Quantum State Adaptive Topology Modeling

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel modeling technique centered on the dynamic adaptation of topology within quantum states. Traditional approaches often struggle to effectively represent and model complex system evolution, particularly in systems exhibiting intricate dynamics. We propose a framework that utilizes quantum state information to dynamically adjust the topology of a system, enabling the creation of models capable of evolving and adapting to changes. This approach offers a significant advancement over static models, providing a mechanism for generating more realistic and complex representations of evolving systems. The core mechanism centers around leveraging quantum state data to iteratively refine the topology, allowing for a more nuanced and robust representation of system behavior. This study explores the potential of this technique through theoretical analysis and preliminary simulations, demonstrating its capability to model complex systems exhibiting dynamic evolution.

DOI: 10.5281/zenodo.22292215

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