Quantum Information Compression Algorithm: Dynamic Entropy Adjustment

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

Quantum information compression is a critical field for preserving and transmitting quantum information, offering the potential to significantly reduce the volume of data required. Conventional compression algorithms often rely on static parameters, limiting the effectiveness of compression. This paper proposes a novel quantum information compression algorithm, termed "Dynamic Entropy Adjustment" (DEA), that dynamically adjusts the quantum state to maximize information utilization. We demonstrate that the algorithm's compression efficiency is directly proportional to the effectiveness of entropy adjustment, leading to improved data compression rates. The algorithm's core mechanism leverages the inherent sensitivity of quantum states to environmental fluctuations, enabling a more adaptive and efficient compression process. This paper explores the theoretical foundations of DEA and presents preliminary experimental results showcasing its superior performance compared to existing classical compression methods.

DOI: 10.5281/zenodo.22314605

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