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Coherent polar encoding polarizes the phase channel

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QAlgorithms.Papers.Independent.Intakethird100.P23.phase_polarization

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

prove2quantum

Let U:C2→Cb⊗CeU:\mathbb C^2\to\mathbb C^b\otimes\mathbb C^eU:C2→Cb⊗Ce be an isometry, so U†U=IU^\dagger U=IU†U=I, defining a memoryless channel to Bob and its fixed complementary channel to Eve. All binary inputs are uniform and entropies are in bits. At recursion depth n≥0n\ge0n≥0, let N=2nN=2^nN=2n and apply the coherent Arikan encoder GN=BNF⊗nG_N=B_NF^{\otimes n}GN​=BN​F⊗n, where F=(1011)F=\left(\begin{smallmatrix}1&0\\1&1\end{smallmatrix}\right)F=(11​01​). Amplitude synthesis retains previous bits and averages future bits; phase synthesis retains future bits and averages previous bits, with Bob's coherent copy register CNC^NCN retained. Write r(W)=∥ρ0ρ1∥1=F(W)r(W)=\|\sqrt{\rho_0}\sqrt{\rho_1}\|_1=\sqrt{F(W)}r(W)=∥ρ0​​ρ1​​∥1​=F(W)​ for the root fidelity of a binary channel WWW. Fix 0<β<1/20<\beta<1/20<β<1/2 and put tn=2−Nβt_n=2^{-N^\beta}tn​=2−Nβ. Let GA,GP,GEG_A,G_P,G_EGA​,GP​,GE​ be the respective amplitude-good, phase-good, and Eve-amplitude-good sets, with the strict rule r(WN(i))<tnr(W_N^{(i)})<t_nr(WN(i)​)<tn​. Write A=GA∩GP\mathcal A=G_A\cap G_PA=GA​∩GP​ and B=(GA∪GP)c\mathcal B=(G_A\cup G_P)^cB=(GA​∪GP​)c. Each set depends on nnn and β\betaβ.

The physical encoded purification for a phase string xxx is

∣σx,N⟩=2−N/2∑z∈{0,1}N(−1)x⋅z∣ϕzGN⟩BNEN∣z⟩CN.|\sigma_{x,N}\rangle=2^{-N/2}\sum_{z\in\{0,1\}^N}(-1)^{x\cdot z}|\phi_{zG_N}\rangle^{B^NE^N}|z\rangle^{C^N}.∣σx,N​⟩=2−N/2z∈{0,1}N∑​(−1)x⋅z∣ϕzGN​​⟩BNEN∣z⟩CN.

Construct the synthesized phase channels from its BNCNB^NC^NBNCN marginal with the reverse history convention above. If I(WP)I(W_P)I(WP​) is the single-use phase channel's symmetric Holevo information, then

lim⁡n→∞∣GP∣2n=I(WP).\lim_{n\to\infty}\frac{|G_P|}{2^n}=I(W_P).n→∞lim​2n∣GP​∣​=I(WP​).

This identifies the asymptotic supply of phase-good positions for the coding scheme.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P23
Formal statement
namespace QAlgorithms.Papers.Independent.Intakethird100.P23

open scoped BigOperators ComplexConjugate Matrix

open Filter

open QAlgorithms (Qubits)

open QAlgorithms.Papers.Independent.Information100.P67 (IsDegradable)

attribute [local instance] Classical.propDecidable

/-- Phase polarization for the actual Eq.(8) vector and reverse side information
(I.B, PDF pp.2–3); the limit is along N=2^n. -/
theorem phase_polarization {b e : ℕ} (U : Matrix (Fin b × Fin e) Bool ℂ)
    (hU : Uᴴ * U = 1) (beta : ℝ) (hbeta0 : 0 < beta) (hbeta1 : beta < 1 / 2) :
    Tendsto (fun n => indexRate (goodPhase U n beta)) atTop (nhds (phaseInformation U)) := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P23
Source
Quantum polar codes for arbitrary channels, arXiv:1201.2906v2, PDF p. 3, I.B, Eq. (8)
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What the Lean code literally says, in plain math · gpt-6.1-sol

For all natural numbers b,eb,eb,e, every complex matrix UUU with rows indexed by {0,…,b−1}×{0,…,e−1}\{0,\ldots,b-1\}\times\{0,\ldots,e-1\}{0,…,b−1}×{0,…,e−1} and Boolean columns satisfying U†U=I2U^\dagger U=I_2U†U=I2​, and every real β\betaβ satisfying 0<β<120<\beta<\tfrac120<β<21​, the following convergence holds. Identify Boolean values with 0,10,10,1. For each natural number nnn, including 000, set N=2nN=2^nN=2n and define a binary matrix G(n)G^{(n)}G(n) by

Grj(n)=1⟺∀ 0≤k<n, ⌊j2k⌋ mod 2≤⌊r2n−1−k⌋ mod 2,G^{(n)}_{rj}=1 \quad\Longleftrightarrow\quad \forall\,0\le k<n,\ \left\lfloor\frac{j}{2^k}\right\rfloor\bmod2 \le \left\lfloor\frac{r}{2^{n-1-k}}\right\rfloor\bmod2,Grj(n)​=1⟺∀0≤k<n, ⌊2kj​⌋mod2≤⌊2n−1−kr​⌋mod2,

with entry zero otherwise, and define pn(u)j=(∑r=0N−1urGrj(n)) mod 2p_n(u)_j=(\sum_{r=0}^{N-1}u_rG^{(n)}_{rj})\bmod2pn​(u)j​=(∑r=0N−1​ur​Grj(n)​)mod2. Define vectors and matrices

wx(r,u,z)=2−N/2(−1)∑jxjuj∏j=0N−1U(rj,zj),pn(u)j,Qn(x)=Tr⁡z∣wx⟩⟨wx∣.w_x(\mathbf r,u,\mathbf z) = 2^{-N/2}(-1)^{\sum_jx_ju_j} \prod_{j=0}^{N-1}U_{(r_j,z_j),p_n(u)_j}, \qquad Q_n(x)=\operatorname{Tr}_{\mathbf z}|w_x\rangle\langle w_x|.wx​(r,u,z)=2−N/2(−1)∑j​xj​uj​j=0∏N−1​U(rj​,zj​),pn​(u)j​​,Qn​(x)=Trz​∣wx​⟩⟨wx​∣.

Thus Qn(x)Q_n(x)Qn​(x) is indexed by pairs (r,u)(\mathbf r,u)(r,u). For i<Ni<Ni<N, let mi+(x)m_i^+(x)mi+​(x) be the full length-NNN bit string whose jjj-th bit is xjx_jxj​ when i<ji<ji<j, and zero otherwise, and put

Pn,i(a)=2−(N−1)∑x:xi=a∣mi+(x)⟩⟨mi+(x)∣⊗Qn(x).P_{n,i}(a) = 2^{-(N-1)} \sum_{x:x_i=a} |m_i^+(x)\rangle\langle m_i^+(x)|\otimes Q_n(x).Pn,i​(a)=2−(N−1)x:xi​=a∑​∣mi+​(x)⟩⟨mi+​(x)∣⊗Qn​(x).

For square matrices define

Fr(K,L)=Re⁡tr⁡K L K,S(K)=−Re⁡tr⁡[(x↦xlog⁡2x)(K)],F_{\mathrm r}(K,L) = \operatorname{Re}\operatorname{tr} \sqrt{\sqrt K\,L\,\sqrt K}, \qquad S(K)=-\operatorname{Re}\operatorname{tr}\bigl[(x\mapsto x\log_2x)(K)\bigr],Fr​(K,L)=RetrK​LK​​,S(K)=−Retr[(x↦xlog2​x)(K)],

where the matrix functions use the real continuous functional calculus. Let Pn={i<N:Fr(Pn,i(0),Pn,i(1))<2−Nβ}\mathcal P_n=\{i<N:F_{\mathrm r}(P_{n,i}(0),P_{n,i}(1))<2^{-N^\beta}\}Pn​={i<N:Fr​(Pn,i​(0),Pn,i​(1))<2−Nβ}. With Qa=Q0((a))Q_a=Q_0((a))Qa​=Q0​((a)), the asserted limit is

lim⁡n→∞∣Pn∣2n=S ⁣(Q0+Q12)−S(Q0)+S(Q1)2.\lim_{n\to\infty}\frac{|\mathcal P_n|}{2^n} = S\!\left(\frac{Q_0+Q_1}{2}\right) -\frac{S(Q_0)+S(Q_1)}2.n→∞lim​2n∣Pn​∣​=S(2Q0​+Q1​​)−2S(Q0​)+S(Q1​)​.

The isometry hypothesis cannot hold if b=0b=0b=0 or e=0e=0e=0.

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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