import Mathlib import OAI.Analysis.FreeWords.MatrixAverageTrace import OAI.Analysis.FreeWords.RankOneCompression namespace OAI noncomputable section namespace KKMatrixQuantization open KKTraceTransfer KKWeingarten MeasureTheory open scoped BigOperators Matrix.Norms.L2Operator noncomputable section variable {H : Type*} [NormedAddCommGroup H] [InnerProductSpace ℂ H] [CompleteSpace H] variable {M : VonNeumannAlgebra H} (τ : FaithfulNormalTrace M) variable {d : ℕ} (ρ : Matrix (Fin d) (Fin d) ℂ →⋆ₐ[ℂ] ConcreteAlgebra M) theorem traceNorm_compression_sq (q x : ConcreteAlgebra M) (hq : IsStarProjection q) : (((traceNorm τ (q*x*q))^2 : ℝ) : ℂ)=τ.map (q*star x*q*x) := by rw [traceNorm_sq] have hq2 : q*q=q := hq.isIdempotentElem have hqs : star q=q := hq.isSelfAdjoint simp only [star_mul,hqs] calc τ.map (q*(star x*q)*(q*x*q)) = τ.map ((q*star x*(q*q)*x)*q) := by congr 1 _ = τ.map (q*(q*star x*q*x)) := by rw [hq2,τ.tracial] _ = _ := by simp only [← mul_assoc,hq2] theorem average_traceNorm_sq [NeZero d] (x : ConcreteAlgebra M) : τ.map (matrixAverage ρ (star x)*x)=(((traceNorm τ (matrixAverage ρ x))^2 : ℝ) : ℂ) := by rw [traceNorm_sq, matrixAverage_star] calc τ.map (matrixAverage ρ (star x)*x) = τ.map (star x*matrixAverage ρ x) := matrixAverage_trace_symm ρ τ _ _ _ = τ.map (matrixAverage ρ (star x)*matrixAverage ρ x) := by rw [matrixAverage_trace_symm,matrixAverage_idempotent] theorem continuous_compression_energy (z : Fin d) (x : ConcreteAlgebra M) : Continuous (fun U => (traceNorm τ (rankOne ρ z U*x*rankOne ρ z U))^2) := by have he (U : Matrix.unitaryGroup (Fin d) ℂ) : (traceNorm τ (rankOne ρ z U*x*rankOne ρ z U))^2= (τ.map (rankOne ρ z U*star x*rankOne ρ z U*x)).re := by simpa only [Complex.ofReal_re] using congrArg Complex.re (traceNorm_compression_sq τ _ x (rankOne_projection ρ z U)) simp_rw [he] exact Complex.continuous_re.comp (continuous_rankOne_pair τ ρ z (star x) x) theorem integral_compression_energy (hd : 2 ≤ d) (z : Fin d) (x : ConcreteAlgebra M) : (∫ U : Matrix.unitaryGroup (Fin d) ℂ, (traceNorm τ (rankOne ρ z U*x*rankOne ρ z U))^2 ∂matrixHaar d)= ((traceNorm τ x)^2+(d : ℝ)*(traceNorm τ (matrixAverage ρ x))^2)/((d : ℝ)*((d : ℝ)+1)) := by have : NeZero d := ⟨by omega⟩ have he := integral_rankOne_pair τ ρ hd z (star x) x rw [← traceNorm_sq,average_traceNorm_sq] at he have hU (U : Matrix.unitaryGroup (Fin d) ℂ) : τ.map (rankOne ρ z U*star x*rankOne ρ z U*x)= (((traceNorm τ (rankOne ρ z U*x*rankOne ρ z U))^2 : ℝ) : ℂ) := (traceNorm_compression_sq τ _ x (rankOne_projection ρ z U)).symm simp_rw [hU] at he rw [integral_complex_ofReal] at he rw [mul_comm,← div_eq_mul_inv] at he exact_mod_cast he theorem integral_compression_sum {ι : Type*} [Fintype ι] (hd : 2 ≤ d) (z : Fin d) (x : ι → ConcreteAlgebra M) : (∫ U : Matrix.unitaryGroup (Fin d) ℂ, ∑ i,(traceNorm τ (rankOne ρ z U*x i*rankOne ρ z U))^2 ∂matrixHaar d)= ((∑ i,(traceNorm τ (x i))^2)+(d : ℝ)*∑ i,(traceNorm τ (matrixAverage ρ (x i)))^2)/ ((d : ℝ)*((d : ℝ)+1)) := by rw [integral_finsetSum _ (fun i _ => (continuous_compression_energy τ ρ z (x i)).integrable_of_hasCompactSupport (HasCompactSupport.of_compactSpace _))] simp only [integral_compression_energy τ ρ hd z,← Finset.sum_div,Finset.sum_add_distrib,Finset.mul_sum] theorem exists_rankOne_small_compression {ι : Type*} [Fintype ι] (hd : 2 ≤ d) (z : Fin d) (x : ι → ConcreteAlgebra M) (ε : ℝ) (hb : ((∑ i,(traceNorm τ (x i))^2)+(d : ℝ)*∑ i,(traceNorm τ (matrixAverage ρ (x i)))^2)/ ((d : ℝ)*((d : ℝ)+1)) < ε/(d : ℝ)) : ∃ U : Matrix.unitaryGroup (Fin d) ℂ, ∑ i,(traceNorm τ (rankOne ρ z U*x i*rankOne ρ z U))^2 < ε/(d : ℝ) := by by_contra hh push Not at hh have hi : Integrable (fun U : Matrix.unitaryGroup (Fin d) ℂ => ∑ i,(traceNorm τ (rankOne ρ z U*x i*rankOne ρ z U))^2) (matrixHaar d) := by apply integrable_finsetSum intro i hi exact (continuous_compression_energy τ ρ z (x i)).integrable_of_hasCompactSupport (HasCompactSupport.of_compactSpace _) have hle := integral_mono (integrable_const (ε/(d : ℝ))) hi hh rw [integral_const,integral_compression_sum τ ρ hd z x] at hle simp only [probReal_univ,smul_eq_mul,one_mul] at hle linarith end end KKMatrixQuantization end end OAI