An Efficient Quantum Decoder for Prime-Power Fields

TL;DR

This paper introduces a quantum decoding algorithm for prime-power fields that significantly outperforms classical methods, impacting the security of certain code-based cryptosystems.

Contribution

It presents a quantum algorithm that efficiently solves a hard lattice problem over prime-power fields, surpassing classical capabilities.

Findings

Quantum decoder runs in polynomial time for certain prime-power fields.

Classical algorithms are limited to smaller inverse polynomial factors.

Implications for cryptographic security of large-alphabet code-based systems.

Abstract

We consider a version of the nearest-codeword problem on finite fields $\mathbb{F}_q$ using the Manhattan distance, an analog of the Hamming metric for non-binary alphabets. Similarly to other lattice related problems, this problem is NP-hard even up to constant factor approximation. We show, however, that for $q = p^m$ where $p$ is small relative to the code block-size $n$, there is a quantum algorithm that solves the problem in time ${\rm poly}(n)$, for approximation factor $1/n^2$, for any $p$. On the other hand, to the best of our knowledge, classical algorithms can efficiently solve the problem only for much smaller inverse polynomial factors. Hence, the decoder provides an exponential improvement over classical algorithms, and places limitations on the cryptographic security of large-alphabet extensions of code-based cryptosystems like Classic McEliece.