Title: Topological Information Extraction via Dynamic Quantum State Modeling

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel algorithm for extracting richer topological information from quantum states. Traditional topological analysis often relies on static representations, limiting the ability to fully characterize complex quantum systems. Our approach leverages the inherent dynamism of quantum states to construct a dynamic quantum state model and utilize it for information extraction. The core mechanism involves establishing a model based on quantum state evolution, enabling the identification and representation of intricate topological structures. This innovation promises a more flexible and insightful understanding of quantum phenomena, potentially offering significant advancements in quantum information processing and analysis. We demonstrate the effectiveness of this method through theoretical analysis and preliminary experimental validation, highlighting its potential to unlock new insights into quantum systems.

DOI: 10.5281/zenodo.22315804

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