Adaptive Geometry for Quantum Data Compression

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel quantum data compression technique based on adaptive geometry. Traditional quantum data compression methods often rely on complex quantum algorithms, presenting challenges in terms of speed and efficiency. This approach leverages the inherent complexity of geometric data structures to achieve high compression rates and low latency in quantum data transmission. The core mechanism involves constructing a compression model that utilizes geometric data to optimize compression and delay. The research explores the potential of this method to overcome limitations of existing approaches and offer a promising path toward efficient quantum data management.

DOI: 10.5281/zenodo.22265997

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