import OAI.Analysis.CharacterCriterion.MultiplicativeChannels namespace OAI noncomputable section open scoped TensorProduct open scoped InnerProductSpace open scoped BigOperators open Set Module open Topology open NormedSpace open scoped ComplexOrder open scoped ComplexOrder open scoped InnerProductSpace open scoped InnerProductSpace open NormedSpace open scoped TensorProduct InnerProductSpace open UniformSpace variable [KirchbergRordam.GenericRW.Size] local notation "rankNum" => KirchbergRordam.GenericRW.Size.n variable [KirchbergRordam.GenericRW.PauliData] omit [KirchbergRordam.GenericRW.Size] [KirchbergRordam.GenericRW.PauliData] open Filter Topology BoundedContinuousFunction open Filter Topology open Topology open scoped TensorProduct CStarAlgebra open scoped CStarAlgebra ComplexOrder open NormedSpace open scoped ComplexOrder open scoped ComplexOrder open scoped InnerProductSpace open scoped CStarAlgebra ComplexOrder open scoped TensorProduct InnerProductSpace open UniformSpace namespace KirchbergRordam.BalancedDropChannels open MatrixDiagonalPath DiagonalIteration BalancedDropIteration open BalancedDropMultiplicity BalancedDropSystem DropChannels open MultiplicativeChannel (Channel) open scoped CStarAlgebra ComplexOrder open Filter Topology def finalPath (n k : ℕ) := normalizedPath n (k+1) def endPath (n k : ℕ) (t : unitInterval) := finalPath n k t*star (finalPath n k 1) lemma endPath_continuous (n k : ℕ) : Continuous (endPath n k) := (normalizedPath_continuous n (k+1)).mul continuous_const @[simp] lemma endPath_one (n k : ℕ) : endPath n k 1=1 := mul_inv_cancel _ def stageLeft (n k : ℕ) : Channel DimensionDrop23 (BalancedDropLimit.Stage (n+k+1)) := DropChannels.left (next (stage (n+k))) (next (stage (n+k))+1) (finalPath n k) (normalizedPath_continuous n (k+1)) (normalizedPath_zero n (k+1)) (zeroRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half)) def stageRight (n k : ℕ) : Channel DimensionDrop23 (BalancedDropLimit.Stage (n+k+1)) := DropChannels.right (next (stage (n+k))) (next (stage (n+k))+1) (endPath n k) (endPath_continuous n k) (endPath_one n k) (oneRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half*star (normalizedPath n k 1))) lemma stage_unit_sum (n k : ℕ) : stageLeft n k 1+stageRight n k 1=1 := DropChannels.unit_sum _ _ _ _ _ _ _ _ _ _ lemma norm_sub_two {B : Type*} [SeminormedAddCommGroup B] (a b c : B) {ε : ℝ} (ha : ‖a-c‖≤ε) (hb : ‖b-c‖≤ε) : ‖a-b‖≤2*ε := by calc _ = ‖(a-c)-(b-c)‖ := by congr 1; abel _ ≤ ‖a-c‖+‖b-c‖ := norm_sub_le _ _ _ ≤ _ := by linarith lemma map_next (n k : ℕ) (x : BalancedDropLimit.Stage n) : BalancedDropLimit.chain.map n (n+k+1) (by omega) x = step (stage (n+k)) (stage_two (n+k)) (BalancedDropLimit.chain.map n (n+k) (Nat.le_add_right n k) x) := by rw [BalancedDropLimit.chain.map_succ n (n+k) (Nat.le_add_right n k)] rfl lemma stageLeft_bound (n k : ℕ) (x : BalancedDropLimit.Stage n) {ε : ℝ} (hε : 0≤ε) (hp : ∀ t : unitInterval, ‖conj (star (normalizedPath n k t)) ((BalancedDropLimit.chain.map n (n+k) (Nat.le_add_right n k) x).val t)- (BalancedDropLimit.chain.map n (n+k) (Nat.le_add_right n k) x).val 0‖≤ε) (hf : ∀ t : unitInterval, ‖conj (star (finalPath n k t)) ((BalancedDropLimit.chain.map n (n+k+1) (by omega) x).val t)- (BalancedDropLimit.chain.map n (n+k+1) (by omega) x).val 0‖≤ε) (d : DimensionDrop23) : ‖stageLeft n k d * (show BalancedDropLimit.Stage (n+k+1) from BalancedDropLimit.chain.map n (n+k+1) (by omega) x)- (show BalancedDropLimit.Stage (n+k+1) from BalancedDropLimit.chain.map n (n+k+1) (by omega) x) * stageLeft n k d‖≤4*ε*‖d‖ := by let g : BalancedDropLimit.Stage (n+k+1) := BalancedDropLimit.chain.map n (n+k+1) (by omega) x change ‖((stageLeft n k d*g-g*stageLeft n k d).val)‖≤_ apply (ContinuousMap.norm_le _ (by positivity)).mpr intro t change ‖(leftScalar t • conj (finalPath n k t) (MatrixTensor.leftMatrix (zeroRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half) d))) * g.val t- g.val t*(leftScalar t • conj (finalPath n k t) (MatrixTensor.leftMatrix (zeroRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half) d)))‖≤_ apply (smul_commutator _ _ _ (leftScalar_norm t)).trans let ρ : DimensionDrop23 →⋆ₐ[ℂ] MatrixTensor.Mat (P (next (stage (n+k))) × Q (next (stage (n+k)))) := MatrixTensor.leftMatrix.comp (zeroRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half)) have he := zeroRep_bound (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half) (BalancedDropLimit.chain.map n (n+k) (Nat.le_add_right n k) x) d (hp half) rw [←map_next n k x] at he have ht := transport_bound ρ d (finalPath n k t) (g.val t) (g.val 0) hε (hf t) he convert ht using 1 <;> first | rfl | ring lemma stageRight_bound (n k : ℕ) (x : BalancedDropLimit.Stage n) {ε : ℝ} (hε : 0≤ε) (hp : ∀ t : unitInterval, ‖conj (star (normalizedPath n k t)) ((BalancedDropLimit.chain.map n (n+k) (Nat.le_add_right n k) x).val t)- (BalancedDropLimit.chain.map n (n+k) (Nat.le_add_right n k) x).val 0‖≤ε) (hf : ∀ t : unitInterval, ‖conj (star (finalPath n k t)) ((BalancedDropLimit.chain.map n (n+k+1) (by omega) x).val t)- (BalancedDropLimit.chain.map n (n+k+1) (by omega) x).val 0‖≤ε) (d : DimensionDrop23) : ‖stageRight n k d * (show BalancedDropLimit.Stage (n+k+1) from BalancedDropLimit.chain.map n (n+k+1) (by omega) x)- (show BalancedDropLimit.Stage (n+k+1) from BalancedDropLimit.chain.map n (n+k+1) (by omega) x) * stageRight n k d‖≤8*ε*‖d‖ := by let f : BalancedDropLimit.Stage (n+k) := BalancedDropLimit.chain.map n (n+k) (Nat.le_add_right n k) x let g : BalancedDropLimit.Stage (n+k+1) := BalancedDropLimit.chain.map n (n+k+1) (by omega) x have hm : ‖conj (star (normalizedPath n k half*star (normalizedPath n k 1))) (f.val half)-f.val 1‖≤2*ε := by rw [norm_twisted_difference] exact norm_sub_two _ _ _ (hp half) (hp 1) have he := oneRep_bound (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half*star (normalizedPath n k 1)) f d hm change _ ≤ 2*(2*ε)*‖d‖ at he rw [show 2*(2*ε)*‖d‖=(4*ε)*‖d‖ by ring] at he dsimp only [f] at he rw [←map_next n k x] at he change ‖((stageRight n k d*g-g*stageRight n k d).val)‖≤_ apply (ContinuousMap.norm_le _ (by positivity)).mpr intro t change ‖(rightScalar t • conj (endPath n k t) (MatrixTensor.rightMatrix (oneRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half*star (normalizedPath n k 1)) d))) * g.val t- g.val t*(rightScalar t • conj (endPath n k t) (MatrixTensor.rightMatrix (oneRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half*star (normalizedPath n k 1)) d)))‖≤_ apply (smul_commutator _ _ _ (rightScalar_norm t)).trans let ρ : DimensionDrop23 →⋆ₐ[ℂ] MatrixTensor.Mat (P (next (stage (n+k))) × Q (next (stage (n+k)))) := MatrixTensor.rightMatrix.comp (oneRep (stage (n+k)) (stage_two (n+k)) (normalizedPath n k half*star (normalizedPath n k 1))) have ht : ‖conj (star (endPath n k t)) (g.val t)-g.val 1‖≤2*ε := by rw [endPath,norm_twisted_difference] exact norm_sub_two _ _ _ (hf t) (hf 1) have hc := transport_bound ρ d (endPath n k t) (g.val t) (g.val 1) (by positivity : 0≤2*ε) ht he convert hc using 1 <;> first | rfl | ring end KirchbergRordam.BalancedDropChannels namespace KirchbergRordam.BalancedDropChannels open BalancedDropLimit BalancedDropIteration open MultiplicativeChannel (Channel) open scoped CStarAlgebra ComplexOrder open Filter Topology lemma finite_stage (n : ℕ) (F : Finset (Stage n)) (ε : ℝ) (hε : 0<ε) : ∃ φ ψ : Channel DimensionDrop23 Algebra, φ 1+ψ 1=1 ∧ ∀ x∈F, ∀ d : DimensionDrop23, ‖φ d*inclusion n x-inclusion n x*φ d‖≤ε*‖d‖ ∧ ‖ψ d*inclusion n x-inclusion n x*ψ d‖≤ε*‖d‖ := by have he : ∀ᶠ k in atTop, ∀ x∈F, ∀ t : unitInterval, ‖DiagonalIteration.conj (star (normalizedPath n k t)) ((chain.map n (n+k) (Nat.le_add_right n k) x).val t)- (chain.map n (n+k) (Nat.le_add_right n k) x).val 0‖≤ε/8 := by apply (Filter.eventually_all_finset F).mpr intro x hx exact eventually_untwist_small n x (ε/8) (by positivity) obtain ⟨K,hK⟩ := Filter.eventually_atTop.mp he let φ := MultiplicativeChannel.postcompose (stageLeft n K) (inclusion (n+K+1)) let ψ := MultiplicativeChannel.postcompose (stageRight n K) (inclusion (n+K+1)) refine ⟨φ,ψ,?_,fun x hx d => ?_⟩ · change BalancedDropLimit.inclusion _ (stageLeft n K 1)+BalancedDropLimit.inclusion _ (stageRight n K 1)=1 rw [←map_add,stage_unit_sum,map_one] · have hl := stageLeft_bound n K x (by positivity : 0≤ε/8) (hK K le_rfl x hx) (hK (K+1) (Nat.le_succ K) x hx) d have hr := stageRight_bound n K x (by positivity : 0≤ε/8) (hK K le_rfl x hx) (hK (K+1) (Nat.le_succ K) x hx) d have hm : inclusion (n+K+1) (chain.map n (n+K+1) (by omega) x)=inclusion n x := CStarInductiveLimit.of_map system n (n+K+1) (by omega) x have hc (r : Stage (n+K+1)) := DropChannels.commutator_map_bound (inclusion (n+K+1)) r (chain.map n (n+K+1) (by omega) x) have hcl := (hc (stageLeft n K d)).trans hl have hcr := (hc (stageRight n K d)).trans hr rw [hm] at hcl hcr change _≤_ at hcl refine ⟨hcl.trans ?_,hcr.trans ?_⟩ <;> nlinarith [norm_nonneg d] lemma channel_perturbation (φ : Channel DimensionDrop23 Algebra) (d : DimensionDrop23) (x y : Algebra) : ‖φ d*x-x*φ d‖≤‖φ d*y-y*φ d‖+2*‖x-y‖*‖d‖ := by calc _ ≤ ‖φ d*y-y*φ d‖+2*‖x-y‖*‖φ d‖ := DropChannels.norm_commutator_change (φ d) x y _ ≤ _ := add_le_add le_rfl (mul_le_mul_of_nonneg_left (φ.norm_le d) (by positivity : 0≤2*‖x-y‖)) lemma finite_control (F : Finset Algebra) (ε : ℝ) (hε : 0<ε) : ∃ φ ψ : Channel DimensionDrop23 Algebra, φ 1+ψ 1=1 ∧ ∀ x∈F, ∀ d : DimensionDrop23, ‖φ d*x-x*φ d‖≤ε*‖d‖ ∧ ‖ψ d*x-x*ψ d‖≤ε*‖d‖ := by classical obtain ⟨n,a,ha⟩ := BalancedDropHalfFlip.common_stage F (ε/4) (by positivity) obtain ⟨φ,ψ,hu,h⟩ := finite_stage n (F.image a) (ε/2) (by positivity) refine ⟨φ,ψ,hu,fun x hx d => ?_⟩ have hb := h (a x) (Finset.mem_image_of_mem a hx) d have hd := (ha x hx).le rw [norm_sub_rev] at hd constructor · have hc := channel_perturbation φ d x (inclusion n (a x)) nlinarith [mul_le_mul_of_nonneg_right hd (norm_nonneg d),hb.1] · have hc := channel_perturbation ψ d x (inclusion n (a x)) nlinarith [mul_le_mul_of_nonneg_right hd (norm_nonneg d),hb.2] end KirchbergRordam.BalancedDropChannels namespace KirchbergRordam.MultiplicativeChannel open Filter Topology TopologicalSpace open scoped CStarAlgebra ComplexOrder variable {A D : Type*} [CStarAlgebra A] [CStarAlgebra D] def sequence (φ : ℕ → Channel D A) : Channel D (NormUltrapower.BoundedSeq A) where linear := { toFun d := BoundedContinuousFunction.ofNormedAddCommGroupDiscrete (fun n => φ n d) ‖d‖ (fun n => (φ n).norm_le d) map_add' d e := by ext n; exact (φ n).linear.map_add d e map_smul' z d := by ext n; exact (φ n).linear.map_smul z d } norm_le d := (BoundedContinuousFunction.norm_le (norm_nonneg d)).mpr (fun n => (φ n).norm_le d) mul_eq d e := by ext n; exact (φ n).mul_eq d e lemma sequence_apply (φ : ℕ → Channel D A) (d : D) (n : ℕ) : sequence φ d n=φ n d := rfl def centralize (ω : Ultrafilter ℕ) (φ : Channel D (NormUltrapower.Algebra A ω)) (hφ : ∀ d, φ d∈NormUltrapower.centralSubalgebra ω) : Channel D (NormUltrapower.CentralAlgebra A ω) where linear := { toFun d := ⟨φ d,hφ d⟩ map_add' d e := Subtype.ext (φ.linear.map_add d e) map_smul' z d := Subtype.ext (φ.linear.map_smul z d) } norm_le d := φ.norm_le d mul_eq d e := Subtype.ext (φ.mul_eq d e) lemma sequence_central [TopologicalSpace.SeparableSpace A] (ω : Ultrafilter ℕ) (hω : (ω : Filter ℕ)≤cofinite) (φ : ℕ → Channel D A) (hφ : ∀ i d, Tendsto (fun n => ‖φ n d*denseSeq A i-denseSeq A i*φ n d‖) atTop (𝓝 0)) : ∀ d, postcompose (sequence φ) (NormUltrapower.quotientMap ω) d∈NormUltrapower.centralSubalgebra ω := by intro d rw [NormUltrapower.mem_central_iff] intro a let z := NormUltrapower.quotientMap ω (sequence φ d) change NormUltrapower.diagonal ω a*z=z*NormUltrapower.diagonal ω a refine (denseRange_denseSeq A).induction_on a (p := fun a => NormUltrapower.diagonal ω a*z=z*NormUltrapower.diagonal ω a) (isClosed_eq (by fun_prop) (by fun_prop)) ?_ intro i have hz := (hφ i d).mono_left (by simpa only [Nat.cofinite_eq_atTop] using hω) have he : sequence φ d*NormUltrapower.constantSeq (denseSeq A i)- NormUltrapower.constantSeq (denseSeq A i)*sequence φ d∈NormUltrapower.nullIdeal ω := (NormUltrapower.mem_nullIdeal ω _).mpr hz have heq := Ideal.Quotient.eq.mpr he exact heq.symm theorem no_central_character_of_finite_channels [TopologicalSpace.SeparableSpace A] (H : ∀ (F : Finset A) (ε : ℝ), 0<ε → ∃ φ ψ : Channel DimensionDrop23 A, φ 1+ψ 1=1 ∧ ∀ a∈F, ∀ d : DimensionDrop23, ‖φ d*a-a*φ d‖≤ε*‖d‖ ∧ ‖ψ d*a-a*ψ d‖≤ε*‖d‖) (ω : Ultrafilter ℕ) (hω : (ω : Filter ℕ)≤cofinite) : IsEmpty (NormUltrapower.CentralAlgebra A ω →⋆ₐ[ℂ] ℂ) := by classical choose φ ψ hu hc using fun n : ℕ => H ((Finset.range n).image (denseSeq A)) (1/((n:ℝ)+1)) (by positivity) have hz (r : ℕ → Channel DimensionDrop23 A) (hr : ∀ n i, i ‖r n d*denseSeq A i-denseSeq A i*r n d‖) atTop (𝓝 0) := by intro i d apply squeeze_zero' (Eventually.of_forall (fun n => norm_nonneg _)) (g := fun n : ℕ => (1/((n:ℝ)+1))*‖d‖) · filter_upwards [eventually_gt_atTop i] with n hn exact hr n i hn d · simpa only [zero_mul] using tendsto_one_div_add_atTop_nhds_zero_nat.mul_const ‖d‖ have hl := sequence_central ω hω φ (hz φ (fun n i hi d => (hc n (denseSeq A i) (Finset.mem_image_of_mem _ (Finset.mem_range.mpr hi)) d).1)) have hr := sequence_central ω hω ψ (hz ψ (fun n i hi d => (hc n (denseSeq A i) (Finset.mem_image_of_mem _ (Finset.mem_range.mpr hi)) d).2)) let l := centralize ω (postcompose (sequence φ) (NormUltrapower.quotientMap ω)) hl let r := centralize ω (postcompose (sequence ψ) (NormUltrapower.quotientMap ω)) hr apply no_character_of_pair l r apply Subtype.ext change NormUltrapower.quotientMap ω (sequence φ 1)+NormUltrapower.quotientMap ω (sequence ψ 1)=1 rw [←_root_.map_add,←_root_.map_one (NormUltrapower.quotientMap ω)] congr 1 ext n exact hu n end KirchbergRordam.MultiplicativeChannel namespace KirchbergRordam.TensorHalfFlip open Filter Topology open scoped CStarAlgebra universe u variable {D C : Type u} [CStarAlgebra D] [CStarAlgebra C] [Nontrivial D] [Nontrivial C] theorem injective_of_halfFlip (h : HalfFlip D) (φ : D →⋆ₐ[ℂ] C) : Function.Injective φ := by apply (injective_iff_map_eq_zero φ).mpr intro d hd let f : MaxTensor.Algebra D D →⋆ₐ[ℂ] MinTensor.Algebra C D := MaxTensor.lift (MinTensor.includeLeft.comp φ) MinTensor.includeRight (fun a b => MinTensor.legs_commute (φ a) b) have hL (a : D) : f (MaxTensor.includeLeft a)=MinTensor.includeLeft (φ a) := DFunLike.congr_fun (MaxTensor.lift_includeLeft _ _ _) a have hR (a : D) : f (MaxTensor.includeRight a)=MinTensor.includeRight a := DFunLike.congr_fun (MaxTensor.lift_includeRight _ _ _) a obtain ⟨u,hu⟩ := h have ht := ((map_continuous f).tendsto _).comp (hu d) have hz (n : ℕ) : f (conj (u n) (MaxTensor.includeLeft d))=0 := by simp only [conj,Unitary.conjStarAlgAut_apply,map_mul,map_star,hL,hd,map_zero,mul_zero,zero_mul] change Tendsto (fun n => f (conj (u n) (MaxTensor.includeLeft d))) atTop (𝓝 (f (MaxTensor.includeRight d))) at ht simp only [hz,hR] at ht have he : MinTensor.includeRight (A:=C) d=0 := (tendsto_nhds_unique tendsto_const_nhds ht).symm exact (MinTensor.includeRight_isometry (A:=C) (B:=D)).injective (he.trans (map_zero _).symm) end KirchbergRordam.TensorHalfFlip namespace KirchbergRordam.BalancedDropLimit open Filter theorem central_no_character (ω : Ultrafilter ℕ) (hω : (ω : Filter ℕ)≤cofinite) : IsEmpty (NormUltrapower.CentralAlgebra Algebra ω →⋆ₐ[ℂ] ℂ) := MultiplicativeChannel.no_central_character_of_finite_channels BalancedDropChannels.finite_control ω hω end KirchbergRordam.BalancedDropLimit namespace KirchbergRordam open Filter Topology NormUltrapower theorem balanced_drop_character_criterion (A : Type) [CStarAlgebra A] [Nontrivial A] [TopologicalSpace.SeparableSpace A] (ω : Ultrafilter ℕ) (hω : (ω : Filter ℕ)≤cofinite) : IsEmpty (CentralAlgebra A ω →⋆ₐ[ℂ] ℂ) ↔ Nonempty (A ≃⋆ₐ[ℂ] MinTensor.Algebra A BalancedDropLimit.Algebra) := by constructor · intro hF obtain ⟨ι⟩ := BalancedDropLimit.to_central A ω hω hF obtain ⟨u,hu⟩ := BalancedDropHalfFlip.exists_half_flip exact spatial_absorption_of_central_maximal_half_flip A BalancedDropLimit.Algebra ω ι u hu · rintro ⟨θ⟩ obtain ⟨e⟩ := central_isomorphism θ ω obtain ⟨r⟩ := minimal_tensor_central_right A BalancedDropLimit.Algebra ω have hF := BalancedDropLimit.central_no_character ω hω exact ⟨fun χ => hF.false ((χ.comp e.symm.toStarAlgHom).comp r)⟩ theorem balanced_drop_hom_injective {C : Type} [CStarAlgebra C] [Nontrivial C] (φ : BalancedDropLimit.Algebra →⋆ₐ[ℂ] C) : Function.Injective φ := TensorHalfFlip.injective_of_halfFlip BalancedDropHalfFlip.exists_half_flip φ end KirchbergRordam end end OAI