Corollary 4 (Wall 2013): is nondecreasing for concave
ProvedWallGSL.unital_positive_map_trace_concave_nondecreasingCorollary 4 (appendix). Let be an density matrix and let be a positive, trace-preserving, identity-preserving linear map on complex matrices. Then for every function that is concave on ,
In particular the von Neumann entropy does not decrease.
This expresses that the probability eigenvalues can only evolve towards equalization; the paper uses it with the function for and for (eqs. (A.8)–(A.10)).
Formalization Note The paper says "convex"; the statement is formalized for concave , because the paper's own example (A.8)–(A.9) is concave and the convex version is false: for and the completely depolarizing map , a pure state has when .
import Mathlib open Matrix open scoped ComplexOrder
namespace WallGSL
/-- Corollary 4 (appendix) of Wall (2013), with the convexity condition read as concavity
(see the formalization note): for every function `f` concave on `[0, ∞)`, the quantity
`tr f(ρ) = ∑ⱼ f(pⱼ)` does not decrease under a trace-preserving, identity-preserving,
positive linear map `T`. -/
theorem unital_positive_map_trace_concave_nondecreasing
{n : ℕ} (T : Matrix (Fin n) (Fin n) ℂ →ₗ[ℂ] Matrix (Fin n) (Fin n) ℂ)
(hT_pos : ∀ A : Matrix (Fin n) (Fin n) ℂ, A.PosSemidef → (T A).PosSemidef)
(hT_trace : ∀ A : Matrix (Fin n) (Fin n) ℂ, (T A).trace = A.trace)
(hT_one : T 1 = 1)
(ρ : Matrix (Fin n) (Fin n) ℂ) (hρ : ρ.PosSemidef) (hρ_tr : ρ.trace = 1)
(f : ℝ → ℝ) (hf : ConcaveOn ℝ (Set.Ici 0) f) :
∑ j, f (hρ.isHermitian.eigenvalues j) ≤ ∑ j, f ((hT_pos ρ hρ).isHermitian.eigenvalues j) := by sorry
end WallGSL
Read-back
What the Lean code literally says, in plain math · Aristotle (Harmonic) - same agent as the drafter; non-blind
Provenance note — this read-back is NOT blind. It was written by the same agent (Aristotle, by Harmonic) that drafted the Lean statements, with full knowledge of the source paper and of the intended meaning. It is therefore not independent testimony and must not be mistaken for a blind audit; reviewers should treat it as the drafter's own literal reading of the code and compare it against the source themselves.
Data. A natural number ; a -linear map on complex matrices; an complex matrix ; and a function .
Hypotheses.
- maps positive semidefinite matrices to positive semidefinite matrices;
- for all ;
- ;
- is positive semidefinite with ;
- is concave on (no condition on ).
Conclusion. With the eigenvalues of and those of (with multiplicity),
For the trace of is , so hypothesis 4 cannot hold and the statement is vacuous in that case.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.