Quantum Entanglement Time Scale Mapping for Optimization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum entanglement, a fundamental quantum phenomenon, offers a unique potential for enhancing optimization algorithms. This paper explores the application of quantum entanglement to create a self-adaptive time scale mapping, designed to improve the precision of complex systems through dynamic time scale adjustment. We propose a novel framework that leverages the non-linear properties of entangled states to dynamically adjust the rate of change within a system, leading to more accurate predictions and control. The core mechanism centers around utilizing entangled states to represent the system's state and generate a time scale mapping that responds to changes in the system's dynamics. This theoretical framework provides a fundamentally new approach to optimization by shifting the focus from static parameter adjustments to dynamic time scale manipulation, offering a promising pathway towards enhanced predictive capabilities. The potential impact of this research extends to diverse fields including complex systems modeling, control systems, and data analysis.

DOI: 10.5281/zenodo.22184274

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