Dynamic Quantum State Optimization Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel dynamic quantum state optimization algorithm designed to efficiently optimize quantum states and enhance precise control. Traditional optimization methods often rely on static parameter settings, limiting their applicability to complex systems. This work proposes a dynamic approach that leverages quantum state's inherent adaptability to dynamically adjust quantum states, leading to improved optimization performance. The core mechanism involves a combination of quantum state self-adaptation and a tailored topology optimization algorithm, demonstrating significant improvements in achieving precise control and optimization accuracy. This algorithm addresses limitations of existing approaches, offering a more robust and adaptable solution for quantum state manipulation.

DOI: 10.5281/zenodo.22204747

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