自适应几何群的动态拓扑变换与量子计算的协同应用

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper explores the synergistic potential of self-adaptive geometric group dynamics and quantum computing. We develop a novel framework for dynamic topology transformation leveraging self-adaptive geometric group transformations, utilizing quantum computation to facilitate rapid and efficient transformations of complex geometric structures. The core mechanism involves the application of self-adaptive transformations to geometry, enhancing computational efficiency. This approach offers a significant advancement over traditional static topology optimization methods, particularly in scenarios involving dynamic environments and complex geometric transformations. The study demonstrates the efficacy of this framework through simulations and preliminary results, highlighting the benefits of combining these two powerful techniques.

DOI: 10.5281/zenodo.22499319

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