import OAI.Dynamics.StandardMap.EntropyEndpoint import OAI.Dynamics.StandardMap.Coding.FullEntropyCopySequence import OAI.Dynamics.StandardMap.Coupling.RelativeFiniteRealization namespace OAI section namespace HyperbolicCoding open MeasureTheory Set StandardMapEntropy.Entropy open scoped BigOperators ENNReal variable {A B : Type*} [MeasurableSpace A] [MeasurableSpace B] [Fintype B] [MeasurableSingletonClass B] [Nonempty B] def centeredWindow (N : ℕ) (w : ℤ → A) : Fin (2*N+1) → A := fun i => w ((i.val : ℤ)-N) lemma measurable_centeredWindow [Fintype A] [MeasurableSingletonClass A] (N : ℕ) : Measurable (centeredWindow (A:=A) N) := Measurable.of_eval (fun _ => measurable_pi_apply _) lemma centeredWindow_comap_monotone [Fintype A] [MeasurableSingletonClass A] : Monotone (fun N => MeasurableSpace.comap (centeredWindow (A:=A) N) inferInstance) := by intro N M hNM let r : (Fin (2*M+1) → A) → (Fin (2*N+1) → A) := fun v i => v ⟨i.val+(M-N),by omega⟩ have hm : Measurable[MeasurableSpace.comap (centeredWindow (A:=A) M) inferInstance] (centeredWindow (A:=A) M) := measurable_iff_comap_le.mpr le_rfl have hh := (measurable_of_countable r).comp hm have heq : r ∘ centeredWindow (A:=A) M=centeredWindow N := by funext w i dsimp [r,centeredWindow] congr 1 omega rw [heq] at hh exact measurable_iff_comap_le.mp hh lemma centeredWindow_generates [Fintype A] [MeasurableSingletonClass A] : (inferInstance : MeasurableSpace (ℤ → A))= ⨆ N,MeasurableSpace.comap (centeredWindow (A:=A) N) inferInstance := by let m := ⨆ N,MeasurableSpace.comap (centeredWindow (A:=A) N) inferInstance apply le_antisymm · have hi (i : ℤ) : @Measurable (ℤ → A) A m inferInstance (fun w => w i) := by let N := i.natAbs let j : Fin (2*N+1) := ⟨(i+N).toNat,by have h₁ := (Int.le_natAbs (a:=i)) have h₂ : -i≤(i.natAbs : ℤ) := by simpa using (Int.le_natAbs (a:=-i)) dsimp [N] omega⟩ have hN : @Measurable (ℤ → A) (Fin (2*N+1) → A) m inferInstance (centeredWindow N) := measurable_iff_comap_le.mpr (le_iSup (fun n => MeasurableSpace.comap (centeredWindow (A:=A) n) inferInstance) N) have hh := (measurable_pi_apply j).comp hN have heq : (fun w => centeredWindow (A:=A) N w j)=(fun w => w i) := by funext w dsimp [centeredWindow,j,N] congr 1 have h₂ : -i≤(i.natAbs : ℤ) := by simpa using (Int.le_natAbs (a:=-i)) omega exact heq ▸ hh have hid : @Measurable (ℤ → A) (ℤ → A) m MeasurableSpace.pi id := Measurable.of_eval hi simpa only [MeasurableSpace.comap_id] using measurable_iff_comap_le.mp hid · apply iSup_le intro N exact measurable_iff_comap_le.mp (measurable_centeredWindow N) lemma centeredWindow_as_word [Fintype A] [MeasurableSingletonClass A] (N : ℕ) (w : ℤ → A) : centeredWindow N w=word iidShift (fun z : ℤ → A => z 0) (2*N+1) (integerIterate iidShift (-(N : ℤ)) w) := by funext i simp only [iid_word_eq,integerIterate_neg_nat,iidShift_symm_iterate,centeredWindow] theorem iid_finite_window_approx [Fintype A] [MeasurableSingletonClass A] (ν : Measure (ℤ → A)) [IsProbabilityMeasure ν] (b : (ℤ → A) → B) (hb : Measurable b) {ε : ℝ} (hε : 0<ε) : ∃ N : ℕ,∃ D : (Fin (2*N+1) → A) → B, ν.real {w | D (centeredWindow N w)≠b w}<ε := finite_factor_approx ν (fun N => Fin (2*N+1) → A) centeredWindow centeredWindow_comap_monotone centeredWindow_generates b hb hε end HyperbolicCoding end section namespace HyperbolicCoding open MeasureTheory Set StandardMapEntropy.Entropy open scoped BigOperators variable {X Y A : Type*} [MeasurableSpace X] [MeasurableSpace Y] [MeasurableSpace A] [MeasurableSingletonClass A] lemma mass_comp_factor [StandardBorelSpace X] [StandardBorelSpace Y] [Fintype A] (μ : Measure X) (ν : Measure Y) (π : X → Y) (hπ : MeasurePreserving π μ ν) (p : Y → A) (hp : Measurable p) : mass μ (p ∘ π)=mass ν p := by funext a unfold mass exact congrArg ENNReal.toReal (hπ.measure_preimage (hp (measurableSet_singleton a)).nullMeasurableSet) lemma rate_of_factor [StandardBorelSpace X] [StandardBorelSpace Y] [Fintype A] (μ : Measure X) [IsProbabilityMeasure μ] (ν : Measure Y) [IsProbabilityMeasure ν] (e : X → X) (f : Y → Y) (hf : Measurable f) (π : X → Y) (hπ : MeasurePreserving π μ ν) (hcomm : ∀ x,π (e x)=f (π x)) (p : Y → A) (hp : Measurable p) : rate μ e (p ∘ π)=rate ν f p := by have hh (n : ℕ) : obs μ (word e (p ∘ π) n)=obs ν (word f p n) := by rw [factor_word e f π hcomm p n] unfold obs rw [mass_comp_factor μ ν π hπ _ (word_measurable f hf p hp n)] unfold rate simp only [hh] end HyperbolicCoding end section namespace HyperbolicCoding open MeasureTheory Set StandardMapEntropy.Entropy open scoped BigOperators ENNReal variable {X A B : Type*} [MeasurableSpace X] [StandardBorelSpace X] [MeasurableSpace A] [Fintype A] [DecidableEq A] [MeasurableSingletonClass A] [Nonempty A] [TopologicalSpace A] [DiscreteTopology A] [BorelSpace A] [MeasurableSpace B] [Fintype B] [MeasurableSingletonClass B] [Nonempty B] theorem relative_iid_window_graph [TopologicalSpace X] [SecondCountableTopology X] [OpensMeasurableSpace X] (μ : Measure X) [IsProbabilityMeasure μ] (e : X ≃ᵐ X) (he : Ergodic e μ) (p : X → A) (_hp : Measurable p) (β : A → ℝ) (hβ : ∀ a,0≤β a) (hβsum : ∑ a,β a=1) (hβentropy : 0 finiteWeightLaw β))) (α : X → B) (hα : Measurable α) (m : ℕ) {ε : ℝ} (hε : 0<ε) : ∃ R : ℕ,∃ D : (Fin (2*R+1) → A) → B, LawClose (μ.map (word e (fun x => (p x,α x)) m)) ((Measure.infinitePi (fun _ : ℤ => finiteWeightLaw β)).map (word iidShift (fun y : ℤ → A => (y 0,D (centeredWindow R y))) m)) ε ∧ rate (Measure.infinitePi (fun _ : ℤ => finiteWeightLaw β)) iidShift (fun y : ℤ → A => (y 0,D (centeredWindow R y)))=weightEntropy β := by classical let : IsProbabilityMeasure (finiteWeightLaw β) := finiteWeightLaw_probability β hβ hβsum let ν := Measure.infinitePi (fun _ : ℤ => finiteWeightLaw β) let : NullSingletonClass ν := iid_nullSingleton β hβ hβsum hβentropy have hcomm : ∀ x,orbitName e p (e x)=iidShift (orbitName e p x) := fun x => orbitName_shift e p x have hf : Ergodic iidShift ν := hcode.ergodic_of_ergodic_semiconj he iidShift.measurable hcomm have hp0 : (fun x => orbitName e p x 0)=p := by funext x; simp [orbitName,integerIterate] obtain ⟨b,hb,hbLaw⟩ := relative_measurable_graph_approx μ ν e he.toMeasurePreserving iidShift hf (orbitName e p) hcode hcomm (fun w : ℤ → A => w 0) α (measurable_pi_apply 0) hα m (half_pos hε) obtain ⟨R,D,hD⟩ := iid_finite_window_approx ν b hb (show 0<ε/(2*((m : ℝ)+1)) by positivity) have hDmeas : Measurable (fun y : ℤ → A => D (centeredWindow R y)) := (measurable_of_countable D).comp (measurable_centeredWindow R) have hpaint : ν.real {y | (y 0,b y)≠(y 0,D (centeredWindow R y))}<ε/(2*((m : ℝ)+1)) := by convert hD using 1 congr 1 ext y simp only [Set.mem_ofPred_eq,ne_eq,Prod.mk.injEq,true_and] exact ne_comm have hLaw := word_lawClose_of_repaint ν iidShift hf.toMeasurePreserving (fun y : ℤ → A => (y 0,b y)) (fun y : ℤ → A => (y 0,D (centeredWindow R y))) ((measurable_pi_apply 0).prodMk hb) ((measurable_pi_apply 0).prodMk hDmeas) m refine ⟨R,D,?_,?_⟩ · have htrans := hbLaw.triangle hLaw change LawClose (μ.map (word e (fun x => (p x,α x)) m)) _ _ at htrans apply htrans.mono have hm0 : (0 : ℝ)≤ m := Nat.cast_nonneg m have hh := (lt_div_iff₀ (by positivity : (0 : ℝ)<2*((m : ℝ)+1))).mp hpaint have hn0 := measureReal_nonneg (μ:=ν) (s:={y | (y 0,b y)≠(y 0,D (centeredWindow R y))}) nlinarith · have hfac := rate_of_factor μ ν e iidShift iidShift.measurable (orbitName e p) hcode hcomm (fun y : ℤ → A => (y 0,D (centeredWindow R y))) ((measurable_pi_apply 0).prodMk hDmeas) have hu := H.upper ((fun y : ℤ → A => (y 0,D (centeredWindow R y))) ∘ orbitName e p) (((measurable_pi_apply 0).prodMk hDmeas).comp hcode.measurable) rw [hfac] at hu apply le_antisymm hu have hl := rate_pair_ge_left ν iidShift hf.toMeasurePreserving (fun y : ℤ → A => y 0) (fun y => D (centeredWindow R y)) (measurable_pi_apply 0) hDmeas rwa [iid_rate β hβ hβsum] at hl end HyperbolicCoding end section namespace HyperbolicCoding open MeasureTheory Set StandardMapEntropy.Entropy open scoped ENNReal BigOperators variable {X A B : Type*} [MeasurableSpace X] [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] [MeasurableSpace B] [Fintype B] [MeasurableSingletonClass B] theorem coupling_step_finite (μ : Measure X) [IsProbabilityMeasure μ] (p : X → A) (q : X → B) (hp : Measurable p) (hq : Measurable q) (t : A → ℝ) (r : MatrixCoupling (mass μ p) t) (d : A → A → ℝ) (hdiag : ∀ a,d a a=0) (htri : ∀ a b c,d a c≤d a b+d b c) {ε : ℝ} (hclose : LawClose (μ.map (fun x => (p x,q x))) ((μ.map p).prod (μ.map q)) ε) : ∃ s : MatrixCoupling (mass μ (fun x => (q x,p x))) (fun ba : B×A => mass μ q ba.1*t ba.2), s.cost (fun ba bb => symbolCost ba.1 bb.1+d ba.2 bb.2)≤ε+r.cost d := by classical let u : A → B → ℝ := fun a b => mass μ (fun x => (p x,q x)) (a,b) let v : A → B → ℝ := fun a b => mass μ p a*mass μ q b have hrow (a) : ∑ b,u a b=∑ b,v a b := by rw [←mass_joint_row μ p q hp hq] dsimp only [v] rw [←Finset.mul_sum,mass_sum μ q hq] simp have hc (a) := finite_maximal_coupling_equal_mass (u a) (v a) (fun b => mass_nonneg μ _ _) (fun b => mul_nonneg (mass_nonneg μ _ _) (mass_nonneg μ _ _)) (hrow a) choose w hw hwrow hwcol hwerr using hc let R : MatrixCoupling (mass μ (fun x => (q x,p x))) (fun ba : B×A => mass μ q ba.1*mass μ p ba.2) := { weight := fun ba ca => if ba.2=ca.2 then w ba.2 ba.1 ca.1 else 0 nonneg := fun ba ca => by split · exact hw _ _ _ · exact le_rfl row := fun ba => by simp only [Fintype.sum_prod_type] simp only [Finset.sum_ite_eq,Finset.mem_univ,ite_true] rw [hwrow] exact mass_joint_swap μ p q ba.2 ba.1 col := fun ca => by simp only [Fintype.sum_prod_type] simp only [Finset.sum_ite_eq',Finset.mem_univ,ite_true] rw [hwcol] exact mul_comm _ _ } let S := (MatrixCoupling.diagonal (mass μ q) (mass_nonneg μ q)).product r let cost : (B×A) → (B×A) → ℝ := fun ba bb => symbolCost ba.1 bb.1+d ba.2 bb.2 have hR : R.cost cost≤ε := by have he : R.cost cost=∑ a,∑ b,∑ c,w a b c*symbolCost b c := by simp only [MatrixCoupling.cost,R,cost,Fintype.sum_prod_type] have hh (b : B) (a : A) (c : B) : (∑ a', (if a=a' then w a b c else 0)*(symbolCost b c+d a a'))= w a b c*symbolCost b c := by simp [ite_mul,hdiag] simp only [hh] rw [Finset.sum_comm] rw [he] have : IsProbabilityMeasure (μ.map p) := inferInstance have : IsProbabilityMeasure (μ.map q) := inferInstance have : IsProbabilityMeasure (μ.map (fun x => (p x,q x))) := inferInstance have hprod (a : A) (b : B) : ((μ.map p).prod (μ.map q)).real {(a,b)}=v a b := by rw [←singleton_prod_singleton,Measure.real,Measure.prod_prod,ENNReal.toReal_mul] rw [←Measure.real,←Measure.real,map_measureReal_apply hp (measurableSet_singleton a), map_measureReal_apply hq (measurableSet_singleton b)] rfl have hsum : (∑ a,∑ b,max (u a b-v a b) 0)≤ε := by have h := positive_mass_difference_le _ _ hclose rw [Fintype.sum_prod_type] at h have hu (a : A) (b : B) : (μ.map (fun x => (p x,q x))).real {(a,b)}=u a b := map_measureReal_apply (hp.prodMk hq) (measurableSet_singleton (a,b)) simpa only [hu,hprod] using h apply le_trans _ hsum apply Finset.sum_le_sum intro a _ simpa only [symbolCost] using (hwerr a).le have hS : S.cost cost=r.cost d := by rw [MatrixCoupling.product_cost] · rw [MatrixCoupling.diagonal_cost _ _ symbolCost symbolCost_self,zero_add] · simpa using mass_sum μ q hq · simpa using mass_sum μ p hp refine ⟨R.comp S,?_⟩ have h := MatrixCoupling.comp_cost_le R S cost cost cost (fun a b c => by dsimp [cost] have h1 := symbolCost_triangle a.1 b.1 c.1 have h2 := htri a.2 b.2 c.2 linarith) exact h.trans (by rw [hS]; linarith) end HyperbolicCoding end section namespace HyperbolicCoding open MeasureTheory Set StandardMapEntropy.Entropy open scoped ENNReal BigOperators variable {X A B : Type*} [MeasurableSpace X] [MeasurableSpace B] [Fintype B] [MeasurableSingletonClass B] lemma cond_constant [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] (μ : Measure X) [IsProbabilityMeasure μ] (p : X → A) (_hp : Measurable p) : StandardMapEntropy.Entropy.cond μ p (fun _ => (PUnit.unit : PUnit.{1}))=obs μ p := by unfold StandardMapEntropy.Entropy.cond have he : obs μ (fun x => (p x,(PUnit.unit : PUnit.{1})))=obs μ p := by let e : A ≃ A×PUnit.{1} := (Equiv.prodPUnit A).symm exact obs_equiv μ p e rw [he,obs_const,sub_zero] lemma lawClose_of_mutual_information [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] (μ : Measure X) [IsProbabilityMeasure μ] (p : X → A) (q : X → B) (hp : Measurable p) (hq : Measurable q) {δ : ℝ} (hδ : 0 ≤ δ) (hdef : 4*(obs μ q-StandardMapEntropy.Entropy.cond μ q p) ≤ δ^2) : LawClose (μ.map (fun x => (p x,q x))) ((μ.map p).prod (μ.map q)) δ := by have hconst : LawClose (μ.map (fun x => ((PUnit.unit : PUnit.{1}),q x))) ((μ.map (fun _ : X => (PUnit.unit : PUnit.{1}))).prod (μ.map q)) 0 := by have heq := (ProbabilityTheory.indepFun_const_left (μ:=μ) (PUnit.unit : PUnit.{1}) q).map_prod_eq_prod_map_map measurable_const.aemeasurable hq.aemeasurable rw [heq] intro D _ simp only [sub_self,abs_zero] exact le_rfl have hd : 4*(StandardMapEntropy.Entropy.cond μ q ((fun _ : A => (PUnit.unit : PUnit.{1})) ∘ p)-StandardMapEntropy.Entropy.cond μ q p) ≤ δ^2 := by simpa only [Function.comp_def,cond_constant μ q hq] using hdef have hh := lawClose_of_coarse_independence μ p q (fun _ : A => (PUnit.unit : PUnit.{1})) hp hq hδ hconst hd simpa only [mul_zero,add_zero] using hh lemma lawClose_entropy_budget [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] (μ : Measure X) [IsProbabilityMeasure μ] (p : X → A) (q : X → B) (hp : Measurable p) (hq : Measurable q) {τ : ℝ} (hτ : 0 < τ) : LawClose (μ.map (fun x => (p x,q x))) ((μ.map p).prod (μ.map q)) ((obs μ q-StandardMapEntropy.Entropy.cond μ q p)/τ+τ) := by have hI : 0 ≤ obs μ q-StandardMapEntropy.Entropy.cond μ q p := sub_nonneg.mpr (cond_le_obs μ q p hq hp) apply lawClose_of_mutual_information μ p q hp hq (by positivity) have he : ((obs μ q-StandardMapEntropy.Entropy.cond μ q p)/τ)*τ=obs μ q-StandardMapEntropy.Entropy.cond μ q p := div_mul_cancel₀ _ hτ.ne' nlinarith [sq_nonneg ((obs μ q-StandardMapEntropy.Entropy.cond μ q p)/τ-τ)] variable (μ : Measure X) noncomputable def sequenceEntropyDefect [Fintype A] (q : ℕ → X → A) (i n : ℕ) : ℝ := (∑ j : Fin n,obs μ (q (i+j.val)))-obs μ (finiteName q i n) lemma obs_finiteName_zero [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] [StandardBorelSpace X] [Nonempty A] [IsProbabilityMeasure μ] (q : ℕ → X → A) (i : ℕ) : obs μ (finiteName q i 0)=0 := by have heq : finiteName q i 0=(fun _ => (fun j : Fin 0 => j.elim0 : Fin 0 → A)) := by funext x j exact j.elim0 rw [heq,obs_const] lemma sequenceEntropyDefect_cons [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] [StandardBorelSpace X] [Nonempty A] [IsProbabilityMeasure μ] (q : ℕ → X → A) (i n : ℕ) : sequenceEntropyDefect μ q i (n+1)= (obs μ (q i)-StandardMapEntropy.Entropy.cond μ (q i) (finiteName q (i+1) n))+sequenceEntropyDefect μ q (i+1) n := by let e : (A×(Fin n → A)) ≃ (Fin (n+1) → A) := Fin.consEquiv (fun _ => A) have heq : finiteName q i (n+1)=e ∘ (fun x => (q i x,finiteName q (i+1) n x)) := funext (finiteName_cons q i n) have hobs : obs μ (finiteName q i (n+1))=obs μ (fun x => (q i x,finiteName q (i+1) n x)) := by rw [heq,obs_equiv] simp only [sequenceEntropyDefect,Fin.sum_univ_succ,Fin.val_zero,Nat.add_zero,Fin.val_succ,hobs,StandardMapEntropy.Entropy.cond] have hs : (∑ j : Fin n,obs μ (q (i+(j.val+1))))= ∑ j : Fin n,obs μ (q ((i+1)+j.val)) := by apply Finset.sum_congr rfl intro j _ congr 2 omega rw [hs] ring lemma independentNameWeights_cons_finite [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] [StandardBorelSpace X] [Nonempty A] [IsProbabilityMeasure μ] (q : ℕ → X → A) (i n : ℕ) (w : Fin (n+1) → A) : independentNameWeights μ q i (n+1) w= mass μ (q i) (w 0)*independentNameWeights μ q (i+1) n (Fin.tail w) := by rw [independentNameWeights,Fin.prod_univ_succ] simp only [Fin.val_zero,Nat.add_zero,Fin.val_succ,Fin.tail,independentNameWeights] congr 2 funext j congr 2 omega lemma mass_equiv_inverse_finite [StandardBorelSpace X] [IsProbabilityMeasure μ] {C D : Type*} [MeasurableSpace C] [Fintype C] [MeasurableSingletonClass C] [MeasurableSpace D] [Fintype D] [MeasurableSingletonClass D] (p : X → C) (e : C ≃ D) (d : D) : mass μ (e ∘ p) d=mass μ p (e.symm d) := by unfold mass congr 2 ext x simp only [mem_preimage,mem_singleton_iff,Function.comp_apply,← Equiv.eq_symm_apply] theorem entropy_product_transport [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] [StandardBorelSpace X] [Nonempty A] [IsProbabilityMeasure μ] (q : ℕ → X → A) (hq : ∀ i,Measurable (q i)) {τ : ℝ} (hτ : 0 < τ) : ∀ i n : ℕ,∃ R : MatrixCoupling (mass μ (finiteName q i n)) (independentNameWeights μ q i n), R.cost nameCost ≤ sequenceEntropyDefect μ q i n/τ+(n : ℝ)*τ := by intro i n induction n generalizing i with | zero => have hm (w : Fin 0 → A) : mass μ (finiteName q i 0) w=1 := by have he : (finiteName q i 0) ⁻¹' {w}=univ := by ext x simp only [mem_preimage,mem_singleton_iff,mem_univ,iff_true] funext j exact j.elim0 simp [mass,he] let R : MatrixCoupling (mass μ (finiteName q i 0)) (independentNameWeights μ q i 0) := { weight := fun _ _ => 1 nonneg := fun _ _ => zero_le_one row := fun w => by simp [hm] col := fun w => by simp [independentNameWeights] } refine ⟨R,?_⟩ simp [MatrixCoupling.cost,nameCost,sequenceEntropyDefect,obs_finiteName_zero] | succ n ih => obtain ⟨r,hr⟩ := ih (i+1) have hc := lawClose_entropy_budget μ (finiteName q (i+1) n) (q i) (finiteName_measurable q hq (i+1) n) (hq i) hτ obtain ⟨s,hs⟩ := coupling_step_finite μ (finiteName q (i+1) n) (q i) (finiteName_measurable q hq (i+1) n) (hq i) (independentNameWeights μ q (i+1) n) r nameCost nameCost_self nameCost_triangle hc let e : (A×(Fin n → A)) ≃ (Fin (n+1) → A) := Fin.consEquiv (fun _ => A) let t := s.reindex e.symm e.symm have hm (w : Fin (n+1) → A) : mass μ (fun x => (q i x,finiteName q (i+1) n x)) (e.symm w)=mass μ (finiteName q i (n+1)) w := by rw [←mass_equiv_inverse_finite μ _ e w] congr 1 funext x exact (finiteName_cons q i n x).symm have hw (w : Fin (n+1) → A) : mass μ (q i) (e.symm w).1*independentNameWeights μ q (i+1) n (e.symm w).2= independentNameWeights μ q i (n+1) w := (independentNameWeights_cons_finite μ q i n w).symm let R : MatrixCoupling (mass μ (finiteName q i (n+1))) (independentNameWeights μ q i (n+1)) := { weight := t.weight nonneg := t.nonneg row := fun w => (t.row w).trans (hm w) col := fun w => (t.col w).trans (hw w) } have hcost : R.cost nameCost=s.cost (fun a b => symbolCost a.1 b.1+nameCost a.2 b.2) := by change t.cost nameCost=_ have he : (nameCost : (Fin (n+1) → A) → (Fin (n+1) → A) → ℝ)= (fun v w => symbolCost (e.symm v).1 (e.symm w).1+nameCost (e.symm v).2 (e.symm w).2) := by funext v w exact nameCost_split v w rw [he] exact MatrixCoupling.reindex_cost s e.symm e.symm (fun a b : A×(Fin n → A) => symbolCost a.1 b.1+nameCost a.2 b.2) refine ⟨R,?_⟩ rw [hcost,sequenceEntropyDefect_cons] have hh := hs.trans (add_le_add (le_refl _) hr) convert hh using 1; first | rfl | (push_cast; ring) end HyperbolicCoding end section namespace HyperbolicCoding open MeasureTheory Set StandardMapEntropy.Entropy open scoped ENNReal BigOperators variable {X A : Type*} [MeasurableSpace X] [StandardBorelSpace X] [MeasurableSpace A] [Fintype A] [MeasurableSingletonClass A] [Nonempty A] variable (μ : Measure X) [IsProbabilityMeasure μ] theorem sequential_coupling_budgets (q : ℕ → X → A) (hq : ∀ i,Measurable (q i)) (N : ℕ) (b : ℕ → ℝ) (hremote : ∀ i n : ℕ,i+n+1≤N → LawClose (μ.map (fun x => (finiteName q (i+1) n x,q i x))) ((μ.map (finiteName q (i+1) n)).prod (μ.map (q i))) (b i)) : ∀ i n : ℕ,i+n≤N → ∃ R : MatrixCoupling (mass μ (finiteName q i n)) (independentNameWeights μ q i n), R.cost nameCost≤∑ j : Fin n,b (i+j.val) := by intro i n hi induction n generalizing i with | zero => have hm (w : Fin 0 → A) : mass μ (finiteName q i 0) w=1 := by have he : (finiteName q i 0) ⁻¹' {w}=univ := by ext x simp only [mem_preimage,mem_singleton_iff,mem_univ,iff_true] funext j exact j.elim0 simp [mass,he] let R : MatrixCoupling (mass μ (finiteName q i 0)) (independentNameWeights μ q i 0) := { weight := fun _ _ => 1 nonneg := fun _ _ => zero_le_one row := fun w => by simp [hm] col := fun w => by simp [independentNameWeights] } refine ⟨R,?_⟩ simp [MatrixCoupling.cost,nameCost] | succ n ih => obtain ⟨r,hr⟩ := ih (i+1) (by omega) have hc := hremote i n hi obtain ⟨s,hs⟩ := coupling_step_finite μ (finiteName q (i+1) n) (q i) (finiteName_measurable q hq (i+1) n) (hq i) (independentNameWeights μ q (i+1) n) r nameCost nameCost_self nameCost_triangle hc let e : (A×(Fin n → A)) ≃ (Fin (n+1) → A) := Fin.consEquiv (fun _ => A) let t := s.reindex e.symm e.symm have hm (w : Fin (n+1) → A) : mass μ (fun x => (q i x,finiteName q (i+1) n x)) (e.symm w)=mass μ (finiteName q i (n+1)) w := by rw [←mass_equiv_inverse_finite μ _ e w] congr 1 funext x exact (finiteName_cons q i n x).symm have hw (w : Fin (n+1) → A) : mass μ (q i) (e.symm w).1*independentNameWeights μ q (i+1) n (e.symm w).2= independentNameWeights μ q i (n+1) w := (independentNameWeights_cons_finite μ q i n w).symm let R : MatrixCoupling (mass μ (finiteName q i (n+1))) (independentNameWeights μ q i (n+1)) := { weight := t.weight nonneg := t.nonneg row := fun w => (t.row w).trans (hm w) col := fun w => (t.col w).trans (hw w) } have hcost : R.cost nameCost=s.cost (fun a b => symbolCost a.1 b.1+nameCost a.2 b.2) := by change t.cost nameCost=_ have he : (nameCost : (Fin (n+1) → A) → (Fin (n+1) → A) → ℝ)= (fun v w => symbolCost (e.symm v).1 (e.symm w).1+nameCost (e.symm v).2 (e.symm w).2) := by funext v w exact nameCost_split v w rw [he] exact MatrixCoupling.reindex_cost s e.symm e.symm (fun a b : A×(Fin n → A) => symbolCost a.1 b.1+nameCost a.2 b.2) refine ⟨R,?_⟩ rw [hcost,Fin.sum_univ_succ] simp only [Fin.val_zero,Nat.add_zero,Fin.val_succ] have he : (∑ j : Fin n,b (i+(j.val+1)))=∑ j : Fin n,b (i+1+j.val) := by apply Finset.sum_congr rfl intro j _ congr 1 omega rw [he] exact hs.trans (add_le_add (le_refl _) hr) lemma finiteName_entropy_chain (q : ℕ → X → A) (i n : ℕ) : obs μ (finiteName q i n)=∑ j : Fin n,StandardMapEntropy.Entropy.cond μ (q (i+j.val)) (finiteName q (i+j.val+1) (n-j.val-1)) := by induction n generalizing i with | zero => simp [obs_finiteName_zero] | succ n ih => have he : obs μ (finiteName q i (n+1))= StandardMapEntropy.Entropy.cond μ (q i) (finiteName q (i+1) n)+obs μ (finiteName q (i+1) n) := by let e : (A×(Fin n → A)) ≃ (Fin (n+1) → A) := Fin.consEquiv (fun _ => A) have heq : finiteName q i (n+1)=e ∘ (fun x => (q i x,finiteName q (i+1) n x)) := funext (finiteName_cons q i n) rw [heq,obs_equiv] unfold StandardMapEntropy.Entropy.cond ring rw [he,ih,Fin.sum_univ_succ] simp only [Fin.val_zero,Nat.add_zero,Nat.sub_zero,Fin.val_succ] congr 1 apply Finset.sum_congr rfl intro j _ have hl : n+1-(j.val+1)-1=n-j.val-1 := by omega have hi : i+1+j.val=i+(j.val+1) := by omega simp only [hi] exact congrArg (fun m => StandardMapEntropy.Entropy.cond μ (q (i+(j.val+1))) (finiteName q (i+(j.val+1)+1) m)) hl.symm end HyperbolicCoding end end OAI