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arXiv · 2410.21124

Quantum channel coding: Approximation algorithms and strong converse exponents

Aadil Oufkir·Mario Berta
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Abstract

We study relaxations of entanglement-assisted quantum channel coding and establish that non-signaling assistance and a natural semi-definite programming relaxation\, -- \,termed meta-converse\, -- \,are equivalent in terms of success probabilities. We then present a rounding procedure that transforms any non-signaling-assisted strategy into an entanglement-assisted one and prove an approximation ratio of $(1 - e^{-1})$ in success probabilities for the special case of measurement channels. For fully quantum channels, we give a weaker (dimension dependent) approximation ratio, that is nevertheless still tight to characterize the strong converse exponent of entanglement-assisted channel coding [Li and Yao, IEEE Tran.~Inf.~Theory (2024)]. Our derivations leverage ideas from position-based coding, quantum decoupling theorems, the matrix Chernoff inequality, and input flattening techniques.

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Aadil Oufkir, Mario Berta. 2024-10-28. Quantum channel coding: Approximation algorithms and strong converse exponents. https://doi.org/10.22331/q-2025-10-06-1877

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