计算机科学
量子计算机
量子算法
量子电路
量子
理论计算机科学
计算机工程
量子网络
计算机体系结构
量子力学
物理
作者
Weiwei Zhu,Jiangtao Pi,Qiuyuan Peng
标识
DOI:10.1145/3564982.3564989
摘要
With the rapid development of quantum computing, the variational quantum algorithms capitalize on the classical optimizer and parametrized quantum circuit to provide outperformance on specific tasks such as combinatorial optimization problems. However, the performance of these hybrid quantum-classical algorithms heavily relies on the design of quantum circuit architecture. Being restricted by the noise of the near-term quantum device, how to trade off the computational power of quantum circuits and the noise of quantum gates is a challenging task for design circuit architecture. In this paper, we give a brief view of the recently proposed methods for quantum architecture search including the differentiable circuit search method, deep reinforcement learning based method, and evolutionary based methods.
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