基于自组织矩阵的量子态压缩

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum state compression is a crucial aspect of quantum information processing, offering the potential to significantly reduce the volume of quantum information required for transmission and storage. This paper investigates a novel approach to quantum state compression based on the principles of self-organizing matrices, leveraging the inherent structure of quantum networks to achieve efficient data compression. We explore the concept of using self-organizing matrices to represent and compress quantum states, demonstrating its effectiveness through theoretical analysis and preliminary experiments. The core mechanism focuses on utilizing the self-organizing properties of the matrices to achieve compression without significant loss of quantum information. The paper presents a detailed explanation of the proposed algorithm, its mathematical formulation, and the results of testing. The core claim emphasizes the potential for substantial improvements in quantum information transmission efficiency. The research demonstrates a promising path toward a more efficient and practical quantum information transfer paradigm.

DOI: 10.5281/zenodo.22487304

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