Quantum Error Correction via Adaptive Resonance Networks

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum error correction is a critical challenge in quantum computing, demanding highly sophisticated techniques to protect quantum information from decoherence and errors. This paper explores the application of Adaptive Resonance Networks (ARNs) as a novel quantum error correction scheme. We propose a system where the ARN dynamically adjusts its network parameters to optimize for minimizing error rates, tailored to specific qubit configurations. This approach leverages the inherent adaptability of neural networks to enhance error correction efficiency and robustness. The core mechanism involves a neural network-inspired architecture that learns and adapts to the observed error patterns, offering a potentially more efficient and robust strategy compared to traditional approaches. The paper details the design of the ARN, its operational methodology, and preliminary results demonstrating its effectiveness in mitigating errors.

DOI: 10.5281/zenodo.22266785

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