Quantum Adaptive Geometry Transformation Algorithm

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper presents a novel quantum adaptive geometry transformation algorithm designed to enhance computational efficiency by dynamically adjusting geometric transformation parameters based on input data. Traditional geometric transformation algorithms often struggle with complex transformations, and this approach leverages quantum mechanics to achieve improved performance. The core mechanism involves a quantum state representation and a dynamically evolved transformation process, resulting in significant gains in computational speed and robustness for a range of geometric transformations. This work explores the potential of quantum algorithms to address limitations in existing geometric computation methods.

DOI: 10.5281/zenodo.22280874

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