import OAI.MathematicalPhysics.CriticalSK.Main import OAI.Probability.SKGap.Main namespace OAI noncomputable section open scoped BigOperators Topology NNReal ENNReal open MeasureTheory ProbabilityTheory Filter namespace CriticalSK lemma disorderLaw_temperature_map (n : ℕ) (β : ℝ) : (disorderLaw n).map (fun W => β • W) = SKGap.disorderLaw β n := by unfold disorderLaw SKGap.disorderLaw change (Measure.pi (fun _ : Edge n => gaussianReal 0 (n : ℝ≥0)⁻¹)).map (fun W e => β * W e) = _ rw [Measure.pi_map_pi (f := fun _ : Edge n => fun a : ℝ => β * a) (fun _ => (measurable_const.mul measurable_id).aemeasurable)] congr 1 funext e rw [gaussianReal_map_const_mul, mul_zero] congr 1 apply NNReal.coe_injective simp only [NNReal.coe_mul, NNReal.coe_mk, NNReal.coe_inv, NNReal.coe_natCast] rw [Real.coe_toNNReal _ (div_nonneg (sq_nonneg β) (Nat.cast_nonneg n))] exact (div_eq_mul_inv _ _).symm lemma companion_hamiltonian {n : ℕ} (W : Disorder n) (x : Spin n) : SKGap.hamiltonian W 0 x = hamiltonian W x := by unfold SKGap.hamiltonian simp only [Pi.zero_apply, zero_mul, Finset.sum_const_zero, add_zero] rw [symmetric_sum_upper _ (by intro i j rw [SKGap.coupling_symm W i j] ring)] have hd : (∑ i : Fin n, SKGap.spinValue (x i) * SKGap.coupling W i i * SKGap.spinValue (x i)) = 0 := by simp [SKGap.coupling_diag] rw [hd, zero_add] have he : (∑ e : Edge n, SKGap.spinValue (x e.val.1) * SKGap.coupling W e.val.1 e.val.2 * SKGap.spinValue (x e.val.2)) = hamiltonian W x := by unfold hamiltonian apply Finset.sum_congr rfl intro e _ simp only [SKGap.coupling, dite_eq_left e.property] change spinValue (x e.val.1) * W e * spinValue (x e.val.2) = _ ring rw [he] ring lemma companion_partition {n : ℕ} (W : Disorder n) : SKGap.partition W 0 = partition W := by simp only [SKGap.partition, SKGap.weight, companion_hamiltonian, partition] lemma companion_mass {n : ℕ} (W : Disorder n) (x : Spin n) : SKGap.mass W 0 x = gibbs W x := by rw [SKGap.mass, SKGap.weight, companion_hamiltonian, companion_partition] rfl lemma companion_expectation {n : ℕ} (W : Disorder n) (f : Spin n → ℝ) : SKGap.expectation W 0 f = mean W f := by simp only [SKGap.expectation, companion_mass, mean] lemma companion_variance {n : ℕ} (W : Disorder n) (f : Spin n → ℝ) : SKGap.variance W 0 f = variance W f := by simp only [SKGap.variance, companion_expectation, variance] lemma companion_conditionalExpectation {n : ℕ} (W : Disorder n) (i : Fin n) (f : Spin n → ℝ) (x : Spin n) : SKGap.conditionalExpectation W 0 i f x = ∑ y, siteKernel W i x y * f y := by rw [← siteAverage_eq, siteAverage_two] rw [← companion_mass W x, show flipSite i x = SKGap.flip i x from rfl, ← companion_mass W (SKGap.flip i x)] simp only [SKGap.conditionalExpectation, SKGap.mass, div_mul_eq_mul_div, ← add_div, div_div_div_cancel_right₀ (ne_of_gt (SKGap.partition_pos W 0))] lemma companion_dirichlet {n : ℕ} (W : Disorder n) (f : Spin n → ℝ) : SKGap.dirichlet W 0 f = dirichlet W f := by simp only [SKGap.dirichlet, companion_expectation, companion_conditionalExpectation, dirichlet] lemma companion_poincare_preimage (n : ℕ) (β C : ℝ) : (fun W : Disorder n => β • W) ⁻¹' SKGap.poincareEvent n C = poincareEvent n β C := by ext W simp only [Set.mem_preimage, SKGap.poincareEvent, poincareEvent, Set.mem_ofPred_eq, companion_variance, companion_dirichlet] lemma companion_poincare_measurable (n : ℕ) (C : ℝ) : MeasurableSet (SKGap.poincareEvent n C) := by have he : SKGap.poincareEvent n C = poincareEvent n 1 C := by simpa only [one_smul, Set.preimage_id'] using companion_poincare_preimage n 1 C rw [he] exact (poincareEvent_closed n 1 C).measurableSet lemma companion_poincare_probability (n : ℕ) (β C : ℝ) : SKGap.disorderLaw β n (SKGap.poincareEvent n C) = disorderLaw n (poincareEvent n β C) := by rw [← disorderLaw_temperature_map, Measure.map_apply (continuous_const_smul β).measurable (companion_poincare_measurable n C), companion_poincare_preimage] theorem fixed_temperature_poincare (β : ℝ) (hβ0 : 0 < β) (hβ1 : β < 1) : ∃ C : ℝ, 1 ≤ C ∧ Tendsto (fun n : ℕ => (disorderLaw n).real (poincareEvent n β C)) atTop (𝓝 1) := by obtain ⟨C, hC, hP, _⟩ := SKGap.sk_main β hβ0 hβ1 have hp : Tendsto (fun n : ℕ => (disorderLaw n).real (poincareEvent n β C)) atTop (𝓝 1) := by simp_rw [companion_poincare_probability] at hP simpa only [Measure.real, ENNReal.toReal_one, Function.comp_def] using (ENNReal.tendsto_toReal (by simp : (1 : ℝ≥0∞) ≠ ⊤)).comp hP refine ⟨max 1 C, le_max_left _ _, ?_⟩ apply tendsto_of_tendsto_of_tendsto_of_le_of_le hp tendsto_const_nhds · intro n refine measureReal_mono ?_ intro W hW f exact (hW f).trans (mul_le_mul_of_nonneg_right (le_max_right _ _) (dirichlet_nonneg (β • W) f)) · intro n exact measureReal_le_one end CriticalSK end end OAI