基于量子自适应拓扑的几何数据压缩

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the application of quantum-adapted topology for geometric data compression. Traditional data compression techniques rely on classical algorithms, but this research investigates a novel approach leveraging the unique properties of quantum-adapted geometry. The core mechanism involves a quantum-induced transformation that allows for more efficient compression and decompression, ultimately enhancing data storage efficiency. We present a theoretical framework and preliminary experimental results demonstrating the potential of this method.

DOI: 10.5281/zenodo.22196691

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