Quantum Error Correction Coding Based Distributed Learning Algorithm

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper proposes a novel distributed learning algorithm leveraging the redundancy inherent in quantum error correction (QEC) coding. The core idea is to encode the learning outcomes of each node into the channels of a QEC code, subsequently decoding them to recover the original information. Through iterative exchanges of encoded information via these channels, nodes collaboratively learn. Unlike traditional distributed learning which often assumes ideal communication channels, this approach constructs a robust system directly utilizing the noise-resilient properties of QEC. We formally define the algorithm, outlining the encoding and decoding processes, and analyze its potential to improve learning efficiency and resilience, particularly in environments with significant communication noise. The key contribution lies in the integration of QEC into the distributed learning framework, creating a fundamentally more robust and potentially more efficient learning paradigm. The theoretical framework presented here provides a foundation for future research into applying QEC-based distributed learning to various complex systems. ---

DOI: 10.5281/zenodo.22271758

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