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arXiv · 2605.20958

High-Dimensional Carrier-Assisted Entanglement Purification Based on Mutually Unbiased Bases

Zihua Song·Lin Chen·Yongge Wang
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Abstract

Distilling high-dimensional entanglement under general asymmetric Pauli noise remains challenging. For the unprocessed qutrit single-carrier recurrence studied here, severe noise asymmetry can prevent the convergence condition from being satisfied. In this paper, we investigate carrier-assisted entanglement purification protocols, namely CAEPP and mCAEPP, first for two-qutrit systems, and show that the unprocessed single-carrier recurrence is bottlenecked by marginal $X$-error probabilities. To overcome this limitation, we introduce MUB-guided preprocessing that combines randomized inversion-pair symmetrization with deterministic maximum-line alignment. For any qutrit Pauli channel with initial fidelity $p_{00}>1/3$, we prove that, conditioned on successful syndrome outcomes, the MUB-adapted recurrence converges for every sufficiently large fixed carrier number and that its fixed-point fidelity approaches one in the subsequent large-carrier limit. We further extend the algebraic carrier-assisted framework and the asymmetric-noise bottleneck to arbitrary qudit dimensions, and show that in prime-power dimensions the finite-field preprocessing gives the sufficient threshold $p_{00}>1/d$. A certified equal-target comparison over a finite deterministic optimization domain further shows that neither the MUB-adapted strategy nor complete Pauli-label twirling uniformly dominates the other in finite-resource cost.

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Zihua Song, Lin Chen, Yongge Wang. 2026-05-20. High-Dimensional Carrier-Assisted Entanglement Purification Based on Mutually Unbiased Bases. https://arxiv.org/abs/2605.20958

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