import OAI.Analysis.FreeEntropy.MicrostatesLower namespace OAI noncomputable section open MeasureTheory ProbabilityTheory Filter Set open scoped Topology ENNReal namespace FiniteEntropySeparation theorem chosen_cutoff_real_bound {h R δ Δ β : ℝ} (hh0 : 0 diagonalMicrostates (Model.τ chosenP) (Model.X chosenP h) R k (D k) have hs k : MeasurableSet (S k) := diagonalMicrostates_measurable _ _ _ _ _ have hv0 k : volume (S k)≠0 := matrixVolumeEntropy_ne_bot_volume (hD0 k) _ (ne_bot_of_gt ((EReal.bot_lt_coe β).trans (hvol k))) have hvt k : volume (S k)≠⊤ := ne_of_lt (microstates_volume_lt_top (Model.τ chosenP) (Model.X chosenP h) R hR k (D k) _) let μ := fun k => cond volume (S k) have hprob : ∀k,IsProbabilityMeasure (μ k) := fun k => cond_isProbabilityMeasure_of_finite (hv0 k) (hvt k) let : ∀k,IsProbabilityMeasure (μ k) := hprob have hμ k : ∀ᵐa ∂μ k,a∈S k := ae_cond_mem (hs k) have hn k : (S k).Nonempty := by apply Set.nonempty_iff_ne_empty.mpr intro he apply hv0 k rw [he,measure_empty] have hinit (k : ℕ) : β≤normalizedMatrixEntropy (μ k) (chosenStart h) := by have hnorm : ∀ᵐa ∂μ k,‖a‖≤Real.sqrt (((chosenP+1:ℕ):ℝ)*D k)*R := FreeTensor.diagonalMicrostates_norm_ae (Model.X chosenP h) hR μ hμ k have hb := normalizedMatrixEntropy_cond_lower (hD0 k) (S k) (hv0 k) (hvt k) (show 0≤Real.sqrt (((chosenP+1:ℕ):ℝ)*D k)*R by positivity) hnorm (chosenStart_pos hh0) have he : β<((D k:ℝ)^2)⁻¹*Real.log (volume (S k)).toReal+((chosenP+1:ℕ):ℝ)/2*Real.log (D k) := by apply EReal.coe_lt_coe_iff.mp have hbvol : (β:EReal)< matrixVolumeEntropy (S k) := hvol k rwa [matrixVolumeEntropy_coe (S k) (hv0 k) (hvt k)] at hbvol exact he.le.trans (by simpa only [zpow_neg,zpow_ofNat] using hb) have hterm := chosen_terminal_gaussian hD0 hDm.tendsto_atTop hh0 hh1 hR hδ hΔ hδΔ hsep hq hh hn μ hμ have hflow := Model.matrixFlow_limit chosenP chosenP_ge_two hD0 hDm.tendsto_atTop hh0 hR hn μ hμ (chosenStart_pos hh0) (chosenStart_le_time hh1) hinit hterm exact flow_to_chiStar_gap hh0 hh1 hflow theorem chosen_cutoff_bound {h R δ Δ : ℝ} (hh0 : 0