Title: Quantum Resonance-Based Constraint Optimization for Complex Systems

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum resonance, a theoretical concept in quantum mechanics, offers a unique approach to optimization that has garnered increasing attention in recent years. This paper explores the application of quantum resonance to constraint optimization, specifically for systems characterized by high degrees of entanglement. We propose a novel algorithm utilizing the principles of quantum resonance to create a feedback loop that stabilizes solutions and facilitates the discovery of global optima in these complex environments. The core mechanism centers around generating resonant frequencies within the system, which promotes efficient exploration of the solution space and facilitates the identification of optimal configurations. This work presents a framework for tackling optimization challenges with intricate feedback loops, potentially offering a significant advancement over traditional methods. The paper details the algorithm's design, implementation, and preliminary results, demonstrating the potential of quantum resonance to provide a new methodology for achieving robust and globally optimal solutions within complex systems.

DOI: 10.5281/zenodo.22263165

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