Self-Adaptive Chaos Models in Quantum Computation Evolution

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper explores the application of self-adaptive chaos models to quantum computation evolution, aiming to provide precise simulations of complex systems and dynamic geometric transformations. Traditional computational methods often struggle with the intricacies of dynamic systems, and this integrated approach offers a novel pathway to enhanced simulation fidelity and evolution. We propose a framework utilizing quantum computation's inherent properties to achieve accurate, dynamic geometric modifications to system evolution. The core mechanism involves the iterative application of self-adaptive chaos dynamics, generating subtle geometric shifts that influence the system's trajectory. The resulting simulations demonstrate improved accuracy and robustness compared to traditional methods, particularly in scenarios involving complex, nonlinear dynamics. This research presents a fundamentally new method for quantum computation evolution, leveraging the principles of self-adaptive chaos to achieve unprecedented precision and flexibility.

DOI: 10.5281/zenodo.22499334

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