The Quantum Algorithmic Optimization of Self-Organized Structures

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the application of self-organized quantum algorithms to optimize complex geometric structures. Traditional quantum algorithms are often limited by the inherent challenges of quantum systems, particularly in maintaining coherence and entanglement. This work proposes a novel approach that leverages the dynamic nature of graphs to guide the optimization process, enabling global optimization of complex geometries. The core mechanism centers around the design of a self-organizing quantum algorithm that adapts to the structure of the problem, iteratively refining the solution towards the desired outcome. The research explores the potential of using graph representations to model the geometric structure, and the resulting algorithm's ability to enhance the performance of various optimization tasks. The paper introduces a framework for evaluating the effectiveness of such algorithms using a defined metric. Finally, the work discusses the theoretical implications and potential future directions of this approach.

DOI: 10.5281/zenodo.22192384

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