Adaptive Quantum Algorithm-Based Dynamic Topology Modeling (AQDMM)

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper introduces an innovative approach to dynamic topology modeling, leveraging the power of adaptive quantum algorithms to simulate complex systems and dynamically adjust model parameters. Traditional approaches often struggle with the complexity and scalability of these simulations. AQDMM offers a fundamentally new paradigm by employing quantum algorithms to create and refine complex topological structures, enabling more accurate and efficient modeling. This research explores the design and implementation of AQDMM, highlighting its potential for simulating a wide range of systems exhibiting dynamic topology. The paper details the core mechanism, focusing on quantum algorithms for topology representation and adaptive parameter adjustment. The resulting model demonstrates significant improvements in simulation accuracy and efficiency compared to existing methods, particularly for systems with intricate topological relationships. The study emphasizes the benefits of this approach in tackling problems requiring real-time adaptation to dynamic systems.

DOI: 10.5281/zenodo.22614188

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