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Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper presents a novel approach to quantum state optimization, leveraging adaptive algorithms to dynamically adjust key parameters within a quantum system. Traditional optimization techniques often struggle with the complex, multi-dimensional nature of quantum systems, leading to suboptimal performance. This work introduces a new method that systematically adjusts quantum state parameters to enhance performance, offering a significant improvement over existing approaches. The core mechanism centers on employing a self-tuning algorithm to iteratively refine the quantum state, resulting in enhanced coherence, reduced noise, and ultimately, improved computational capabilities. The study demonstrates the efficacy of this method through a series of simulations focusing on a specific quantum circuit design, showcasing its ability to achieve higher fidelity and efficiency. The focus is on demonstrating a practical and effective methodology for optimizing quantum systems.

DOI: 10.5281/zenodo.22184614

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