Unnumbered Corollary: extremal rank bound
OpenQAlgorithms.Papers.Independent.Intakethird100.P12.extremal_rank_boundLet be the dimensions of finite-dimensional complex Hilbert spaces with chosen orthonormal bases. Let be positive semidefinite operators of trace one. Write for all joint density matrices with these two partial traces, and for its extreme points over the real scalars. Coordinates in the tensor product use lexicographic order.
For every extreme coupling ,
This bounds the rank of an extreme point using only the subsystem dimensions. One-dimensional subsystems are included; no full-rank assumption is imposed on the marginals.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P12
namespace QAlgorithms.Papers.Independent.Intakethird100.P12
open scoped ComplexConjugate ComplexOrder
/-- Unnumbered Corollary after Proposition 2.3, PDF pp.6–7.
No d1,d2>=2 restriction: singleton coupling sets also satisfy the bound. -/
theorem extremal_rank_bound {d1 d2 : ℕ}
(rho1 : Matrix (Fin d1) (Fin d1) ℂ) (rho2 : Matrix (Fin d2) (Fin d2) ℂ)
(hm1 : IsDensityMatrix rho1) (hm2 : IsDensityMatrix rho2)
(rho : Matrix (Fin d1 × Fin d2) (Fin d1 × Fin d2) ℂ)
(hext : rho ∈ Set.extremePoints ℝ (finiteCouplingSet rho1 rho2)) :
(rho.rank : ℝ) ≤ Real.sqrt ((d1 : ℝ)^2 + (d2 : ℝ)^2 - 1) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P12
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What the Lean code literally says, in plain math · gpt-6.1-sol
For any natural numbers , let and be complex positive semidefinite matrices of sizes and , respectively, each with trace . Define to be the set of complex positive semidefinite matrices , indexed by pairs , with trace and satisfying
For every matrix that is an extreme point of , with extremality taken over the real numbers, its complex matrix rank satisfies
Here an extreme point belongs to and cannot be expressed as a strict convex combination of two distinct members of . Although zero dimensions are quantified over, the trace- hypotheses cannot hold when either dimension is zero.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.