openAI-math-dataset / lean /OAI /Probability /InvariantIsing /Spectral /SelectedCompactPressure.lean
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import OAI.Probability.InvariantIsing.Spectral.SelectedPartitionPressure
import OAI.Probability.InvariantIsing.Spectral.CompactPartitionContinuity
import OAI.Probability.InvariantIsing.Spectral.SpectralApproximationSqueeze
namespace OAI
/-! Compact spectral pressure along arbitrary diverging dimensions. -/
noncomputable section
open MeasureTheory ProbabilityTheory IsingPerceptron Filter Set
open scoped Topology
namespace InvariantIsing
theorem selected_compact_pressure_tendsto
(hhaar : HaarConcentrationInput) (hgauss : GaussianLipschitzVarianceInput)
(hpub : PanchenkoTalagrandFieldPairInput)
(μ : (N : ℕ) → Measure (Orthogonal N)) [∀ N, IsProbabilityMeasure (μ N)]
[∀ N, (μ N).IsMulRightInvariant]
(N : ℕ → ℕ) (hN : ∀ k, 0 < N k) (hNlim : Tendsto N atTop atTop)
(eig : (k : ℕ) → Fin (N k) → ℝ) (ν : ProbabilityMeasure ℝ) (a b : ℝ)
(hcompact : IsCompact (ν : Measure ℝ).support)
(hbound : (ν : Measure ℝ).support ⊆ Icc a b)
(ha : a∈(ν : Measure ℝ).support) (hb : b∈(ν : Measure ℝ).support)
(heig : ∀ k i, eig k i∈Icc a b)
(hweak : Tendsto (fun k => empiricalSpectralLaw (hN k) (eig k)) atTop (𝓝 ν)) :
Tendsto (fun k => ∫ V, rotatedPressure (eig k) (matrixRotation V⁻¹) (fun _ => 0) ∂μ (N k))
atTop (𝓝 (variationalFunctional (measureR (ν : Measure ℝ) b)).toReal) := by
let δ := fun k : ℕ => (1 : ℝ)/(k+1)
let D (k : ℕ) : CompactSpectralPartition ν a b (δ k) := Classical.choice
(exists_compact_spectral_partition ν a b (δ k) hcompact hbound (by dsimp [δ]; positivity))
have hab : a ≤ b := (hbound ha).2
have hδ : Tendsto δ atTop (𝓝 0) := tendsto_one_div_add_atTop_nhds_zero_nat (𝕜 := ℝ)
have hL := compact_partition_variational_tendsto ν a b δ D hab ha hb hbound hδ
apply spectral_approximation_squeeze _
(fun j k => ∫ V, rotatedPressure (fun i => (D j).lowerValue (eig k i))
(matrixRotation V⁻¹) (fun _ => 0) ∂μ (N k))
(fun j k => ∫ V, rotatedPressure (fun i => (D j).upperValue (eig k i))
(matrixRotation V⁻¹) (fun _ => 0) ∂μ (N k))
(fun j => (variationalFunctional (measureR ((D j).law : Measure ℝ) (D j).edge)).toReal)
δ _ hL hδ
(fun j => ((D j).selected_pressure_tendsto hhaar hgauss hpub μ N hN hNlim eig hweak).1)
(fun j => ((D j).selected_pressure_tendsto hhaar hgauss hpub μ N hN hNlim eig hweak).2)
intro j
exact Filter.Eventually.of_forall fun k =>
(D j).mean_pressure_bounds (hN k) (μ (N k)) (eig k) ha hb hab (heig k)
end InvariantIsing
end
end OAI