openAI-math-dataset / lean /OAI /Analysis /JiangSu /DimensionFunctions /FiniteSpectralIntegralOrthogonal.lean
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import Mathlib
import OAI.Analysis.TracialSplitting.PreparedBlocks
import OAI.Analysis.JiangSu.DimensionFunctions.FiniteSpectralIntegral
import OAI.Analysis.JiangSu.CuntzSemigroup.FiniteCuntzSums
namespace OAI
noncomputable section
namespace Pureness
open TraceCone MeasureTheory Set
open scoped ENNReal NNReal CStarAlgebra
variable {D : Type*} [NonUnitalCStarAlgebra D] [PartialOrder D] [StarOrderedRing D]
lemma positive_mul_power_zero (a b : Positive D) (hab : a.1*b.1 = 0)
(r : ℝ≥0) (hr : 0 < r) : a.1 * (Positive.power r b).1 = 0 := by
have hf : Continuous (fun t : ℝ => t^(r : ℝ)) := continuous_id.rpow_const (fun _ => Or.inr r.2)
have hz : (0 : ℝ)^(r : ℝ) = 0 := Real.zero_rpow (by exact_mod_cast hr.ne')
have h := cfc_intertwine b Positive.zero a.1 (by simpa [Positive.zero] using hab)
(fun t : ℝ => t^(r : ℝ)) hf hz
change a.1 * b.1 ^ r = 0
rw [CFC.nnrpow_eq_cfcₙ_real b.1 r b.2]
simpa [Positive.zero] using h
lemma positive_sqrt_mul_zero (a b : Positive D) (hab : a.1*b.1 = 0) :
CFC.sqrt a.1 * CFC.sqrt b.1 = 0 := by
have h := positive_mul_power_zero a b hab (1/2) (by norm_num)
have hs : (Positive.power (1/2) b).1*a.1 = 0 := by
simpa only [star_mul,a.2.star_eq,(Positive.power (1/2) b).2.star_eq,star_zero] using congrArg star h
have ht := positive_mul_power_zero (Positive.power (1/2) b) a hs (1/2) (by norm_num)
have hu := congrArg star ht
have hv : (Positive.power (1/2) a).1 * (Positive.power (1/2) b).1 = 0 := by
simpa only [star_mul,(Positive.power (1/2) a).2.star_eq,
(Positive.power (1/2) b).2.star_eq,star_zero] using hu
simpa only [Positive.power,CFC.nnrpow_eq_pow,← CFC.sqrt_eq_nnrpow] using hv
private noncomputable abbrev positiveSqrt (a : Positive D) : D := CFC.sqrt a.1
private theorem positiveSqrt_star (a : Positive D) : star (positiveSqrt a) = positiveSqrt a :=
(CFC.sqrt_nonneg a.1).star_eq
private theorem positiveSqrt_mul (a : Positive D) : positiveSqrt a * positiveSqrt a = a.1 :=
CFC.sqrt_mul_sqrt_self a.1 a.2
variable {A : Type*} [CStarAlgebra A] [PartialOrder A] [StarOrderedRing A]
def finiteOrthogonalColumn (n : ℕ) (M N : FinMatrix A n) :
CStarMatrix (Fin n × Fin 2) (Fin n × Fin 2) A :=
fun i j => if j.2 = 0 then if i.2 = 0 then M i.1 j.1 else N i.1 j.1 else 0
omit [PartialOrder A] [StarOrderedRing A] in
lemma finiteOrthogonalColumn_starMul (n : ℕ) (M N : FinMatrix A n) :
star (finiteOrthogonalColumn n M N)*finiteOrthogonalColumn n M N =
matrixInterleaveRaw n (star M*M+star N*N,0) := by
apply CStarMatrix.ext
rintro ⟨i,r⟩ ⟨j,s⟩
fin_cases r <;> fin_cases s <;>
simp [finiteOrthogonalColumn,matrixInterleaveRaw_entry',CStarMatrix.mul_apply,CStarMatrix.star_apply,
Fintype.sum_prod_type,Fin.sum_univ_two,CStarMatrix.add_apply,Finset.sum_add_distrib,apply_ite star]
omit [PartialOrder A] [StarOrderedRing A] in
lemma finiteOrthogonalColumn_mulStar (n : ℕ) (M N : FinMatrix A n)
(hMN : M*star N = 0) (hNM : N*star M = 0) :
finiteOrthogonalColumn n M N*star (finiteOrthogonalColumn n M N) =
matrixInterleaveRaw n (M*star M,N*star N) := by
apply CStarMatrix.ext
rintro ⟨i,r⟩ ⟨j,s⟩
have h1 := congrArg (fun P : FinMatrix A n => P i j) hMN
have h2 := congrArg (fun P : FinMatrix A n => P i j) hNM
fin_cases r <;> fin_cases s <;>
simp_all [finiteOrthogonalColumn,matrixInterleaveRaw_entry',CStarMatrix.mul_apply,CStarMatrix.star_apply,
Fintype.sum_prod_type,apply_ite star]
theorem finiteSpectralIntegral_add_orthogonal
(d : finiteCuntzSubmonoid (A := A) →+ ℝ≥0∞) (hd : Monotone d)
(n : ℕ) (M N : Positive (FinMatrix A n)) (hMN : M.1*N.1 = 0) :
finiteSpectralIntegral d n (Positive.add M N) =
finiteSpectralIntegral d n M + finiteSpectralIntegral d n N := by
let e := CStarMatrix.reindexₐ ℂ A (finProdFinEquiv : (Fin n × Fin 2) ≃ Fin (n*2))
let y := e (finiteOrthogonalColumn n (positiveSqrt M) (positiveSqrt N))
have hcross := positive_sqrt_mul_zero M N hMN
have hcross' : positiveSqrt N * positiveSqrt M = 0 := by
simpa only [star_mul,positiveSqrt_star M,positiveSqrt_star N,star_zero] using congrArg star hcross
have hl : Positive.starMul y = Positive.map (matrixInterleave n) (positiveProduct (Positive.add M N) Positive.zero) := by
apply Subtype.ext
change star (e (finiteOrthogonalColumn n (positiveSqrt M) (positiveSqrt N))) *
e (finiteOrthogonalColumn n (positiveSqrt M) (positiveSqrt N)) =
e (matrixInterleaveRaw n (M.1+N.1,0))
rw [← map_star,← map_mul,finiteOrthogonalColumn_starMul,
positiveSqrt_star M,positiveSqrt_star N,
positiveSqrt_mul M,positiveSqrt_mul N]
have hr : Positive.mulStar y = Positive.map (matrixInterleave n) (positiveProduct M N) := by
apply Subtype.ext
change e (finiteOrthogonalColumn n (positiveSqrt M) (positiveSqrt N)) *
star (e (finiteOrthogonalColumn n (positiveSqrt M) (positiveSqrt N))) =
e (matrixInterleaveRaw n (M.1,N.1))
rw [← map_star,← map_mul,finiteOrthogonalColumn_mulStar n _ _
(by simpa only [positiveSqrt_star N] using hcross)
(by simpa only [positiveSqrt_star M] using hcross'),
positiveSqrt_star M,positiveSqrt_star N,
positiveSqrt_mul M,positiveSqrt_mul N]
have h := finiteSpectralIntegral_polar d (n*2) y
rw [hl,hr,finiteSpectralIntegral_block_add d hd,finiteSpectralIntegral_block_add d hd,
finiteSpectralIntegral_zero,add_zero] at h
exact h
end Pureness
end
end OAI