Core Claim: Develop a framework based on self-adaptive quantum system time exponents to simulate the time behavior of complex quantum systems using inherent self-correlation, allowing for automated parameter adjustment to achieve optimal prediction accuracy.

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum systems exhibit inherently complex and time-dependent behaviors, posing significant challenges for accurate modeling and simulation. Current time-index models often rely on approximations, limiting their ability to capture the true dynamics of these systems. This paper introduces a novel approach leveraging self-adaptive quantum system time exponents to address these limitations. We propose a framework that dynamically adjusts model parameters based on the system's inherent self-correlation, enabling automated parameter optimization for enhanced prediction accuracy. This method utilizes the system's self-adjoint nature to guide the model's evolution and improve the representation of time-dependent processes. We demonstrate the effectiveness of this approach through simulations of various quantum systems, showcasing superior predictive performance compared to traditional methods. This research contributes to the advancement of quantum simulation by providing a robust and automated tool for modeling complex time-dependent phenomena. The framework offers a fundamentally new perspective on time-index modeling, capitalizing on the unique properties of quantum systems.

DOI: 10.5281/zenodo.22243326

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