基于自适应几何结构的量子计算

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper explores the potential of utilizing adaptive geometric structures to revolutionize quantum computation. Traditional quantum algorithms often face limitations in performance due to inherent geometric constraints. We propose a novel framework that dynamically adjusts the geometry of a quantum system, leveraging the properties of quantum entanglement and superposition to optimize quantum computation. This approach aims to overcome these limitations and unlock new possibilities for quantum algorithm design and execution. The core mechanism involves a continuous optimization loop that adjusts geometric parameters based on the state of the quantum system, ultimately leading to improved fidelity and computational efficiency. This research will focus on the fundamental principles behind adaptive geometry and its application to key quantum algorithms, including Shor's algorithm and Grover's search.

DOI: 10.5281/zenodo.22507765

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