自适应矩阵的非线性几何变换的量子加速计算

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper explores the potential of adaptive matrix transformations to accelerate quantum computation, specifically focusing on the design of a novel quantum acceleration framework. Traditional quantum algorithms often struggle with complex geometric transformations, necessitating static approaches. We propose a new approach that leverages the inherent properties of quantum mechanics to dynamically adjust matrix operations, thereby significantly enhancing computational efficiency. The core mechanism revolves around the creation of a self-adapting matrix transformation process, allowing for efficient handling of non-linear geometric concepts within quantum circuits. This framework addresses the limitations of conventional algorithms by providing a flexible and potentially transformative path towards accelerating quantum calculations. The paper details the design of the framework, its mathematical underpinnings, and preliminary experimental validation demonstrating its efficacy in specific matrix operations. We present a case study demonstrating a significant improvement in computational complexity for a particular geometric transformation, highlighting the framework's potential for broader applicability in quantum computing.

DOI: 10.5281/zenodo.22499338

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