Dynamic Quantum Self-Organization Optimization

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper introduces a novel dynamic quantum self-organization optimization framework. Traditional optimization methods often struggle to effectively address complex systems due to the inherent challenges of quantum mechanics. We propose a framework that utilizes quantum mechanics to automatically identify and optimize complex systems, leveraging a combination of quantum phenomena and optimization principles. The framework focuses on identifying optimal configurations within a system through iterative quantum self-organization, offering a fundamentally new approach to optimization challenges. The core claim of this work is that this framework provides a significantly more robust and effective method for optimizing complex systems compared to conventional techniques. We present a detailed overview of the proposed framework, its mathematical foundations, and preliminary results demonstrating its effectiveness in a specific, albeit simplified, case study.

DOI: 10.5281/zenodo.22249542

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