import Mathlib import OAI.Analysis.CoulombIonization.Localization.SqrtMultiplier namespace OAI noncomputable section namespace CoulombObservation open MeasureTheory Filter open scoped Topology BigOperators ContDiff section Work_ObservationIntegral_scope open MeasureTheory Set Filter open scoped ENNReal NNReal Topology lemma integrable_bounded_probability {Ω : Type*} [MeasurableSpace Ω] {μ : Measure Ω} [IsFiniteMeasure μ] {q : Ω → ℝ} (hq : Measurable q) (hn : ∀ x, 0 ≤ q x) (hb : ∀ x, q x ≤ 1) : Integrable q μ := by apply (integrable_const (1:ℝ)).mono' hq.aestronglyMeasurable exact ae_of_all _ (fun x => by simpa only [Real.norm_eq_abs, abs_of_nonneg (hn x)] using hb x) lemma bounded_probability_rpow_integrable {Ω : Type*} [MeasurableSpace Ω] {μ : Measure Ω} [IsFiniteMeasure μ] {q : Ω → ℝ} (hq : Measurable q) (hn : ∀ x, 0 ≤ q x) (hb : ∀ x, q x ≤ 1) {a : ℝ} (ha : 0 ≤ a) : Integrable (fun x => q x ^ a) μ := by apply integrable_bounded_probability (hq.pow_const a) · exact fun x => Real.rpow_nonneg (hn x) _ · exact fun x => Real.rpow_le_one (hn x) (hb x) ha lemma integral_bounded_probability_rpow {Ω : Type*} [MeasurableSpace Ω] {μ : Measure Ω} [IsProbabilityMeasure μ] {q : Ω → ℝ} (hq : Measurable q) (hn : ∀ x, 0 ≤ q x) (hb : ∀ x, q x ≤ 1) {a : ℝ} (ha : 0 ≤ a) (ha1 : a ≤ 1) : (∫ x, q x ^ a ∂μ) ≤ (∫ x, q x ∂μ)^a := by apply (Real.concaveOn_rpow ha ha1).le_map_integral · exact (Real.continuous_rpow_const ha).continuousOn · exact isClosed_Ici · exact ae_of_all _ hn · exact integrable_bounded_probability hq hn hb · exact bounded_probability_rpow_integrable hq hn hb ha def eventMomentOrder (p : ℝ) : ℕ := ⌈-Real.log p⌉₊+1 lemma eventMomentOrder_pos (p : ℝ) : 0 < eventMomentOrder p := by unfold eventMomentOrder; omega lemma eventMomentOrder_bound {p : ℝ} (hp : 0 < p) (hp1 : p ≤ 1) : (eventMomentOrder p : ℝ) ≤ 2*(1-Real.log p) := by have hl := Real.log_nonpos hp.le hp1 have hc := Nat.ceil_lt_add_one (show 0 ≤ -Real.log p by linarith) dsimp [eventMomentOrder] push_cast linarith lemma eventMomentOrder_rpow_bound {p : ℝ} (hp : 0 < p) : p ^ (-((eventMomentOrder p : ℝ)⁻¹)) ≤ Real.exp 1 := by rw [Real.rpow_def_of_pos hp, Real.exp_le_exp] have hk : (0:ℝ) < eventMomentOrder p := by exact_mod_cast eventMomentOrder_pos p have hc := Nat.le_ceil (-Real.log p) have hle : -Real.log p ≤ (eventMomentOrder p : ℝ) := by dsimp [eventMomentOrder]; push_cast; linarith rw [mul_neg, ← neg_mul, ← div_eq_mul_inv, div_le_iff₀ hk] simpa using hle lemma eventMomentOrder_integral_bound {p : ℝ} (hp : 0 < p) (hp1 : p ≤ 1) : (eventMomentOrder p : ℝ)^5 * p^(1-(eventMomentOrder p:ℝ)⁻¹) ≤ (32*Real.exp 1)*(1-Real.log p)^5*p := by have hl : 0 ≤ 1-Real.log p := by linarith [Real.log_nonpos hp.le hp1] have hk : 0 ≤ (eventMomentOrder p : ℝ) := Nat.cast_nonneg _ have hpow := pow_le_pow_left₀ hk (eventMomentOrder_bound hp hp1) 5 have hprod := mul_le_mul hpow (eventMomentOrder_rpow_bound hp) (Real.rpow_nonneg hp.le _) (by positivity : 0 ≤ (2*(1-Real.log p))^5) rw [sub_eq_add_neg, Real.rpow_add hp, Real.rpow_one] calc _ = ((eventMomentOrder p : ℝ)^5 * p^(-((eventMomentOrder p:ℝ)⁻¹)))*p := by ring _ ≤ (2*(1-Real.log p))^5 * Real.exp 1 * p := mul_le_mul_of_nonneg_right hprod hp.le _ = _ := by ring lemma eventLog_eq {p : ℝ} (hp : 0 < p) : Real.log (Real.exp 1/p) = 1-Real.log p := by rw [Real.log_div (ne_of_gt (Real.exp_pos _)) (ne_of_gt hp), Real.log_exp] end Work_ObservationIntegral_scope open MeasureTheory Set Finset open scoped ENNReal NNReal BigOperators ContDiff def arrayFisher {J I : Type*} [Fintype J] [Fintype I] [DecidableEq I] (b : J → ℝ) (s : Set (J × I → ℝ)) (x : I → ℝ) : ℝ := ∑ i, (lineDeriv ℝ (fun y => Real.sqrt (arrayLikelihood b s y)) x (Pi.single i 1))^2 lemma arrayFisher_nonneg {J I : Type*} [Fintype J] [Fintype I] [DecidableEq I] (b : J → ℝ) (s : Set (J × I → ℝ)) (x : I → ℝ) : 0 ≤ arrayFisher b s x := sum_nonneg (fun _ _ => sq_nonneg _) lemma arrayFisher_measurable {J I : Type*} [Fintype J] [Fintype I] [DecidableEq I] (b : J → ℝ) {s : Set (J × I → ℝ)} (hs : MeasurableSet s) : Measurable (arrayFisher b s) := by apply Finset.measurable_sum intro i _ exact (measurable_lineDeriv (sqrtArrayLikelihood_lipschitz b hs).continuous).pow_const 2 lemma reciprocal_moment_sub_one_nonneg {k : ℕ} (hk : 0 < k) : 0 ≤ 1-(k:ℝ)⁻¹ := by have hh : (1:ℝ) ≤ k := by exact_mod_cast hk have hi : (k:ℝ)⁻¹ ≤ 1 := inv_le_one_of_one_le₀ hh linarith lemma arrayFisher_integrable {J I : Type*} [Fintype J] [Fintype I] [DecidableEq I] (b : J → ℝ) {s : Set (J × I → ℝ)} (hs : MeasurableSet s) (μ : Measure (I → ℝ)) [IsFiniteMeasure μ] : Integrable (arrayFisher b s) μ := by have hC := observationMomentConstant_pos have hbound (x : I → ℝ) : arrayFisher b s x ≤ (observationMomentConstant/4) * ∑ j, (b j)^2 := by simpa [arrayFisher] using sqrtArrayLikelihood_lineDeriv_sq b hs x (k := 1) (by decide) apply (integrable_const ((observationMomentConstant/4) * ∑ j, (b j)^2)).mono' (arrayFisher_measurable b hs).aestronglyMeasurable filter_upwards [] with x simpa only [Real.norm_eq_abs, abs_of_nonneg (arrayFisher_nonneg b s x)] using hbound x lemma arrayFisher_integral_moment {J I : Type*} [Fintype J] [Fintype I] [DecidableEq I] (b : J → ℝ) {s : Set (J × I → ℝ)} (hs : MeasurableSet s) (μ : Measure (I → ℝ)) [IsProbabilityMeasure μ] {k : ℕ} (hk : 0 < k) : (∫ x, arrayFisher b s x ∂μ) ≤ (observationMomentConstant/4) * (k:ℝ)^5 * (∑ j, (b j)^2) * (∫ x, arrayLikelihood b s x ∂μ)^(1-(k:ℝ)⁻¹) := by have ha := reciprocal_moment_sub_one_nonneg hk have ha1 : 1-(k:ℝ)⁻¹ ≤ 1 := sub_le_self _ (inv_nonneg.mpr (Nat.cast_nonneg _)) have hq := (arrayLikelihood_contDiff b hs (n := 1)).continuous.measurable have hC := observationMomentConstant_pos have hj := integral_bounded_probability_rpow (μ := μ) hq (arrayLikelihood_nonneg b hs) (arrayLikelihood_le_one b hs) ha ha1 calc _ ≤ ∫ x, (observationMomentConstant/4) * (k:ℝ)^5 * (∑ j, (b j)^2) * (arrayLikelihood b s x)^(1-(k:ℝ)⁻¹) ∂μ := by apply integral_mono (arrayFisher_integrable b hs μ) ((bounded_probability_rpow_integrable hq (arrayLikelihood_nonneg b hs) (arrayLikelihood_le_one b hs) ha).const_mul _) exact fun x => sqrtArrayLikelihood_lineDeriv_sq b hs x hk _ = ((observationMomentConstant/4) * (k:ℝ)^5 * (∑ j, (b j)^2)) * ∫ x, (arrayLikelihood b s x)^(1-(k:ℝ)⁻¹) ∂μ := integral_const_mul _ _ _ ≤ _ := mul_le_mul_of_nonneg_left hj (by positivity) def observationFisherConstant : ℝ := 8 * Real.exp 1 * observationMomentConstant lemma observationFisherConstant_pos : 0 < observationFisherConstant := by unfold observationFisherConstant exact mul_pos (mul_pos (by norm_num) (Real.exp_pos _)) observationMomentConstant_pos theorem arrayFisher_integral_log {J I : Type*} [Fintype J] [Fintype I] [DecidableEq I] (b : J → ℝ) {s : Set (J × I → ℝ)} (hs : MeasurableSet s) (μ : Measure (I → ℝ)) [IsProbabilityMeasure μ] (hp : 0 < ∫ x, arrayLikelihood b s x ∂μ) : (∫ x, arrayFisher b s x ∂μ) ≤ observationFisherConstant * (∑ j, (b j)^2) * (Real.log (Real.exp 1/(∫ x, arrayLikelihood b s x ∂μ)))^5 * (∫ x, arrayLikelihood b s x ∂μ) := by let p := ∫ x, arrayLikelihood b s x ∂μ have hp1 : p ≤ 1 := by have h := integral_mono (integrable_bounded_probability (μ := μ) ((arrayLikelihood_contDiff b hs (n:=1)).continuous.measurable) (arrayLikelihood_nonneg b hs) (arrayLikelihood_le_one b hs)) (integrable_const (1:ℝ)) (arrayLikelihood_le_one b hs) simpa [p] using h have hC := observationMomentConstant_pos have hb : 0 ≤ ∑ j, (b j)^2 := sum_nonneg (fun _ _ => sq_nonneg _) have hbound := arrayFisher_integral_moment b hs μ (eventMomentOrder_pos p) have hlog := mul_le_mul_of_nonneg_left (eventMomentOrder_integral_bound hp hp1) (show 0 ≤ observationMomentConstant/4 * ∑ j, (b j)^2 by positivity) change _ ≤ observationFisherConstant * (∑ j, (b j)^2) * Real.log (Real.exp 1/p)^5 * p rw [eventLog_eq hp] calc _ ≤ (observationMomentConstant/4) * (eventMomentOrder p:ℝ)^5 * (∑ j, (b j)^2) * p^(1-(eventMomentOrder p:ℝ)⁻¹) := hbound _ = (observationMomentConstant/4 * ∑ j, (b j)^2) * ((eventMomentOrder p:ℝ)^5 * p^(1-(eventMomentOrder p:ℝ)⁻¹)) := by ring _ ≤ (observationMomentConstant/4 * ∑ j, (b j)^2) * ((32*Real.exp 1)*(1-Real.log p)^5*p) := hlog _ = _ := by dsimp [observationFisherConstant]; ring end CoulombObservation end end OAI