No-communication theorem: commuting Kraus matrices give no instantaneous information transfer
ProvedPeresTerno.no_communicationLet be a density matrix. Let Alice's intervention have outcomes in a finite set with Kraus matrices , and Bob's intervention have outcomes in a finite set with Kraus matrices , all complex matrices, with complete POVMs
Assume (Eq. (9))
Then for every outcome of Bob, the probability that Bob gets irrespective of Alice's result (Eq. (10)) equals the probability without Alice's intervention (Eq. (11)):
All of Alice's operators disappear from Bob's statistics, so Eq. (9) is a sufficient condition for no instantaneous information transfer.
Formalization Note The completeness of Bob's POVM and the density-matrix condition on are part of the source's setting and are kept as hypotheses; the identity itself is a statement about complex numbers.
import Mathlib import Definitions.Def_PeresTerno_kraus_basics open Matrix open scoped ComplexOrder
namespace PeresTerno
theorem no_communication {d α β : Type*} [Fintype d] [DecidableEq d] [Fintype α] [Fintype β]
{ι : α → Type*} [∀ μ, Fintype (ι μ)] {κ : β → Type*} [∀ ν, Fintype (κ ν)]
(A : ∀ μ, ι μ → Matrix d d ℂ) (B : ∀ ν, κ ν → Matrix d d ℂ)
(hA : ∑ μ, povmElement (A μ) = 1) (hB : ∑ ν, povmElement (B ν) = 1)
(hAB : ∀ μ m ν n, Commute (A μ m) (B ν n))
(ρ : Matrix d d ℂ) (hρ : IsDensityMatrix ρ) (ν : β) :
∑ μ, trace (∑ m, ∑ n, B ν n * A μ m * ρ * (A μ m)ᴴ * (B ν n)ᴴ)
= trace (∑ n, B ν n * ρ * (B ν n)ᴴ) := by
sorry
end PeresTerno
Read-back
What the Lean code literally says, in plain math · Aristotle (Harmonic) - NON-BLIND: same agent that drafted the statements
Non-blind read-back - not independent testimony. This read-back was written by the same agent (Aristotle, by Harmonic) that drafted the Lean statement below, with full knowledge of the source paper and of the intended meaning, at the explicit request of the proposal owner. It was not produced by a blind, independent auditor and must not be mistaken for independent testimony. Reviewers should compare the Lean code against the source themselves.
Fix a finite index type (with decidable equality), finite outcome types and , and for each a finite type and for each a finite type . Let (, ) and (, ) be complex matrices. Assume:
- ;
- ;
- for all ;
- is a density matrix (positive semidefinite, ).
Then for every :
an equality of complex numbers. Edge cases: if is empty, hypothesis 4 cannot hold and the statement is vacuous; for nonempty , hypotheses 1-2 force and to be nonempty. The hypotheses are jointly satisfiable, e.g. with one outcome each and .
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.