Title: Adaptive Quantum Algorithm Optimization of Quantum Systems

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper presents a novel quantum system optimization algorithm based on adaptive quantum system dynamics. Traditional optimization methods often rely on fixed parameters, limiting the potential for improved performance. We propose a dynamically adjustable algorithm that leverages the inherent properties of quantum systems to optimize them in real-time. The core mechanism involves a continuous feedback loop that adjusts algorithm parameters based on the quantum system's state, resulting in enhanced efficiency compared to static optimization techniques. This approach addresses the limitations of current algorithms by providing a framework for adapting to the specific characteristics of each quantum system. The design incorporates a novel weighting scheme to determine the impact of each parameter adjustment, ensuring a balanced and effective optimization process. The results demonstrate significant improvements in various quantum system optimization tasks, particularly in scenarios with complex dynamics.

DOI: 10.5281/zenodo.22263749

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