Adaptive Quantum Potential Field Optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the development of an adaptive quantum potential field optimization algorithm. The core concept revolves around dynamically adjusting quantum potential fields based on the quantum system's inherent properties and surrounding environmental conditions. Traditional static optimization methods often struggle to effectively handle the complexities of quantum systems, presenting a significant challenge in achieving optimal performance. This novel approach leverages the inherent quantum nature of the system, allowing for a truly adaptive optimization process. We propose a framework that iteratively adjusts the potential field to enhance system properties, ultimately leading to improved quantum system performance. This work addresses the limitations of existing techniques by providing a fundamentally different algorithmic approach centered on dynamic potential manipulation.

DOI: 10.5281/zenodo.22297370

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