基于量子纠缠的自适应数据压缩算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel data compression algorithm leveraging the unique properties of quantum entanglement. Traditional data compression methods often rely on statistical redundancy and lossless compression, which can be limited in certain scenarios. This research explores the potential of quantum entanglement to enhance compression efficiency and robustness against noise. We propose a quantum-enhanced data compression scheme that utilizes entangled states to represent data, enabling more efficient data transfer and storage, while simultaneously improving error correction. The algorithm's core mechanism centers around exploiting entanglement to establish a higher-dimensional representation of data, reducing the overall data volume. We demonstrate the effectiveness of this approach through theoretical analysis and preliminary experiments, showcasing significant improvements in compression ratio and resilience to noise compared to existing methods. The research highlights the potential of quantum entanglement to revolutionize data compression, offering a promising path towards more efficient data storage and transmission.

DOI: 10.5281/zenodo.22204954

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