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Quantum State Self-Associating Optimization

Jincheng Zhang

Published Sep 3, 2026• 0 citations
Publisher

Abstract

Quantum State Self-Associating Optimization is a novel optimization algorithm designed to address the challenges of optimizing quantum systems. Traditional optimization methods often struggle with the complexity of quantum systems, necessitating the development of specialized approaches. This paper introduces a new algorithm that leverages the unique self-associating properties of quantum states to provide efficient and automated optimization. The core mechanism centers around utilizing quantum state analysis to guide parameter adjustments, fostering a natural optimization process. We present the algorithm's design, detailed mathematical formulations, and preliminary experimental results demonstrating its effectiveness in optimizing various quantum systems.

DOI
10.5281/zenodo.22265606

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