Gray code based gradient-free optimization algorithm for parameterized quantum circuit  

作　　者：张安琪 武春辉 赵生妹 Anqi Zhang;Chunhui Wu;Shengmei Zhao(Institute of Signal Processing and Transmission,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;Key Laboratory of Broadband Wireless Communication and Sensor Network Technology(Ministry of Education),Nanjing University of Posts and Telecommunications,Nanjing 210003,China)

机构地区：[1]Institute of Signal Processing and Transmission,Nanjing University of Posts and Telecommunications,Nanjing 210003,China [2]Key Laboratory of Broadband Wireless Communication and Sensor Network Technology(Ministry of Education),Nanjing University of Posts and Telecommunications,Nanjing 210003,China

出　　处：《Chinese Physics B》2024年第2期189-194,共6页中国物理B（英文版）

基　　金：This work was supported by the National Natural Science Foundation of China(Grant Nos.61871234 and 62375140);Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX190900).

摘　　要：A Gray code based gradient-free optimization(GCO)algorithm is proposed to update the parameters of parameterized quantum circuits(PQCs)in this work.Each parameter of PQCs is encoded as a binary string,named as a gene,and a genetic-based method is adopted to select the offsprings.The individuals in the offspring are decoded in Gray code way to keep Hamming distance,and then are evaluated to obtain the best one with the lowest cost value in each iteration.The algorithm is performed iteratively for all parameters one by one until the cost value satisfies the stop condition or the number of iterations is reached.The GCO algorithm is demonstrated for classification tasks in Iris and MNIST datasets,and their performance are compared by those with the Bayesian optimization algorithm and binary code based optimization algorithm.The simulation results show that the GCO algorithm can reach high accuracies steadily for quantum classification tasks.Importantly,the GCO algorithm has a robust performance in the noise environment.

关 键 词：gradient-free optimization Gray code genetic-based method 

分 类 号：O413[理学—理论物理] TP18[理学—物理]