Corollary 2: non-entangling channels can increase Schmidt rank
OpenQAlgorithms.Papers.Independent.Intakethird100.P19.schmidtRank_increaseAll Hilbert spaces are finite-dimensional complex spaces with fixed product bases and positive local dimensions. States are positive semidefinite operators of trace one; pure kets have norm one. A non-entangling map is completely positive and preserves the full separable positive cone. A channel is also trace preserving. For integers , there exist a pure state on and a non-entangling channel from to such that
Schmidt rank counts the positive squared Schmidt coefficients. This witnesses failure of Schmidt-rank monotonicity.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P19
noncomputable section
open QAlgorithms QAlgorithms.Entanglement Filter
open scoped Matrix ComplexOrder ComplexConjugate ENNReal
attribute [local instance] Classical.propDecidable Classical.decEq
namespace QAlgorithms.Papers.Independent.Intakethird100.P19
open QAlgorithms.Papers.Independent.Information100.P21 (Op FiniteLOCC)
open QAlgorithms.Papers.Independent.Information100.P19 (Bip)
open QAlgorithms.Papers.Independent.Information100.P69 (CP)
open QAlgorithms.Papers.Independent.Information100.P71 (supportPower SupportIncluded)
open QAlgorithms.Papers.Independent.Dependency50.P19 (epr)
/-- Corollary 2, PDF p.9: currency of rank k can produce a pure state of rank d>k. -/
theorem schmidtRank_increase (k d : ℕ) (hk : 2 ≤ k) (hkd : k < d) :
∃ phi : UnitBipartiteKet d d, ∃ L : Superop (Fin k × Fin k) (Fin d × Fin d),
IsChannel L ∧ NE L ∧ L (epr k) = phi.rho ∧ finiteSchmidtRank phi.ket = d := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P19
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For every pair of natural numbers satisfying , there exist a complex Euclidean vector on with , and a map from matrices on to matrices on , such that is a channel, has a finite Kraus representation, preserves separable positive matrices, and
Here a channel has a finite Kraus representation with ; a separable positive matrix is a finite sum with nonnegative weights and positive semidefinite trace-one factors, without requiring the weights to sum to one; has entry at and zero at all other entries; and are the eigenvalues, in descending order and with multiplicity, of the reduced matrix
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.