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Dynamic Quantum Entropy Reduction Algorithm (DQA)

Jincheng Zhang

Published Sep 4, 2026• 0 citations
Publisher

Abstract

Quantum systems often exhibit inherent limitations in their performance, necessitating sophisticated optimization strategies. Traditional entropy reduction techniques, while valuable, frequently rely on static parameter settings. This paper proposes a novel Dynamic Quantum Entropy Reduction Algorithm (DQA) that dynamically adjusts quantum entropy parameters based on the system's unique characteristics. The DQA aims to overcome the limitations of static parameter tuning by iteratively optimizing the entropy reduction process, leading to enhanced quantum system performance. This research explores the theoretical basis of the algorithm, details its implementation, and presents initial experimental results demonstrating its effectiveness in specific quantum scenarios. The core mechanism of DQA involves a feedback loop that continuously refines the entropy reduction based on system-specific properties.

DOI
10.5281/zenodo.22290646

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