Quantum Decoherence and Information Compression Co-optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper presents a novel approach to co-optimizing quantum decoherence and information compression. The core idea is to leverage the inherent relationship between these two fundamental quantum phenomena. Traditional methods often treat decoherence and information compression as independent processes, neglecting their mutual influence. Our approach dynamically adjusts the measurement frequency and angle, exploiting the characteristics of decoherence to minimize its impact while simultaneously optimizing the information compression encoding scheme. The proposed algorithm aims to maximize information compression efficiency by actively mitigating decoherence effects. We formulate the problem as an optimization task, defining objectives for both decoherence reduction and compression ratio. The theoretical framework and key equations are presented, outlining the methodology for this co-optimization strategy. The ultimate goal is a significantly improved compression rate, especially in scenarios where decoherence is a dominant factor. We explore the mathematical underpinnings of this interaction, providing a robust theoretical foundation for the proposed approach.

DOI: 10.5281/zenodo.22292747

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