Dynamic Topology-Dependent Quantum Error Correction Coding

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper proposes a novel approach to quantum error correction (QEC) that dynamically adapts to topological disturbances encountered during quantum information transmission. The core concept revolves around leveraging machine learning to predict these disturbances and subsequently designing reconfigurable error-correcting codes. Traditional QEC methods often rely on static coding schemes, which are inherently vulnerable to the fluctuating topological environment. Our proposed framework utilizes a predictive model to anticipate the patterns of topological disruption, enabling the real-time adjustment of the coding structure. This dynamic adjustment is achieved by modifying the correlations between qubits, effectively mitigating the detrimental effects of the topological noise. The theoretical framework outlines a system where the error correction efficiency is maximized by responding to the specific characteristics of the quantum channel. The key contributions lie in the integration of machine learning for predictive modeling and the design of adaptable coding strategies, offering a significant advancement over conventional static QEC approaches. The ultimate goal is a more robust and efficient quantum communication system.

DOI: 10.5281/zenodo.22273796

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