openAI-math-dataset / lean /OAI /Probability /ClassicalON /AnnulusCrossing.lean
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Add lean source and binary files (part 119)
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import OAI.Probability.ClassicalON.PoleCrossing
namespace OAI
noncomputable section
open MeasureTheory Set
open scoped BigOperators Classical
namespace ClassicalON.LatticeGraph
def innerSet (G : LatticeGraph) (k : ℕ) : Set G.vertices :=
{x | |(scaledSite k x.val).1|≤1 ∧ |(scaledSite k x.val).2|≤1}
def outerSet (G : LatticeGraph) (k : ℕ) : Set G.vertices :=
{x | 2≤|(scaledSite k x.val).1| ∨ 2≤|(scaledSite k x.val).2|}
theorem inner_outer_disjoint (G : LatticeGraph) (k : ℕ) : Disjoint (G.innerSet k) (G.outerSet k) := by
apply Set.disjoint_left.mpr
intro x hx ho
rcases ho with h | h <;> linarith [hx.1,hx.2]
def positiveLayerPins (G : LatticeGraph) (I O : Set G.vertices) : G.vertices → Option (Spin 3) :=
(poleSystem (fun e : G.edges => e.val.1) (fun e => e.val.2) (fun _ => 0) (I∪O) (fun _ => true)).pin
theorem positiveLayerPins_boundary (G : LatticeGraph) (k : ℕ) (I O : Set G.vertices)
(hI : I⊆G.innerSet k) (hO : O⊆G.outerSet k) :
G.BoundaryPins k 3 (G.positiveLayerPins I O) := by
intro x s hs
by_cases h : x∈I∪O
· rcases h with h | h
· exact Or.inl (hI h)
· exact Or.inr (hO h)
· simp only [positiveLayerPins,poleSystem,h,↓reduceDIte] at hs
cases hs
theorem rotate_positiveLayerPins_pi (G : LatticeGraph) (k : ℕ) (I O : Set G.vertices)
(hI : I⊆G.innerSet k) (hO : O⊆G.outerSet k) :
G.rotatedBoundaryPins k (G.positiveLayerPins I O) Real.pi=
(poleSystem (fun e : G.edges => e.val.1) (fun e => e.val.2) (fun _ => 0) (I∪O)
(fun v => layerSigns I v)).pin := by
funext x
by_cases hx : x∈I∪O
· have htheta : G.thetaPotential k x=if x∈I then 1 else 0 := by
by_cases h : x∈I
· simp only [h,ite_true,thetaPotential]
exact squareTheta_one _ (hI h).1 (hI h).2
· simp only [h,ite_false,thetaPotential]
exact squareTheta_zero _ (hO (hx.resolve_left h))
simp only [rotatedBoundaryPins,positiveLayerPins,poleSystem,hx,↓reduceDIte,Option.map_some]
by_cases hi : x∈I
· rw [show layerSigns I x=false by simp [layerSigns,hi]]
congr 1
exact rotate_pole _ _ (by simpa [hi] using htheta)
· rw [show layerSigns I x=true by simp [layerSigns,hi]]
congr 1
exact rotation_zero_potential _ _ _ (by simpa [hi] using htheta) _
· simp only [rotatedBoundaryPins,positiveLayerPins,poleSystem,hx,↓reduceDIte,Option.map_none]
theorem rotate_positiveLayerPins_zero (G : LatticeGraph) (k : ℕ) (I O : Set G.vertices) :
G.rotatedBoundaryPins k (G.positiveLayerPins I O) 0=G.positiveLayerPins I O := by
funext x
simp only [rotatedBoundaryPins]
cases hp : G.positiveLayerPins I O x with
| none => rfl
| some s =>
simp only [Option.map_some]
congr 1
apply Subtype.ext
change NormedSpace.exp ((0*G.thetaPotential k x) • axisC) s.val=s.val
simp [zero_smul ℝ axisC]
theorem annulus_crossing_small (β : ℝ) (hβ : 0≤β) (ε : ℝ) (hε : 0<ε) :
∃ k : ℕ,4≤k ∧ ∀ (G : LatticeGraph),G.WithinDyadicBox k →
∀ (b : G.edges → ℝ),(∀ e,0≤b e ∧ b e≤β) →
∀ (I O : Set G.vertices),I⊆G.innerSet k → O⊆G.outerSet k →
poleBondMean (fun e : G.edges => e.val.1) (fun e => e.val.2) b (I∪O) (fun _ => true)
(crossingIndicator (fun e : G.edges => e.val.1) (fun e => e.val.2) I O)≤ε := by
obtain ⟨k,hk,hr⟩ := annulus_partition_ratio β hβ ε hε
refine ⟨k,hk,?_⟩
intro G hG b hb I O hI hO
have hd : Disjoint I O := (G.inner_outer_disjoint k).mono hI hO
rw [pole_crossing_ratio _ _ _ (fun e => (hb e).1) _ _ hd]
have h := hr G hG b hb (G.positiveLayerPins I O)
(G.positiveLayerPins_boundary k I O hI hO) Real.pi 0
rw [G.rotate_positiveLayerPins_pi k I O hI hO,G.rotate_positiveLayerPins_zero k I O] at h
change 1-ε≤(poleSystem _ _ b (I∪O) (fun v => layerSigns I v)).Z (fun _ => 1)/
(poleSystem _ _ b (I∪O) (fun _ => true)).Z (fun _ => 1) at h
linarith
end ClassicalON.LatticeGraph
end
end OAI