Title: Topological Entanglement Dynamics with Adaptive Curvature

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper investigates the dynamics of topological entanglement, exploring a new framework for quantifying and controlling its evolution. Traditional entanglement analysis primarily focuses on measuring entanglement properties, while this work proposes a dynamic curvature field that influences entanglement, enabling precise manipulation of the resulting geometric structure. We leverage Bayesian optimization to learn the optimal curvature field, leading to a novel approach for predicting and controlling topological entanglement. The core claim is that this framework offers a significant advancement over existing methods, providing unprecedented precision and potential for manipulating complex quantum states. This research addresses limitations in current entanglement analysis by explicitly modeling the geometric structure of entangled states, offering a fundamentally new perspective on their dynamics.

DOI: 10.5281/zenodo.22459683

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