Adaptive Chaos System Modeling Quantum Computation Optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper presents a novel approach to adaptive chaos system modeling using quantum computation, focusing on optimizing complex system behavior. We introduce a quantum-enhanced optimization algorithm that dynamically adjusts the parameters of a chaotic system, enabling more precise and efficient modeling, particularly within materials science and biological morphology. The core mechanism leverages quantum entanglement and superposition to achieve a sophisticated, self-correcting optimization process. The study demonstrates the potential of this method to significantly enhance the accuracy and speed of complex system simulations, offering a fundamentally new paradigm for tackling challenging problems in these fields. We explore the theoretical underpinnings of the algorithm and present preliminary experimental results showcasing its efficacy.

DOI: 10.5281/zenodo.22296295

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