Title: Adaptive Geometry Transformation Generation based on Quantum Computing

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper explores the potential of quantum computing to revolutionize geometry generation, addressing the computational challenges inherent in creating complex geometric transformations. We propose a novel paradigm leveraging quantum computation to design and optimize geometric transformations, aiming to surpass the limitations of classical methods. The core mechanism centers around quantum algorithms for generating and refining geometric primitives, offering a fundamentally different approach to complex shape creation. This research investigates the feasibility of quantum computing for handling geometric transformations with increased efficiency and precision, ultimately leading to a new generation of computational tools for geometric modeling and design. Specifically, we detail the design of a quantum algorithm for generating and manipulating geometric transformations, emphasizing its potential to overcome the computational bottlenecks encountered in traditional approaches. The paper concludes with a discussion of the challenges and future directions of this research.

DOI: 10.5281/zenodo.22279521

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