Title: Quantum-Inspired Algorithm for Non-Linear System Dynamics

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum-inspired algorithms represent a novel approach to modeling and predicting complex system dynamics, particularly those exhibiting non-linear behavior. This paper proposes a quantum-inspired algorithm designed to enhance the precision of predictions by mimicking quantum principles in approximating the system's evolution. We explore a framework that utilizes probabilistic elements and entanglement-like correlations to represent and navigate the system's trajectory. The core mechanism centers around a modified variational optimization technique, enhanced with quantum-like stochasticity, to achieve improved accuracy in complex simulations. The paper details the algorithm's architecture, introduces the core methodology, and provides preliminary results demonstrating its potential for advancing the field of system dynamics. The long-term goal is to establish a robust and efficient method for tackling challenging scenarios in diverse scientific and engineering domains.

DOI: 10.5281/zenodo.22223205

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