import Mathlib.Probability.Kernel.Composition.CompProd import OAI.NumberTheory.Jacobsthal.Analysis.WeightIntegrals import OAI.NumberTheory.Jacobsthal.Sieve.CompactExponentialMoments namespace OAI namespace Erdos970 section namespace NumberTheoryLean.KernelDensityBridge open Set MeasureTheory ProbabilityTheory open scoped ProbabilityTheory ENNReal open DerivativeWeights TransitionKernels FinitePathGeometry FinitePathMeasures theorem evenToOdd_map_ratio (s : EvenState) : (evenToOdd s).map (Subtype.val : OddState → ℝ) = evenKernel s := by calc _ = (evenKernel s).restrict (Ici (95 / 100 : ℝ)) := by change ((evenKernel s).comap (Subtype.val : OddState → ℝ)).map Subtype.val = _ exact map_comap_subtype_coe (μ := evenKernel s) (s := Ici (95 / 100 : ℝ)) measurableSet_Ici _ = _ := Measure.restrict_eq_self_of_ae_mem (evenKernel_ae_odd_domain s) theorem oddToEven_map_ratio (s : OddState) : (oddToEven s).map (Subtype.val : EvenState → ℝ) = oddKernel s := by calc _ = (oddKernel s).restrict (Ici (198 / 100 : ℝ)) := by change ((oddKernel s).comap (Subtype.val : EvenState → ℝ)).map Subtype.val = _ exact map_comap_subtype_coe (μ := oddKernel s) (s := Ici (198 / 100 : ℝ)) measurableSet_Ici _ = _ := Measure.restrict_eq_self_of_ae_mem (oddKernel_ae_even_domain s) theorem stateKernel_even_ratio (s : EvenState) : (stateKernel (.inl s)).map stateRatio = evenKernel s := by change (evenBranch s).map stateRatio = _ rw [evenBranch, Kernel.map_apply _ measurable_inr, Measure.map_map stateRatio_measurable measurable_inr] exact evenToOdd_map_ratio s theorem stateKernel_odd_ratio (s : OddState) : (stateKernel (.inr s)).map stateRatio = oddKernel s := by change (oddBranch s).map stateRatio = _ rw [oddBranch, Kernel.map_apply _ measurable_inl, Measure.map_map stateRatio_measurable measurable_inl] exact oddToEven_map_ratio s theorem evenToOdd_lintegral_ratio (s : EvenState) {H : ℝ → ℝ≥0∞} (hH : Measurable H) : (∫⁻ t : OddState, H t.1 ∂evenToOdd s) = ∫⁻ t, H t ∂evenKernel s := by rw [← evenToOdd_map_ratio, lintegral_map hH measurable_subtype_coe] theorem oddToEven_lintegral_ratio (s : OddState) {H : ℝ → ℝ≥0∞} (hH : Measurable H) : (∫⁻ t : EvenState, H t.1 ∂oddToEven s) = ∫⁻ t, H t ∂oddKernel s := by rw [← oddToEven_map_ratio, lintegral_map hH measurable_subtype_coe] theorem evenKernel_lintegral_density (s : EvenState) {H : ℝ → ℝ≥0∞} (hH : Measurable H) : (∫⁻ t, H t ∂evenKernel s) = ∫⁻ t, ENNReal.ofReal (transitionDensity .even s.1 t) * H t := by exact Kernel.lintegral_withDensity (Kernel.const EvenState volume) (f := fun s t => ENNReal.ofReal (evenDensity s t)) (ENNReal.measurable_ofReal.comp evenDensity_measurable) s hH theorem oddKernel_lintegral_density (s : OddState) {H : ℝ → ℝ≥0∞} (hH : Measurable H) : (∫⁻ t, H t ∂oddKernel s) = ∫⁻ t, ENNReal.ofReal (transitionDensity .odd s.1 t) * H t := by exact Kernel.lintegral_withDensity (Kernel.const OddState volume) (f := fun s t => ENNReal.ofReal (oddDensity s t)) (ENNReal.measurable_ofReal.comp oddDensity_measurable) s hH theorem transitionDensity_joint_measurable (i : Side) : Measurable (Function.uncurry (transitionDensity i)) := by cases i with | even => change Measurable (fun x : ℝ × ℝ => if x.1 - 1 ≤ x.2 then W x.2 * phiOdd x.2 / phiEven x.1 else 0) apply Measurable.ite (measurableSet_le (measurable_fst.sub measurable_const) measurable_snd) · exact ((W_measurable.comp measurable_snd).mul (phiOdd_continuous.measurable.comp measurable_snd)).div (phiEven_measurable.comp measurable_fst) · exact measurable_const | odd => change Measurable (fun x : ℝ × ℝ => if max 2 (x.1 - 1) ≤ x.2 then W x.2 * phiEven x.2 / phiOdd x.1 else 0) apply Measurable.ite (measurableSet_le (measurable_const.max (measurable_fst.sub measurable_const)) measurable_snd) · exact ((W_measurable.comp measurable_snd).mul (phiEven_measurable.comp measurable_snd)).div (phiOdd_continuous.measurable.comp measurable_fst) · exact measurable_const noncomputable def evenTwoStep : Kernel EvenState (ℝ × ℝ) := (evenToOdd ⊗ₖ oddToEven.prodMkLeft EvenState).map (fun x : OddState × EvenState => (x.1.1, x.2.1)) noncomputable def oddTwoStep : Kernel OddState (ℝ × ℝ) := (oddToEven ⊗ₖ evenToOdd.prodMkLeft OddState).map (fun x : EvenState × OddState => (x.1.1, x.2.1)) instance evenTwoStep_isMarkovKernel : IsMarkovKernel evenTwoStep := Kernel.IsMarkovKernel.map _ ((measurable_subtype_coe.comp measurable_fst).prodMk (measurable_subtype_coe.comp measurable_snd)) instance oddTwoStep_isMarkovKernel : IsMarkovKernel oddTwoStep := Kernel.IsMarkovKernel.map _ ((measurable_subtype_coe.comp measurable_fst).prodMk (measurable_subtype_coe.comp measurable_snd)) theorem evenTwoStep_lintegral (s : EvenState) {H : ℝ × ℝ → ℝ≥0∞} (hH : Measurable H) : (∫⁻ x, H x ∂evenTwoStep s) = ∫⁻ t, ∫⁻ u, ENNReal.ofReal (transitionDensity .even s.1 t) * ENNReal.ofReal (transitionDensity .odd t u) * H (t, u) := by have hm : Measurable (fun x : OddState × EvenState => (x.1.1, x.2.1)) := (measurable_subtype_coe.comp measurable_fst).prodMk (measurable_subtype_coe.comp measurable_snd) rw [evenTwoStep, Kernel.lintegral_map _ hm _ hH] rw [Kernel.lintegral_compProd evenToOdd (oddToEven.prodMkLeft EvenState) s (f := fun x : OddState × EvenState => H (x.1.1, x.2.1)) (hH.comp hm)] change (∫⁻ t : OddState, ∫⁻ u : EvenState, H (t.1, u.1) ∂oddToEven t ∂evenToOdd s) = _ have hinner : ∀ t : OddState, (∫⁻ u : EvenState, H (t.1, u.1) ∂oddToEven t) = ∫⁻ u, ENNReal.ofReal (transitionDensity .odd t.1 u) * H (t.1, u) := by intro t rw [oddToEven_lintegral_ratio t (H := fun u : ℝ => H (t.1, u)) (hH.comp measurable_prodMk_left), oddKernel_lintegral_density t (H := fun u : ℝ => H (t.1, u)) (hH.comp measurable_prodMk_left)] simp_rw [hinner] have hJ : Measurable (fun t : ℝ => ∫⁻ u, ENNReal.ofReal (transitionDensity .odd t u) * H (t, u)) := ((ENNReal.measurable_ofReal.comp (transitionDensity_joint_measurable .odd)).mul hH).lintegral_prod_right rw [evenToOdd_lintegral_ratio s hJ, evenKernel_lintegral_density s hJ] apply lintegral_congr intro t rw [← lintegral_const_mul' _ _ ENNReal.ofReal_ne_top] apply lintegral_congr intro u ring theorem oddTwoStep_lintegral (s : OddState) {H : ℝ × ℝ → ℝ≥0∞} (hH : Measurable H) : (∫⁻ x, H x ∂oddTwoStep s) = ∫⁻ t, ∫⁻ u, ENNReal.ofReal (transitionDensity .odd s.1 t) * ENNReal.ofReal (transitionDensity .even t u) * H (t, u) := by have hm : Measurable (fun x : EvenState × OddState => (x.1.1, x.2.1)) := (measurable_subtype_coe.comp measurable_fst).prodMk (measurable_subtype_coe.comp measurable_snd) rw [oddTwoStep, Kernel.lintegral_map _ hm _ hH] rw [Kernel.lintegral_compProd oddToEven (evenToOdd.prodMkLeft OddState) s (f := fun x : EvenState × OddState => H (x.1.1, x.2.1)) (hH.comp hm)] change (∫⁻ t : EvenState, ∫⁻ u : OddState, H (t.1, u.1) ∂evenToOdd t ∂oddToEven s) = _ have hinner : ∀ t : EvenState, (∫⁻ u : OddState, H (t.1, u.1) ∂evenToOdd t) = ∫⁻ u, ENNReal.ofReal (transitionDensity .even t.1 u) * H (t.1, u) := by intro t rw [evenToOdd_lintegral_ratio t (H := fun u : ℝ => H (t.1, u)) (hH.comp measurable_prodMk_left), evenKernel_lintegral_density t (H := fun u : ℝ => H (t.1, u)) (hH.comp measurable_prodMk_left)] simp_rw [hinner] have hJ : Measurable (fun t : ℝ => ∫⁻ u, ENNReal.ofReal (transitionDensity .even t u) * H (t, u)) := ((ENNReal.measurable_ofReal.comp (transitionDensity_joint_measurable .even)).mul hH).lintegral_prod_right rw [oddToEven_lintegral_ratio s hJ, oddKernel_lintegral_density s hJ] apply lintegral_congr intro t rw [← lintegral_const_mul' _ _ ENNReal.ofReal_ne_top] apply lintegral_congr intro u ring noncomputable def jointDensity (i : Side) (s : ℝ) (x : ℝ × ℝ) : ℝ≥0∞ := ENNReal.ofReal (transitionDensity i s x.1) * ENNReal.ofReal (transitionDensity i.flip x.1 x.2) theorem jointDensity_measurable (i : Side) (s : ℝ) : Measurable (jointDensity i s) := by exact (ENNReal.measurable_ofReal.comp ((transitionDensity_joint_measurable i).comp (measurable_const.prodMk measurable_fst))).mul (ENNReal.measurable_ofReal.comp (transitionDensity_joint_measurable i.flip)) theorem evenTwoStep_eq_withDensity (s : EvenState) : evenTwoStep s = ((volume : Measure ℝ).prod volume).withDensity (jointDensity .even s.1) := by apply Measure.ext_of_lintegral intro H hH rw [evenTwoStep_lintegral s hH, lintegral_withDensity_eq_lintegral_mul _ (jointDensity_measurable .even s.1) hH] have hp := lintegral_prod (μ := (volume : Measure ℝ)) (ν := (volume : Measure ℝ)) (fun x => jointDensity .even s.1 x * H x) ((jointDensity_measurable .even s.1).mul hH).aemeasurable exact hp.symm theorem oddTwoStep_eq_withDensity (s : OddState) : oddTwoStep s = ((volume : Measure ℝ).prod volume).withDensity (jointDensity .odd s.1) := by apply Measure.ext_of_lintegral intro H hH rw [oddTwoStep_lintegral s hH, lintegral_withDensity_eq_lintegral_mul _ (jointDensity_measurable .odd s.1) hH] have hp := lintegral_prod (μ := (volume : Measure ℝ)) (ν := (volume : Measure ℝ)) (fun x => jointDensity .odd s.1 x * H x) ((jointDensity_measurable .odd s.1).mul hH).aemeasurable exact hp.symm end NumberTheoryLean.KernelDensityBridge end section namespace NumberTheoryLean.JointMinorization open Filter Set MeasureTheory ProbabilityTheory open scoped ProbabilityTheory ENNReal open DerivativeWeights TransitionKernels FinitePathGeometry FinitePathMeasures open KernelDensityBridge TwoStepDensityBounds def rectangle (L : ℝ) : Set (ℝ × ℝ) := Icc L (L + 1) ×ˢ Icc (L + 1) (L + 2) theorem rectangle_measurable (L : ℝ) : MeasurableSet (rectangle L) := measurableSet_Icc.prod measurableSet_Icc noncomputable def rectangleLaw (L : ℝ) : Measure (ℝ × ℝ) := ((volume : Measure ℝ).prod volume).restrict (rectangle L) instance rectangleLaw_isProbabilityMeasure (L : ℝ) : IsProbabilityMeasure (rectangleLaw L) := by constructor rw [rectangleLaw, Measure.restrict_apply MeasurableSet.univ, univ_inter, rectangle, Measure.prod_prod, Real.volume_Icc, Real.volume_Icc] rw [show L + 1 - L = 1 by ring, show L + 2 - (L + 1) = 1 by ring] norm_num theorem transitionDensity_nonneg {i : Side} {s : ℝ} (hs : Valid i s) (t : ℝ) : 0 ≤ transitionDensity i s t := by cases i with | even => exact evenDensity_nonneg ⟨s, hs⟩ t | odd => exact oddDensity_nonneg ⟨s, hs⟩ t theorem rectangle_minorization {i : Side} {s L : ℝ} (hL : 3 ≤ L) (hs : Valid i s) (hsL : s ≤ L) : ENNReal.ofReal (minorizationSize L) • rectangleLaw L ≤ ((volume : Measure ℝ).prod volume).withDensity (jointDensity i s) := by rw [rectangleLaw, ← withDensity_const, ← withDensity_indicator (rectangle_measurable L)] apply withDensity_mono apply Eventually.of_forall intro x by_cases hx : x ∈ rectangle L · rw [indicator_of_mem hx] change ENNReal.ofReal (minorizationSize L) ≤ ENNReal.ofReal (transitionDensity i s x.1) * ENNReal.ofReal (transitionDensity i.flip x.1 x.2) rw [← ENNReal.ofReal_mul (transitionDensity_nonneg hs x.1)] exact ENNReal.ofReal_le_ofReal (le_trans (minorizationSize_le_rectangle i L) (rectangle_density_lower hL hs hsL hx.1 hx.2)) · rw [indicator_of_notMem hx] exact zero_le theorem evenTwoStep_rectangle_minorization {L : ℝ} (hL : 3 ≤ L) (s : EvenState) (hs : s.1 ≤ L) : ENNReal.ofReal (minorizationSize L) • rectangleLaw L ≤ evenTwoStep s := by rw [evenTwoStep_eq_withDensity] exact rectangle_minorization hL s.2 hs theorem oddTwoStep_rectangle_minorization {L : ℝ} (hL : 3 ≤ L) (s : OddState) (hs : s.1 ≤ L) : ENNReal.ofReal (minorizationSize L) • rectangleLaw L ≤ oddTwoStep s := by rw [oddTwoStep_eq_withDensity] exact rectangle_minorization hL s.2 hs noncomputable def pairCost (T : ℝ) (x : ℝ × ℝ) : ℝ × ℝ := (x.2, T + cost x.1 + cost x.2) theorem pairCost_measurable (T : ℝ) : Measurable (pairCost T) := measurable_snd.prodMk ((measurable_const.add (cost_measurable.comp measurable_fst)).add (cost_measurable.comp measurable_snd)) noncomputable def minorizingLaw (L T : ℝ) : Measure (ℝ × ℝ) := (rectangleLaw L).map (pairCost T) instance minorizingLaw_isProbabilityMeasure (L T : ℝ) : IsProbabilityMeasure (minorizingLaw L T) := (Measure.isProbabilityMeasure_map_iff (μ := rectangleLaw L) (pairCost_measurable T).aemeasurable).mpr inferInstance noncomputable def evenJointKernel (T : ℝ) : Kernel EvenState (ℝ × ℝ) := evenTwoStep.map (pairCost T) noncomputable def oddJointKernel (T : ℝ) : Kernel OddState (ℝ × ℝ) := oddTwoStep.map (pairCost T) instance evenJointKernel_isMarkovKernel (T : ℝ) : IsMarkovKernel (evenJointKernel T) := Kernel.IsMarkovKernel.map _ (pairCost_measurable T) instance oddJointKernel_isMarkovKernel (T : ℝ) : IsMarkovKernel (oddJointKernel T) := Kernel.IsMarkovKernel.map _ (pairCost_measurable T) theorem even_joint_minorization {L : ℝ} (hL : 3 ≤ L) (s : EvenState) (hs : s.1 ≤ L) (T : ℝ) : ENNReal.ofReal (minorizationSize L) • minorizingLaw L T ≤ evenJointKernel T s := by rw [evenJointKernel, Kernel.map_apply _ (pairCost_measurable T)] have h := Measure.map_mono (evenTwoStep_rectangle_minorization hL s hs) (pairCost_measurable T) rw [Measure.map_smul _ (pairCost_measurable T).aemeasurable] at h exact h theorem odd_joint_minorization {L : ℝ} (hL : 3 ≤ L) (s : OddState) (hs : s.1 ≤ L) (T : ℝ) : ENNReal.ofReal (minorizationSize L) • minorizingLaw L T ≤ oddJointKernel T s := by rw [oddJointKernel, Kernel.map_apply _ (pairCost_measurable T)] have h := Measure.map_mono (oddTwoStep_rectangle_minorization hL s hs) (pairCost_measurable T) rw [Measure.map_smul _ (pairCost_measurable T).aemeasurable] at h exact h theorem compact_joint_minorization (S : ℝ) : ∃ L ε : ℝ, 3 ≤ L ∧ S ≤ L ∧ 0 < ε ∧ ε ≤ 1 ∧ (∀ T : ℝ, IsProbabilityMeasure (minorizingLaw L T)) ∧ (∀ T : ℝ, ∀ s : EvenState, s.1 ≤ S → ENNReal.ofReal ε • minorizingLaw L T ≤ evenJointKernel T s) ∧ (∀ T : ℝ, ∀ s : OddState, s.1 ≤ S → ENNReal.ofReal ε • minorizingLaw L T ≤ oddJointKernel T s) := by refine ⟨max 3 S, minorizationSize (max 3 S), le_max_left _ _, le_max_right _ _, minorizationSize_pos (le_max_left _ _), minorizationSize_le_one _, ?_, ?_, ?_⟩ · intro T infer_instance · intro T s hs exact even_joint_minorization (le_max_left _ _) s (le_trans hs (le_max_right _ _)) T · intro T s hs exact odd_joint_minorization (le_max_left _ _) s (le_trans hs (le_max_right _ _)) T end NumberTheoryLean.JointMinorization end section namespace NumberTheoryLean.GoodPairTransitions open Filter Set MeasureTheory ProbabilityTheory open scoped ENNReal open BuchstabBridge DerivativeWeights WeightFutureIntegrals TransitionKernels open FinitePathGeometry FinitePathMeasures KernelDensityBridge TwoStepDensityBounds JointMinorization def goodPair (s : ℝ) : Set (ℝ × ℝ) := {x | x.1 ∈ Icc (max 2 (s - 1)) (max 2 (s - 1) + 1 / 4) ∧ x.2 ∈ Icc (x.1 - 1) (x.1 - 3 / 4)} theorem goodPair_measurable (s : ℝ) : MeasurableSet (goodPair s) := by exact ((measurableSet_le measurable_const measurable_fst).inter (measurableSet_le measurable_fst measurable_const)).inter ((measurableSet_le (measurable_fst.sub measurable_const) measurable_snd).inter (measurableSet_le measurable_snd (measurable_fst.sub measurable_const))) theorem goodPair_volume (s : ℝ) : ((volume : Measure ℝ).prod volume) (goodPair s) = ENNReal.ofReal (1 / 16 : ℝ) := by rw [Measure.prod_apply (goodPair_measurable s)] have heq : ∀ t : ℝ, volume (Prod.mk t ⁻¹' goodPair s) = (Icc (max 2 (s - 1)) (max 2 (s - 1) + 1 / 4)).indicator (fun _ => ENNReal.ofReal (1 / 4 : ℝ)) t := by intro t by_cases ht : t ∈ Icc (max 2 (s - 1)) (max 2 (s - 1) + 1 / 4) · have hp : Prod.mk t ⁻¹' goodPair s = Icc (t - 1) (t - 3 / 4) := by ext u simp only [mem_preimage, goodPair, mem_ofPred_eq, ht, true_and] rw [hp, Real.volume_Icc, indicator_of_mem ht] congr 1 ring · have hp : Prod.mk t ⁻¹' goodPair s = ∅ := by ext u simp only [mem_preimage, goodPair, mem_ofPred_eq, ht, false_and, mem_empty_iff_false] rw [hp, measure_empty, indicator_of_notMem ht] rw [lintegral_congr heq, lintegral_indicator measurableSet_Icc, setLIntegral_const, Real.volume_Icc] rw [show max 2 (s - 1) + 1 / 4 - max 2 (s - 1) = (1 : ℝ) / 4 by ring] rw [← ENNReal.ofReal_mul (by norm_num : (0 : ℝ) ≤ 1 / 4)] congr 1 norm_num theorem goodPair_bounds {s M t u : ℝ} (hM : 4 ≤ M) (hs : s ≤ M) (hg : (t, u) ∈ goodPair s) : 2 ≤ t ∧ 1 ≤ u ∧ t ≤ M ∧ u ≤ M := by have ht2 : 2 ≤ t := le_trans (le_max_left _ _) hg.1.1 have ha : max 2 (s - 1) ≤ M - 1 := max_le (by linarith) (by linarith) exact ⟨ht2, by linarith [hg.2.1], by linarith [hg.1.2], by linarith [hg.1.2, hg.2.2]⟩ theorem goodPair_terminal {s t u : ℝ} (hg : (t, u) ∈ goodPair s) : u ≤ max (3 / 2) (s - 3 / 2) := by by_cases hs : s ≤ 3 · have ha : max 2 (s - 1) = 2 := max_eq_left (by linarith) have ht := hg.1.2 rw [ha] at ht exact le_trans (show u ≤ 3 / 2 by linarith [hg.2.2]) (le_max_left _ _) · have ha : max 2 (s - 1) = s - 1 := max_eq_right (by linarith) have ht := hg.1.2 rw [ha] at ht exact le_trans (show u ≤ s - 3 / 2 by linarith [hg.2.2]) (le_max_right _ _) theorem phiOdd_le_A (s : ℝ) : phiOdd s ≤ sieveA := by by_cases hs : s ≤ 3 · exact le_of_eq (phiOdd_initial hs) · have h := phiOdd_antitone (show 3 ≤ s by linarith) rwa [phiOdd_initial (s := 3) le_rfl] at h noncomputable def goodPairDensityLower (M : ℝ) : ℝ := (1 / M) ^ 2 * (phiOdd M / sieveA) theorem goodPairDensityLower_pos {M : ℝ} (hM : 4 ≤ M) : 0 < goodPairDensityLower M := by unfold goodPairDensityLower exact mul_pos (sq_pos_of_pos (one_div_pos.mpr (by linarith))) (div_pos (phiOdd_pos M) sieveA_pos) theorem goodPair_density_lower {M : ℝ} (hM : 4 ≤ M) (s : OddState) (hs : s.1 ≤ M) {t u : ℝ} (hg : (t, u) ∈ goodPair s.1) : goodPairDensityLower M ≤ transitionDensity .odd s.1 t * transitionDensity .even t u := by obtain ⟨ht2, hu1, htM, huM⟩ := goodPair_bounds hM hs hg have ht0 : 0 < t := by linarith have hu0 : 0 < u := by linarith have heq := two_step_density_eq (i := .odd) s.2 hg.1.1 hg.2.1 change transitionDensity .odd s.1 t * transitionDensity .even t u = (W t * W u) * (phiOdd u / phiOdd s.1) at heq rw [heq] have hW : (1 / M) ^ 2 ≤ W t * W u := by simpa only [pow_two] using mul_le_mul (W_lower ht0 htM) (W_lower hu0 huM) (one_div_nonneg.mpr (by linarith)) (W_pos ht0).le have hr : phiOdd M / sieveA ≤ phiOdd u / phiOdd s.1 := by calc _ ≤ phiOdd M / phiOdd s.1 := div_le_div_of_nonneg_left (phiOdd_pos M).le (phiOdd_pos s.1) (phiOdd_le_A s.1) _ ≤ _ := div_le_div_of_nonneg_right (phiOdd_antitone huM) (phiOdd_pos s.1).le exact mul_le_mul hW hr (div_pos (phiOdd_pos M) sieveA_pos).le (mul_pos (W_pos ht0) (W_pos hu0)).le theorem goodPair_measure_lower {M : ℝ} (hM : 4 ≤ M) (s : OddState) (hs : s.1 ≤ M) : ENNReal.ofReal (goodPairDensityLower M / 16) ≤ oddTwoStep s (goodPair s.1) := by have hdom : ENNReal.ofReal (goodPairDensityLower M) • ((volume : Measure ℝ).prod volume).restrict (goodPair s.1) ≤ oddTwoStep s := by rw [oddTwoStep_eq_withDensity, ← withDensity_const, ← withDensity_indicator (goodPair_measurable s.1)] apply withDensity_mono apply Eventually.of_forall intro x by_cases hx : x ∈ goodPair s.1 · rw [indicator_of_mem hx] change ENNReal.ofReal (goodPairDensityLower M) ≤ ENNReal.ofReal (transitionDensity .odd s.1 x.1) * ENNReal.ofReal (transitionDensity .even x.1 x.2) rw [← ENNReal.ofReal_mul (transitionDensity_nonneg (i := .odd) s.2 x.1)] exact ENNReal.ofReal_le_ofReal (goodPair_density_lower hM s hs hx) · rw [indicator_of_notMem hx] exact zero_le have h := hdom (goodPair s.1) rw [Measure.smul_apply, Measure.restrict_apply (goodPair_measurable s.1), inter_self, goodPair_volume, smul_eq_mul, ← ENNReal.ofReal_mul (goodPairDensityLower_pos hM).le] at h convert! h using 1 congr 1 ring noncomputable def goodPairProbability (M : ℝ) : ℝ := min (1 / 2) (goodPairDensityLower M / 16) theorem goodPairProbability_pos {M : ℝ} (hM : 4 ≤ M) : 0 < goodPairProbability M := lt_min (by norm_num) (div_pos (goodPairDensityLower_pos hM) (by norm_num)) theorem goodPairProbability_le_one (M : ℝ) : goodPairProbability M ≤ 1 := le_trans (min_le_left _ _) (by norm_num) theorem odd_terminal_progress {M : ℝ} (hM : 4 ≤ M) (s : OddState) (hs : s.1 ≤ M) : ENNReal.ofReal (goodPairProbability M) ≤ oddTwoStep s {x : ℝ × ℝ | x.2 ≤ max (3 / 2) (s.1 - 3 / 2)} := by calc _ ≤ ENNReal.ofReal (goodPairDensityLower M / 16) := ENNReal.ofReal_le_ofReal (min_le_right _ _) _ ≤ oddTwoStep s (goodPair s.1) := goodPair_measure_lower hM s hs _ ≤ _ := measure_mono (fun x hx => goodPair_terminal hx) end NumberTheoryLean.GoodPairTransitions end section namespace NumberTheoryLean.FirstHitKernels open Filter Set MeasureTheory ProbabilityTheory open scoped ProbabilityTheory ENNReal Topology open FinitePathMeasures def regenerationStateSet : Set State := fun z => Sum.elim (fun _ : TransitionKernels.EvenState => False) (fun s : TransitionKernels.OddState => s.1 ≤ 3) z theorem regenerationStateSet_measurable : MeasurableSet regenerationStateSet := by apply measurableSet_sum_iff.mpr constructor · exact MeasurableSet.empty · exact measurableSet_le measurable_subtype_coe measurable_const def regenerationSet : Set CostState := Prod.fst ⁻¹' regenerationStateSet theorem regenerationSet_measurable : MeasurableSet regenerationSet := regenerationStateSet_measurable.preimage measurable_fst @[simp] theorem regeneration_even (s : TransitionKernels.EvenState) (T : ℝ) : (.inl s, T) ∉ regenerationSet := by change ¬False; exact not_false @[simp] theorem regeneration_odd (s : TransitionKernels.OddState) (T : ℝ) : (.inr s, T) ∈ regenerationSet ↔ s.1 ≤ 3 := Iff.rfl noncomputable def killed : Kernel CostState CostState := costKernel.restrict regenerationSet_measurable.compl noncomputable def captured : Kernel CostState CostState := costKernel.restrict regenerationSet_measurable instance killed_isFiniteKernel : IsFiniteKernel killed := by unfold killed; infer_instance instance captured_isFiniteKernel : IsFiniteKernel captured := by unfold captured; infer_instance instance killed_pow_isFiniteKernel (n : ℕ) : IsFiniteKernel (killed ^ n) := by induction n with | zero => change IsFiniteKernel (Kernel.id : Kernel CostState CostState); infer_instance | succ n ih => rw [pow_succ'] change IsFiniteKernel (killed ∘ₖ (killed ^ n)) infer_instance theorem captured_add_killed : captured + killed = costKernel := by ext z : 1 change (costKernel z).restrict regenerationSet + (costKernel z).restrict regenerationSetᶜ = costKernel z exact Measure.restrict_add_restrict_compl regenerationSet_measurable noncomputable def firstHit (n : ℕ) : Kernel CostState CostState := captured ∘ₖ (killed ^ n) instance firstHit_isFiniteKernel (n : ℕ) : IsFiniteKernel (firstHit n) := by unfold firstHit infer_instance noncomputable def firstHitLaw : Kernel CostState CostState := Kernel.sum firstHit instance firstHitLaw_isSFiniteKernel : IsSFiniteKernel firstHitLaw := by unfold firstHitLaw infer_instance theorem firstHit_mass_step (n : ℕ) (z : CostState) : firstHit n z univ + (killed ^ (n + 1)) z univ = (killed ^ n) z univ := by have hp : killed ^ (n + 1) = killed ∘ₖ (killed ^ n) := pow_succ' killed n calc _ = ((captured + killed) ∘ₖ (killed ^ n)) z univ := by rw [Kernel.comp_add_left, add_apply, Measure.add_apply, hp] rfl _ = (costKernel ∘ₖ (killed ^ n)) z univ := by rw [captured_add_killed] _ = _ := by rw [Kernel.comp_apply' _ _ _ MeasurableSet.univ]; simp theorem firstHit_finite_mass (n : ℕ) (z : CostState) : (killed ^ n) z univ + ∑ k ∈ Finset.range n, firstHit k z univ = 1 := by induction n with | zero => simp only [Finset.range_zero, Finset.sum_empty, add_zero, pow_zero] change (Measure.dirac z) univ = 1 simp | succ n ih => rw [Finset.sum_range_succ] calc _ = (∑ k ∈ Finset.range n, firstHit k z univ) + (firstHit n z univ + (killed ^ (n + 1)) z univ) := by ac_rfl _ = (∑ k ∈ Finset.range n, firstHit k z univ) + (killed ^ n) z univ := by rw [firstHit_mass_step] _ = 1 := by simpa only [add_comm] using ih theorem survival_mass_le_one (n : ℕ) (z : CostState) : (killed ^ n) z univ ≤ 1 := by calc _ ≤ (killed ^ n) z univ + ∑ k ∈ Finset.range n, firstHit k z univ := le_add_of_nonneg_right zero_le _ = 1 := firstHit_finite_mass n z theorem firstHit_partial_mass_le_one (n : ℕ) (z : CostState) : (∑ k ∈ Finset.range n, firstHit k z univ) ≤ 1 := by calc _ ≤ (killed ^ n) z univ + ∑ k ∈ Finset.range n, firstHit k z univ := le_add_of_nonneg_left zero_le _ = 1 := firstHit_finite_mass n z theorem survival_mass_antitone (z : CostState) : Antitone (fun n => (killed ^ n) z univ) := by apply antitone_nat_of_succ_le intro n calc _ ≤ firstHit n z univ + (killed ^ (n + 1)) z univ := le_add_of_nonneg_left zero_le _ = _ := firstHit_mass_step n z theorem firstHitLaw_mass_le_one (z : CostState) : firstHitLaw z univ ≤ 1 := by rw [firstHitLaw, Kernel.sum_apply' _ _ MeasurableSet.univ, ENNReal.tsum_eq_iSup_nat] exact iSup_le (fun n => firstHit_partial_mass_le_one n z) instance firstHitLaw_isFiniteKernel : IsFiniteKernel firstHitLaw := ⟨1, by norm_num, fun z => firstHitLaw_mass_le_one z⟩ theorem firstHitLaw_probability_of_survival_vanishes (z : CostState) (hz : Tendsto (fun n => (killed ^ n) z univ) atTop (𝓝 0)) : IsProbabilityMeasure (firstHitLaw z) := by constructor rw [firstHitLaw, Kernel.sum_apply' _ _ MeasurableSet.univ] have hs := hz.add (ENNReal.tendsto_nat_tsum (fun n => firstHit n z univ)) simp only [zero_add, firstHit_finite_mass] at hs exact tendsto_nhds_unique hs tendsto_const_nhds theorem captured_off_regeneration (z : CostState) : captured z regenerationSetᶜ = 0 := by rw [captured, Kernel.restrict_apply' _ _ _ regenerationSet_measurable.compl, compl_inter_self, measure_empty] theorem firstHit_off_regeneration (n : ℕ) (z : CostState) : firstHit n z regenerationSetᶜ = 0 := by rw [firstHit, Kernel.comp_apply' _ _ _ regenerationSet_measurable.compl] simp only [captured_off_regeneration, lintegral_zero] theorem firstHitLaw_off_regeneration (z : CostState) : firstHitLaw z regenerationSetᶜ = 0 := by rw [firstHitLaw, Kernel.sum_apply' _ _ regenerationSet_measurable.compl] simp only [firstHit_off_regeneration, tsum_zero] theorem costKernel_increases_cost (z : CostState) : costKernel z {y : CostState | y.2 ≤ z.2} = 0 := by rw [costKernel_apply z (measurableSet_le measurable_snd measurable_const)] have he : {s : State | ((s, z.2 + FinitePathGeometry.cost (stateRatio s)) : CostState).2 ≤ z.2} = ∅ := by apply Set.eq_empty_iff_forall_notMem.mpr intro s hs have hp := FinitePathGeometry.cost_pos (FinitePathGeometry.valid_pos (stateRatio_valid s)) change z.2 + FinitePathGeometry.cost (stateRatio s) ≤ z.2 at hs linarith change (stateKernel z.1) {s : State | z.2 + FinitePathGeometry.cost (stateRatio s) ≤ z.2} = 0 rw [he, measure_empty] end NumberTheoryLean.FirstHitKernels end end Erdos970 end OAI