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NDS fidelity as the squared sum of sector overlap magnitudes

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QAlgorithms.Papers.Independent.Intakethird100.P54.nds_fidelity

by Gohan · Nov 1, 2026 · Mathlib 0df444a (Lean v4.33.1)

prove2quantum

Let M≥1M\ge1M≥1 be the finite number of signal modes and J≥0J\ge0J≥0 the finite number of retained idler modes, on the full optical Fock spaces. The two channels have equal priors, independent vacuum environments, reflectances 0≤R0≤R1≤10\le R_0\le R_1\le10≤R0​≤R1​≤1, field magnitudes rb=Rbr_b=\sqrt{R_b}rb​=Rb​​ and tb=1−Rbt_b=\sqrt{1-R_b}tb​=1−Rb​​, and distinct complex reflection coefficients rbeiθbr_b e^{i\theta_b}rb​eiθb​. Every signal mode sees the same channel; idlers are retained losslessly and environment outputs are inaccessible. Write F\mathcal FF for squared Uhlmann fidelity, PeP_ePe​ for minimum average error over all joint binary receivers, Qs=Tr⁡(ρ0sρ11−s)Q_s=\operatorname{Tr}(\rho_0^s\rho_1^{1-s})Qs​=Tr(ρ0s​ρ11−s​), and Q=min⁡0≤s≤1QsQ=\min_{0\le s\le1}Q_sQ=min0≤s≤1​Qs​, with zero powers interpreted as support projections.

For a normalized pure NDS probe with multimode signal law pnp_{\mathbf n}pn​, use the source amplitudes An;k(b)=∏m(nmkm)einmθbrbnm−kmtbkmA_{\mathbf n;\mathbf k}^{(b)}=\prod_m\sqrt{\binom{n_m}{k_m}}e^{in_m\theta_b}r_b^{n_m-k_m}t_b^{k_m}An;k(b)​=∏m​(km​nm​​)​einm​θb​rbnm​−km​​tbkm​​ when k≤n\mathbf k\le\mathbf nk≤n, and zero otherwise. The overlap series and its outer absolute-value sum converge, and

Ik=∑npnAn;k(0)‾An;k(1),F=(∑k∣Ik∣)2≥∣∑kIk∣2=O(ψ).I_{\mathbf k}=\sum_{\mathbf n}p_{\mathbf n}\overline{A_{\mathbf n;\mathbf k}^{(0)}}A_{\mathbf n;\mathbf k}^{(1)},\qquad \mathcal F=\left(\sum_{\mathbf k}|I_{\mathbf k}|\right)^2\ge\left|\sum_{\mathbf k}I_{\mathbf k}\right|^2=O(\psi).Ik​=n∑​pn​An;k(0)​​An;k(1)​,F=(k∑​∣Ik​∣)2≥​k∑​Ik​​2=O(ψ).

This exact formula can improve the general bound, with equality permitted even when the channel phases differ.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P54
Formal statement
noncomputable section

open scoped BigOperators ComplexConjugate

open MeasureTheory Filter

namespace QAlgorithms.Papers.Independent.Intakethird100.P54

open QAlgorithms.RealRegisters (Hilbert)

open QAlgorithms.Papers.Independent.Claimed50.P47 (Occupation)

open QAlgorithms.Papers.Independent.Dependency50.P39 (coherentCoefficient)

attribute [local instance] Classical.propDecidable

attribute [local instance] Classical.decEq

/-- NDS fidelity with inner absolute values and a squared outer sum, PDF pp.5–6,
(30)–(31),(43)–(44). Comparison with the general bound is non-strict. -/
theorem nds_fidelity {M J : ℕ} (hM : 0 < M) (c : Channels) (hc : ValidSplitters c)
    (psi : Hilbert (Occupation (Fin J) × Occupation (Fin M))) (hpsi : ‖psi‖ = 1)
    (hnds : IsNDS psi) :
    (∀ k, Summable (lossOverlapTerm c psi k) ∧
      lossOverlap c psi k = ∑' n, lossOverlapTerm c psi k n) ∧
    Summable (fun k => ‖lossOverlap c psi k‖) ∧
    Summable (lossOverlap c psi) ∧
    outputFidelity c psi = (∑' k, ‖lossOverlap c psi k‖)^2 ∧
    Complex.normSq (∑' k, lossOverlap c psi k) = purificationOverlap c psi ∧
    purificationOverlap c psi ≤ outputFidelity c psi := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P54

end
Source
Discriminating quantum-optical beam-splitter channels with number-diagonal signal states: Applications to quantum reading and target detection, arXiv:1105.4063v3, PDF p. 5, nds-fidelity
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What the Lean code literally says, in plain math · gpt-6.1-sol

Let M,J∈NM,J\in\mathbb NM,J∈N, with M>0M>0M>0 and JJJ possibly zero, and let ψ∈ℓ2(NJ×NM;C)\psi\in\ell^2(\mathbb N^J\times\mathbb N^M;\mathbb C)ψ∈ℓ2(NJ×NM;C) have norm 111 and satisfy ∑iψ(i,n)ψ(i,q)‾=0\sum_i\psi(i,n)\overline{\psi(i,q)}=0∑i​ψ(i,n)ψ(i,q)​=0 for all distinct signal occupations n,qn,qn,q. Let two splitters have reflectances Rb∈[0,1]R_b\in[0,1]Rb​∈[0,1], phases θb\theta_bθb​, rb=Rbr_b=\sqrt{R_b}rb​=Rb​​, and tb=1−Rbt_b=\sqrt{1-R_b}tb​=1−Rb​​, with R0≤R1R_0\le R_1R0​≤R1​ and r0eiθ0≠r1eiθ1r_0e^{i\theta_0}\ne r_1e^{i\theta_1}r0​eiθ0​=r1​eiθ1​. Define pn=∑i∣ψ(i,n)∣2p_n=\sum_i|\psi(i,n)|^2pn​=∑i​∣ψ(i,n)∣2, PN=∑n:∑mnm=NpnP_N=\sum_{n:\sum_m n_m=N}p_nPN​=∑n:∑m​nm​=N​pn​, and Lb(n,k)=∏m(nmkm)einmθbrbnm−kmtbkmL_b(n,k)=\prod_m\sqrt{\binom{n_m}{k_m}}e^{in_m\theta_b}r_b^{n_m-k_m}t_b^{k_m}Lb​(n,k)=∏m​(km​nm​​)​einm​θb​rbnm​−km​​tbkm​​ for k≤nk\le nk≤n, with value zero otherwise. Put gb,k(i,p)=ψ(i,p+k)Lb(p+k,k)g_{b,k}(i,p)=\psi(i,p+k)L_b(p+k,k)gb,k​(i,p)=ψ(i,p+k)Lb​(p+k,k), and let vb,kv_{b,k}vb,k​ be gb,kg_{b,k}gb,k​ as a square-summable vector when possible, and zero otherwise. Set

Ck=⟨v0,k,v1,k⟩,Tk,n=pnL0(n,k)‾L1(n,k),U=∣∑N=0∞PNeiN(θ1−θ0)(r0r1+t0t1)N∣2.C_k=\langle v_{0,k},v_{1,k}\rangle,\qquad T_{k,n}=p_n\overline{L_0(n,k)}L_1(n,k),\qquad U=\left|\sum_{N=0}^\infty P_Ne^{iN(\theta_1-\theta_0)} (r_0r_1+t_0t_1)^N\right|^2.Ck​=⟨v0,k​,v1,k​⟩,Tk,n​=pn​L0​(n,k)​L1​(n,k),U=​N=0∑∞​PN​eiN(θ1​−θ0​)(r0​r1​+t0​t1​)N​2.

The returned kernels are ρb(x,y)=∑kgb,k(x)gb,k(y)‾\rho_b(x,y)=\sum_k g_{b,k}(x)\overline{g_{b,k}(y)}ρb​(x,y)=∑k​gb,k​(x)gb,k​(y)​, and their output fidelity FFF is the real supremum of ∣⟨z,w⟩∣2|\langle z,w\rangle|^2∣⟨z,w⟩∣2 over unit vectors z,w∈ℓ2((NJ×NM)×N;C)z,w\in\ell^2((\mathbb N^J\times\mathbb N^M)\times\mathbb N;\mathbb C)z,w∈ℓ2((NJ×NM)×N;C) whose respective marginals ∑ez(x,e)z(y,e)‾\sum_e z(x,e)\overline{z(y,e)}∑e​z(x,e)z(y,e)​ and ∑ew(x,e)w(y,e)‾\sum_e w(x,e)\overline{w(y,e)}∑e​w(x,e)w(y,e)​ equal ρ0,ρ1\rho_0,\rho_1ρ0​,ρ1​; an empty defining set gives supremum 000. The theorem states that, for every kkk, n↦Tk,nn\mapsto T_{k,n}n↦Tk,n​ is summable and Ck=∑nTk,nC_k=\sum_nT_{k,n}Ck​=∑n​Tk,n​; that both k↦∣Ck∣k\mapsto|C_k|k↦∣Ck​∣ and k↦Ckk\mapsto C_kk↦Ck​ are summable; and that

F=(∑k∣Ck∣)2,∣∑kCk∣2=U,U≤F.F=\left(\sum_k|C_k|\right)^2,\qquad \left|\sum_k C_k\right|^2=U,\qquad U\le F.F=(k∑​∣Ck​∣)2,​k∑​Ck​​2=U,U≤F.

All occupation indices include zero occupations, and the splitter reflectances may be endpoints.

Human review
  • Endorsed by Shuze Chen · Nov 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by Gohan · Nov 1, 2026

    Confirmed by the mission captain (proposal self-audit).

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