fin r → CascadePath k) : Matrix (Fin r) (Fin r) ℝ := rowReplicaCovariance k r d p₀ xs + Matrix.diagonal (fun _ => (Δ:ℝ)) def rowReplicaResidualField (k r : ℕ) (xs : Fin r → CascadePath k) (w : (Option (CascadeMarkIndex k) → ℝ) × (Fin r → ℝ)) : EuclideanSpace ℝ (Fin r) := rowReplicaGaussianField k r xs w.1 + WithLp.toLp 2 w.2 def RowReplicaResidualStatement : Prop := ∀ (k r : ℕ) (d : ℕ → ℝ≥0) (p₀ Δ : ℝ≥0) (xs : Fin r → CascadePath k), (rowReplicaResidualCovariance k r d p₀ Δ xs).PosSemidef ∧ ((Measure.infinitePi (fun a => gaussianReal 0 (rootCoordinateVariance k d p₀ a))).prod (Measure.pi (fun _ : Fin r => gaussianReal 0 Δ))).map (rowReplicaResidualField k r xs) = multivariateGaussian 0 (rowReplicaResidualCovariance k r d p₀ Δ xs) end MicroscopicJamming open MeasureTheory ProbabilityTheory Filter Set open scoped ENNReal NNReal Topology BigOperators MatrixOrder namespace MicroscopicJamming def gaussianAdjunctionMap {A : Type*} (m : ℕ) (C : A → Matrix (Fin m) (Fin m) ℝ) (w : A × EuclideanSpace ℝ (Fin m)) : A × EuclideanSpace ℝ (Fin m) := (w.1, Matrix.toEuclideanCLM (𝕜 := ℝ) (CFC.sqrt (C w.1)) w.2) def gaussianAdjunctionMeasure {A : Type*} [MeasurableSpace A] (m : ℕ) (C : A → Matrix (Fin m) (Fin m) ℝ) (μ : Measure A) : Measure (A × EuclideanSpace ℝ (Fin m)) := (μ.prod (stdGaussian (EuclideanSpace ℝ (Fin m)))).map (gaussianAdjunctionMap m C) def GaussianAdjunctionStatement : Prop := ∀ (A : Type) (tA : TopologicalSpace A) (mA : MeasurableSpace A), ∀ (_hB : @BorelSpace A tA mA) (_hSC : SecondCountableTopology A) (_hPM : TopologicalSpace.PseudoMetrizableSpace A), ∀ (m : ℕ) (C : A → Matrix (Fin m) (Fin m) ℝ), Continuous C → (∀ x, (C x).PosSemidef) → (∃ K : ℝ, ∀ x i j, |C x i j| ≤ K) → ∀ (μ : ℕ → ProbabilityMeasure A) (μ₀ : ProbabilityMeasure A), Tendsto μ atTop (𝓝 μ₀) → ∃ (ρ : ℕ → ProbabilityMeasure (A × EuclideanSpace ℝ (Fin m))) (ρ₀ : ProbabilityMeasure (A × EuclideanSpace ℝ (Fin m))), (∀ n, (ρ n : Measure _) = gaussianAdjunctionMeasure m C (μ n)) ∧ (ρ₀ : Measure _) = gaussianAdjunctionMeasure m C μ₀ ∧ Tendsto ρ atTop (𝓝 ρ₀) end MicroscopicJamming end end OAI