Matrix Transformations for Quantum Acceleration

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper investigates the potential of matrix-based geometric transformations as a foundation for quantum acceleration. The core claim posits the development of an algorithm leveraging quantum algorithms' superposition and entanglement to efficiently perform geometric operations, offering a novel approach to accelerating computational tasks. We explore the fundamental principles underlying this approach, detailing the proposed quantum transformation process and its potential benefits. The work aims to demonstrate a practical implementation utilizing quantum computing capabilities to enhance geometric calculations, addressing limitations inherent in conventional computational methods. This research underscores the convergence of quantum mechanics and geometric analysis, presenting a promising avenue for future advancements in computational science.

DOI: 10.5281/zenodo.22629009

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