import OAI.Probability.InvariantIsing.Gaussian.MPClippedTransform namespace OAI /-! Weak convergence in probability of the actual Gaussian empirical law after clipping. -/ noncomputable section open MeasureTheory ProbabilityTheory Filter open scoped Topology namespace InvariantIsing theorem gaussianPattern_clipped_weak {α : ℝ} (hα : 0 < α) {Ω : Type*} [MeasurableSpace Ω] (P : Measure Ω) [IsProbabilityMeasure P] (Z : (N : ℕ) → Ω → EuclideanSpace ℝ (Fin N × Fin (gaussianPatternCount α N))) (hZ : ∀ N, HasLaw (Z N) (stdGaussian _) P) : TendstoInMeasure P (fun k ω => LevyProkhorov.ofMeasure ((empiricalSpectralLaw (Nat.succ_pos k) (gaussianPatternEigenvalues (Z (k+1) ω))).map (spectralClip 0 (marchenkoPasturB α)))) atTop (fun _ => LevyProkhorov.ofMeasure (⟨marchenkoPasturMeasure α,marchenkoPastur_probability hα⟩ : ProbabilityMeasure ℝ)) := by let R := marchenkoPasturB α have hR : 0 ≤ R := sq_nonneg _ let ν : ProbabilityMeasure ℝ := ⟨marchenkoPasturMeasure α,marchenkoPastur_probability hα⟩ let W := fun k ω => compactClippedLaw R hR (empiricalSpectralLaw (Nat.succ_pos k) (gaussianPatternEigenvalues (Z (k+1) ω))) have hh : ∀ t : {t : ℝ // 0 < t}, TendstoInMeasure P (fun k ω => ∫ x, compactResolventTest R t x ∂(W k ω : Measure _)) atTop (fun _ => ∫ x, compactResolventTest R t x ∂(compactClippedLaw R hR ν : Measure _)) := by intro t simp only [W,compactClippedLaw_integral] change TendstoInMeasure P _ atTop (fun _ => ∫ x, positiveResolventTest t (spectralClip 0 (marchenkoPasturB α) x) ∂marchenkoPasturMeasure α) rw [marchenkoPastur_clipped_transform hα t.property] exact gaussianPattern_clipped_stieltjes hα t.property P Z hZ have hc := compact_resolvent_tendstoInMeasure R P W (compactClippedLaw R hR ν) hh have hn : (compactClippedLaw R hR ν).map (fun x => (x : ℝ)) = ν := compactClippedLaw_real_eq R hR ν (marchenkoPastur_mem_nonnegative_interval hα) rw [hn] at hc simpa only [W,compactClippedLaw_real] using hc end InvariantIsing end end OAI