拓扑空间数据压缩算法的量子化模拟

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper investigates the application of quantum simulation techniques to data compression, specifically focusing on the unique properties of topological spaces. Traditional data compression methods often rely on classical simulation, which can be computationally expensive and limited in its ability to effectively handle the inherent structure of topological data. This research proposes a novel approach utilizing quantum simulation to compress data by modeling the underlying quantum states of the topological space. We demonstrate the potential of this method to achieve significantly higher compression rates compared to existing techniques, leveraging the inherent properties of topology for enhanced data representation. The core mechanism involves simulating the quantum evolution of data within a topologically constructed space, leading to a compression ratio significantly improved through quantum effects. We explore the fundamental principles of quantum simulation within the context of data compression and present preliminary results showcasing the effectiveness of this methodology.

DOI: 10.5281/zenodo.22608426

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