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Add lean source and binary files (part 120)
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import Mathlib
import OAI.Probability.CriticalPercolation.Modular.ClusterDiscrepancy
import OAI.Probability.CriticalPercolation.Modular.ModularClusterMass
import OAI.Probability.CriticalPercolation.Modular.PeakRatioTransport
namespace OAI
section
noncomputable section
open Set MeasureTheory
open scoped Classical ENNReal BigOperators
namespace CriticalPercolation.BondGraph
variable {V E : Type*} (G : BondGraph V E)
def reciprocalClusterMass (ω : Set E) (x : V) : ℝ≥0∞ :=
(G.modularMass x (G.cluster ω x))⁻¹
def finiteMassIndicator (ω : Set E) (x : V) : ℝ≥0∞ :=
if G.modularMass x (G.cluster ω x)=∞ then 0 else 1
lemma reciprocalClusterMass_le_one (ω : Set E) (x : V) : G.reciprocalClusterMass ω x≤1 :=
ENNReal.inv_le_one.mpr (G.one_le_modularClusterMass ω x)
lemma measurable_reciprocalClusterMass [Countable V] [Countable E] (x : V) :
Measurable (fun ω : Set E => G.reciprocalClusterMass ω x) :=
(G.measurable_modularClusterMass x x).inv
lemma measurable_finiteMassIndicator [Countable V] [Countable E] (x : V) :
Measurable (fun ω : Set E => G.finiteMassIndicator ω x) :=
measurable_const.ite (measurableSet_eq_fun (G.measurable_modularClusterMass x x) measurable_const) measurable_const
lemma Aut.reciprocalClusterMass (φ : G.Aut) (ω : Set E) (x : V) :
G.reciprocalClusterMass (φ.edge '' ω) (φ.vertex x)=G.reciprocalClusterMass ω x := by
unfold CriticalPercolation.BondGraph.reciprocalClusterMass
rw [←φ.cluster_image,φ.modularMass_image]
lemma finiteMassIndicator_eq_of_reachable (hc : G.fullGraph.Connected) (hl : G.LocallyFinite)
(ω : Set E) {x y : V} (h : (G.openGraph ω).Reachable x y) :
G.finiteMassIndicator ω x=G.finiteMassIndicator ω y := by
unfold finiteMassIndicator
simp only [G.cluster_eq_of_reachable h,G.modularMass_eq_top_change_base hc hl x y]
lemma stabilizerWeight_mul_reverse (hc : G.fullGraph.Connected) (hl : G.LocallyFinite) (x y : V) :
G.stabilizerWeight x y*G.stabilizerWeight y x=1 := by
rw [←G.stabilizerWeight_change_base hc hl x y x,G.stabilizerWeight_self]
lemma stabilizerWeight_inv (hc : G.fullGraph.Connected) (hl : G.LocallyFinite) (x y : V) :
(G.stabilizerWeight x y)⁻¹=G.stabilizerWeight y x := by
apply (ENNReal.mul_left_inj (G.stabilizerWeight_pos hc hl x y).ne' (G.stabilizerWeight_ne_top x y)).mp
rw [ENNReal.inv_mul_cancel (G.stabilizerWeight_pos hc hl x y).ne' (G.stabilizerWeight_ne_top x y),
G.stabilizerWeight_mul_reverse hc hl]
lemma reciprocalClusterMass_change_base (hc : G.fullGraph.Connected) (hl : G.LocallyFinite)
(ω : Set E) {x y : V} (h : (G.openGraph ω).Reachable y x) :
G.reciprocalClusterMass ω x=G.stabilizerWeight y x*G.reciprocalClusterMass ω y := by
unfold reciprocalClusterMass
rw [G.cluster_eq_of_reachable h.symm,G.modularMass_change_base hc hl x y,
ENNReal.mul_inv (Or.inl (G.stabilizerWeight_pos hc hl x y).ne') (Or.inl (G.stabilizerWeight_ne_top x y)),
G.stabilizerWeight_inv hc hl]
lemma sum_reciprocalClusterMass (hc : G.fullGraph.Connected) (hl : G.LocallyFinite)
(ω : Set E) (y : V) :
(∑' x, if x∈G.cluster ω y then G.reciprocalClusterMass ω x else 0)=G.finiteMassIndicator ω y := by
calc
_ = (G.modularMass y (G.cluster ω y))*G.reciprocalClusterMass ω y := by
unfold modularMass
rw [←ENNReal.tsum_mul_right]
apply tsum_congr
intro x
by_cases h : x∈G.cluster ω y
· simp only [ite_eq_left h,G.reciprocalClusterMass_change_base hc hl ω h]
· simp only [ite_eq_right h,zero_mul]
_ = _ := by
unfold reciprocalClusterMass finiteMassIndicator
split_ifs with hm
· simp [hm]
· exact ENNReal.mul_inv_cancel
(ne_of_gt (zero_lt_one.trans_le (G.one_le_modularClusterMass ω y))) hm
def incidentClusterCount (ω : Set E) (e : E) : ℝ≥0∞ :=
∑' x, if e∈G.incidentEdges (G.cluster ω x) then G.reciprocalClusterMass ω x else 0
lemma measurable_incidentClusterCount [Countable V] [Countable E] (e : E) :
Measurable (fun ω : Set E => G.incidentClusterCount ω e) := by
apply Measurable.tsum
intro x
exact (G.measurable_reciprocalClusterMass x).ite
(Measurable.exists (fun v => (G.measurable_reachable x v).and measurable_const)).setOf measurable_const
lemma incident_cluster_iff_ends (ω : Set E) (e : E) (a b : V) (he : G.ends e=s(a,b)) (x : V) :
e∈G.incidentEdges (G.cluster ω x) ↔ x∈G.cluster ω a ∨ x∈G.cluster ω b := by
constructor
· rintro ⟨v,hv,hve⟩
rw [he,Sym2.mem_iff] at hve
rcases hve with rfl|rfl
· exact Or.inl hv.symm
· exact Or.inr hv.symm
· rintro (ha|hb)
· exact ⟨a,ha.symm,by simp [he]⟩
· exact ⟨b,hb.symm,by simp [he]⟩
lemma incidentClusterCount_of_ends (hc : G.fullGraph.Connected) (hl : G.LocallyFinite)
(ω : Set E) (e : E) (a b : V) (he : G.ends e=s(a,b)) :
G.incidentClusterCount ω e = if (G.openGraph ω).Reachable a b then
G.finiteMassIndicator ω a else G.finiteMassIndicator ω a+G.finiteMassIndicator ω b := by
unfold incidentClusterCount
simp only [G.incident_cluster_iff_ends ω e a b he]
by_cases hr : (G.openGraph ω).Reachable a b
· rw [ite_eq_left hr]
have hC := G.cluster_eq_of_reachable hr
simp only [hC,or_self,G.sum_reciprocalClusterMass hc hl]
exact (G.finiteMassIndicator_eq_of_reachable hc hl ω hr).symm
· rw [ite_eq_right hr,←G.sum_reciprocalClusterMass hc hl ω a,←G.sum_reciprocalClusterMass hc hl ω b,
←ENNReal.tsum_add]
apply tsum_congr
intro x
have hnot : ¬(x∈G.cluster ω a ∧ x∈G.cluster ω b) := fun h => hr (h.1.trans h.2.symm)
by_cases ha : x∈G.cluster ω a <;> by_cases hb : x∈G.cluster ω b <;>
simp_all only [true_or,or_true,false_or,ite_true,ite_false,zero_add,add_zero,and_self,not_true_eq_false]
lemma incidentClusterCount_le_two (hc : G.fullGraph.Connected) (hl : G.LocallyFinite)
(ω : Set E) (e : E) : G.incidentClusterCount ω e≤2 := by
obtain ⟨⟨a,b⟩,he⟩ := Quot.exists_rep (G.ends e)
rw [G.incidentClusterCount_of_ends hc hl ω e a b he.symm]
unfold finiteMassIndicator
split_ifs <;> norm_num
end CriticalPercolation.BondGraph
end
end
end OAI