Geometric Chaos: A Quantum Computing Paradigm

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper investigates the application of geometric chaos theory as a foundational paradigm for quantum computing, specifically focusing on the modeling and prediction of time series data. We propose a novel framework that leverages the inherent nonlinear dynamics and self-organization exhibited by geometric chaos to enhance prediction accuracy and provide more robust decision-making capabilities. The core mechanism centers on mapping time series data to the geometric chaos framework, utilizing the unique properties of this system to identify long-term trends and patterns. This approach offers a significant advancement over traditional time series models by explicitly addressing the fundamental characteristics of chaotic systems. This paper demonstrates the potential of this paradigm to achieve more accurate risk assessment and optimization in complex scenarios.

DOI: 10.5281/zenodo.22324083

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