基于张量的混沌动力学系统建模

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper investigates the application of tensor networks to model chaotic dynamical systems. We present a novel method for representing and manipulating chaotic data using tensor networks, enabling the simulation of their evolution and the generation of predictive capabilities. The core mechanism centers around leveraging the inherent properties of tensor networks to capture the complex dynamics of chaotic systems, offering a powerful framework for studying and potentially predicting their behavior. The study encompasses the design of a tensor network representation, the implementation of a simulation algorithm, and an analysis of the resulting dynamical behavior. The potential of this approach to modeling complex systems and generating predictive capabilities is discussed.

DOI: 10.5281/zenodo.22302801

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