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Title: Self-Similarity Geometric Transformation Quantum Acceleration Algorithm

Jincheng Zhang

Published Sep 5, 2026• 0 citations
Publisher

Abstract

This paper explores the potential of self-similarity geometric transformation techniques to accelerate quantum computation. The core focus is the development of a novel quantum acceleration algorithm leveraging self-similarity to efficiently handle complex geometric transformations. Traditional methods often struggle with scaling, while this algorithm promises significant speedups through the exploitation of quantum properties. The proposed algorithm employs a self-consistent transformation process, structured around self-similarity principles, to drastically reduce computational complexity. The paper details the algorithm's design, mathematical foundation, and preliminary experimental results demonstrating its effectiveness. We highlight the advantages of this approach compared to existing methods, emphasizing the potential for rapid processing of intricate geometric transformations, ultimately pushing the boundaries of quantum acceleration. The research also addresses key challenges associated with implementing this algorithm on a quantum platform.

DOI
10.5281/zenodo.22316366

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