自适应拓扑量子计算的量子算法优化
Jincheng Zhang
Abstract
Quantum computing holds immense promise for revolutionizing various fields, and the development of efficient quantum algorithms is crucial for realizing this potential. However, the inherent complexity of quantum systems often necessitates sophisticated optimization techniques. This paper introduces a novel approach to quantum algorithm optimization, centered around the dynamic adjustment of quantum algorithm parameters through the exploitation of quantum topology. We propose a framework that dynamically adjusts these parameters based on the system's state, resulting in enhanced algorithm efficiency and accuracy. This method offers a fundamentally new perspective on quantum algorithm optimization, leveraging the unique properties of quantum topology to guide the optimization process. The core mechanism involves manipulating the quantum state to achieve optimal performance. This work presents a preliminary investigation of this approach and outlines potential future research directions.