Schumacher compression as source transfer
OpenQAlgorithms.Papers.Independent.Intakethird100.P64.sourceSchumacherLet be a unit purification of a density matrix on a finite nonzero register . A separate Source delivers to Alice and retains its inaccessible purifying reference . All target registers are identified copies of . With entropy measured in bits,
For every and every sufficiently large positive , physical local encoding and decoding maps transfer the purification to Bob, with joint full trace-norm error at most , using at most forward qubits. No Bell pairs or other nonlocal assistance are supplied. Local isometric dilations may retain work registers. Any additional generated Bell output may be discarded.
This expresses compression as preserving a Source-controlled quantum system. At entropy zero it permits sublinear communication; it does not assert a nontrivial zero-message finite-block channel.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P64
noncomputable section
namespace QAlgorithms.Papers.Independent.Intakethird100.P64
open QAlgorithms
open QAlgorithms.Papers.Independent.Gap48.P20
(Copies redistributionMarginal subsystemEntropy forwardApply)
open QAlgorithms.Papers.Independent.Dependency50.P48 (densityPower)
open scoped Matrix ComplexConjugate
attribute [local instance] Classical.propDecidable Classical.decEq
/-- PDF p.3, unnumbered compression display: the Source supplies rho at Alice;
H(S)_rho forward qubits per source copy suffice to transfer its full purification
to Bob. Rate zero permits sublinear communication. No input ebits are supplied. -/
theorem sourceSchumacher {R S : Type} [Fintype R] [Fintype S]
[Nonempty R] [Nonempty S] (phi : EuclideanSpace ℂ (R × S))
(hphi : IsState phi) :
SourceTransferAchievable (sourceToAlice S) phi
(vnEntropy (traceLeft (pureDensity phi))) 0 := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P64
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For any finite, nonempty types and vector with , put and , where is applied by continuous functional calculus. For every pair of real numbers and , there is a natural number such that, for every natural number with , there exist natural numbers and complex matrices
satisfying , , and , with the following error bound. Start with the vector on having amplitude ; apply to , send its -bit register to the input of , apply together with the singleton register, and discard both work registers. If is the resulting matrix, retaining , then , where the target vector on has amplitudes
Here , and , with the square root defined by continuous functional calculus. The additional required inequality is ; since , this is simply . Thus no upper bound on is asserted. The numbers may be zero; a zero-bit register is a singleton, while each work register has respectively or basis elements.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.