基于动态自适应的量子信息压缩算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum information compression is a promising field with the potential to revolutionize data storage and transmission. However, traditional compression techniques often rely on static parameter settings, limiting their effectiveness in real-world scenarios where data characteristics change significantly. This paper introduces a novel quantum information compression algorithm based on dynamic self-adaptation. The core of this approach lies in dynamically adjusting the parameters of the compression process to respond to the unique characteristics of the input data. We demonstrate that this dynamic adaptation significantly improves compression rates compared to static compression methods. The algorithm's design incorporates a feedback loop that continuously evaluates the data's state and adjusts the parameters accordingly, ensuring optimal compression. This work explores the potential of this adaptive approach for a range of quantum data types, highlighting its advantages in handling data with varying complexity and dynamic evolution.

DOI: 10.5281/zenodo.22186588

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