Per-mode bound for the output thermal-balance defect by the input defects
ProvedOAI.EntropyPhotonNumber.physical_defect_mode_boundLet be the -mode Fock space with annihilation operators , number operators and the weight (diagonal, ); states are positive operators on with number-basis diagonal summing to . A weighted column family of a state is a family in with such that satisfy and .
Put for , let be the logarithmic mean (, ), (), and let
be the thermal weight. A thermal spectral datum on is a Hilbert basis , weights with , and ; put and . Its observable map sends a bounded operator to
so that . The centered space is the orthogonal complement of (the vector with diagonal entries and zero off-diagonal entries), and is the span of the operators . Finally let (which is ) and .
A spectral logarithm datum for a state consists (among other data) of an eigenbasis of with eigenvalues , , and spectral columns with (a weighted column family of ). For mode put (the mean of ) and .
For let be the thermal spectral datum and . The defect functional of at in mode is the bounded functional on
so that is a weak form of the thermal balance versus . Write for the norm of restricted to the centered space .
Setting. Let , , , , . Let be states with and (beam-splitter output relations). For and states , write for the beam-splitter output (the reduced state of the retained port after the passive rotation of transmissivity in every mode applied to ). Put , and . For a bounded let be the partial expectation, over the second input in state , of the Heisenberg dual of the two-stage map (mix the two inputs at , then mix the result with at , keep the retained port) applied to , and the analogous partial expectation over the first input in state . With the centering in the eigenbasis of , the normalized slices are . Assume , that and are number-diagonal thermal states with means and per mode, and . Let be spectral logarithm data for (with eigenbases and eigenvalues ), and let come from a weighted column family of (weighted column families of , and are also given). For a basis and weights let . Assume the Hessian bounds: for and all ,
and the slack conditions and .
Theorem. For every mode ,
where is the weak mean of in mode .
This controls the thermal-balance defect of the regularized output by those of the inputs, up to the error caused by the thermal replacement; it is the per-mode estimate that is later aggregated over modes.
Formalization Note is the norm of G.defect t ht j; is BKM.quadratic, is BKM.center, are rawFirstSlice, rawSecondSlice, is twoPortLambda η θ, is outputReference η θ a d, is mixtureConstant.
import Mathlib
import Definitions.Def_EntropyPhotonNumber
import Definitions.Def_OAI_MathematicalPhysics_Fock_Beam
import Definitions.Def_OAI_Analysis_QuantumTrace_Basic
import Definitions.Def_OAI_MathematicalPhysics_Fock_Operators
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Gibbs
import Definitions.Def_OAI_Analysis_TensorLp
import Definitions.Def_OAI_InformationTheory_PhotonNumber_BeamTrace
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Functions
import Definitions.Def_OAI_Analysis_DiagonalForms
import Definitions.Def_OAI_InformationTheory_PhotonNumber_ThermalMetric
import Definitions.Def_OAI_InformationTheory_PhotonNumber_BeamForms
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Generator
import Definitions.Def_OAI_InformationTheory_PhotonNumber_SpectralLog
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Continuity
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Entropy
import Definitions.Def_OAI_InformationTheory_PhotonNumber_GibbsVariational
import Definitions.Def_OAI_Analysis_Herglotz
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Interpolation
import Definitions.Def_OAI_InformationTheory_PhotonNumber_SpectralForms
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Contraction
import Definitions.Def_OAI_InformationTheory_PhotonNumber_FiniteVariation
import Definitions.Def_OAI_InformationTheory_PhotonNumber_PhysicalMinimum
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Duality
import Definitions.Def_OAI_InformationTheory_PhotonNumber_Minimum
open OAI OAI.EntropyPhotonNumber
open scoped BigOperators ComplexConjugate
open scoped BigOperators
open MvPolynomial
open scoped BigOperators ComplexConjugate Classical
open Submodule
open scoped ENNReal
open scoped ComplexConjugate
open ContinuousLinearMap
open Set Filter Topology Metric
open MeasureTheory Set Filter Topology Metric InnerProductSpace
open scoped ENNReal NNReal
open Filter Topology
open Set Filter Topology MeasureTheory
open QuantumTrace Annihilation ThermalMetric ThermalSpectral TensorLp
open scoped ComplexConjugate
variable {n : ℕ}theorem OAI.EntropyPhotonNumber.physical_defect_mode_bound (η θ κ ε d : ℝ) (a : Fin 2 → ℝ)
(hη : η ∈ Set.Ioo 0 1) (hθ : θ ∈ Set.Ioo 0 1) (hκ : κ ∈ Set.Icc 0 1) (hκ1 : κ<1)
(hd : 0<d) (ha : ∀ i, 0<a i) (hr0 : 0<outputReference η θ a d)
(ρ : Fin 2 → State n) (τD m γ ω ρ0 : State n)
(h1 : IsBeamSplitterOutput η (ρ 0) (ρ 1) m) (h2 : IsBeamSplitterOutput θ m τD γ)
(G : (i : Fin 2) → SpectralLogData n (ρ i)) (G0 : SpectralLogData n ρ0)
(D : WeightedColumns τD) (M : WeightedColumns m) (V : WeightedColumns γ) (O : WeightedColumns ω)
(hD : ∀ k l, entry τD.op k l=if k=l then (QuantumTrace.thermalWeight n d k:ℂ) else 0)
(hO : ∀ k l, entry ω.op k l=if k=l then (QuantumTrace.thermalWeight n (outputReference η θ a d) k:ℂ) else 0)
(hrepl : ρ0.op=((1-κ:ℝ):ℂ) • γ.op+(κ:ℂ) • ω.op)
(hh₁ : ∀ Z, Z ∈ CenteredTests.operatorSpace G0.basis G0.probability →
(1-κ)^2*BKM.quadratic (G 0).basis (G 0).probability
(BKM.center (G 0).basis (G 0).probability
(rawFirstSlice η θ ⟨hη.1.le,hη.2.le⟩ ⟨hθ.1.le,hθ.2.le⟩ (ρ 1) τD Z)) ≤
(1+ε)*(1-κ)*twoPortLambda η θ 0*(h (outputReference η θ a d)/h (a 0))*
BKM.quadratic G0.basis G0.probability Z)
(hh₂ : ∀ Z, Z ∈ CenteredTests.operatorSpace G0.basis G0.probability →
(1-κ)^2*BKM.quadratic (G 1).basis (G 1).probability
(BKM.center (G 1).basis (G 1).probability
(rawSecondSlice η θ ⟨hη.1.le,hη.2.le⟩ ⟨hθ.1.le,hθ.2.le⟩ (ρ 0) τD Z)) ≤
(1+ε)*(1-κ)*twoPortLambda η θ 1*(h (outputReference η θ a d)/h (a 1))*
BKM.quadratic G0.basis G0.probability Z)
(hr : (1+ε)*(∑ i, twoPortLambda η θ i*a i) ≤ outputReference η θ a d)
(hs : (1+ε)*(∑ i, twoPortLambda η θ i*(a i+1)) ≤ outputReference η θ a d+1)
(j : Fin n) :
‖G0.defect (outputReference η θ a d) hr0 j‖ ≤
Real.sqrt (∑ i, ((1-κ)*twoPortLambda η θ i)*‖(G i).defect (a i) (ha i) j‖^2)+
Real.sqrt ((1-κ)*κ)*‖V.weakMean (outputReference η θ a d) j‖*
mixtureConstant (outputReference η θ a d) := by sorry