Dynamic Topology Transformations: Quantum Algorithm Optimization

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Dynamic topology transformations (DTT) are a powerful technique for generating complex 3D shapes from initial 2D shapes. This research investigates the potential of quantum algorithms to optimize DTT, aiming to enhance geometric modeling and simulation capabilities. We propose a novel quantum algorithm that leverages the unique properties of quantum states to accelerate the optimization process. The core mechanism centers around a quantum optimization loop that iteratively refines the DTT parameters, yielding improved results compared to classical methods. The study will demonstrate the efficacy of this approach through simulations of various geometric transformations. This work presents a promising avenue for advancing the field of geometric modeling and simulation, particularly through the application of quantum optimization.

DOI: 10.5281/zenodo.22272101

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