Quantum-behaved PSO-based Lyapunov control of closed quantum systems

被引:0
|
作者
Liu, Song [1 ]
Kuang, Sen [1 ,2 ]
机构
[1] Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China
[2] Univ Sci & Technol China, CAS Key Lab Technol Geospatial Informat Proc & Ap, Hefei 230027, Peoples R China
来源
2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC) | 2021年
关键词
Quantum systems; Lyapunov control; quantum-behaved PSO algorithm; energy-level connectivity graph; high-population transfer;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A Lyapunov-based control scheme is presented to drive closed quantum systems into any target eigenstate with as high population as possible by the quantum-behaved particle swarm optimization (PSO) algorithm. Based on a Lyapunov function with a Hermitian operator to be constructed, a control law with the unknown parameters contained in the Hermitian operator is designed. To achieve high-population state transfer to the target state, we first initialize those unknown parameters by choosing a path to the target state in its energy-level connectivity graph and setting their values along the path. Then, a set of optimal parameters is found by the quantum-behaved PSO algorithm. Finally, numerical simulation experiments are performed on a five-level quantum system and a four-qubit system to demonstrate the effectiveness of the control scheme in this paper.
引用
收藏
页码:6312 / 6316
页数:5
相关论文
共 50 条
  • [21] Sonar Objective Detection Based on Dilated Separable Densely Connected CNNs and Quantum-Behaved PSO Algorithm
    Wang, Zhen
    Wang, Buhong
    Guo, Jianxin
    Zhang, Shanwen
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2021, 2021
  • [22] Preliminary research on abnormal brain detection by wavelet-energy and quantum-behaved PSO
    Zhang, Yudong
    Ji, Genlin
    Yang, Jiquan
    Wang, Shuihua
    Dong, Zhengchao
    Phillips, Preetha
    Sun, Ping
    TECHNOLOGY AND HEALTH CARE, 2016, 24 : S641 - S649
  • [23] Aeroengine Deviation Parameters Nonlinear Estimation Using Improved Quantum-behaved PSO Algorithm
    Yin Dawei
    Chang Bin
    Yan Xianrong
    Feng Yubo
    PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE, 2012, : 2013 - 2018
  • [24] Quantum-Behaved Particle Swarm Optimization Based on Comprehensive Learning
    Long, HaiXia
    Zhang, XiuHong
    ADVANCES IN ELECTRONIC COMMERCE, WEB APPLICATION AND COMMUNICATION, VOL 2, 2012, 149 : 15 - 20
  • [25] A quantum-behaved evolutionary algorithm based on the Bloch spherical search
    Li, Panchi
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2014, 19 (04) : 763 - 771
  • [26] Dynamic clustering based on quantum-behaved particle swarm optimization
    Fu, Liuqiang
    Zhang, Hongwei
    ADVANCES IN APPLIED SCIENCE AND INDUSTRIAL TECHNOLOGY, PTS 1 AND 2, 2013, 798-799 : 808 - 813
  • [27] Switching control of closed quantum systems via the Lyapunov method
    Zhao, Shouwei
    Lin, Hai
    Xue, Zhengui
    AUTOMATICA, 2012, 48 (08) : 1833 - 1838
  • [28] Optimal Lyapunov-based quantum control for quantum systems
    Hou, S. C.
    Khan, M. A.
    Yi, X. X.
    Dong, Daoyi
    Petersen, Ian R.
    PHYSICAL REVIEW A, 2012, 86 (02):
  • [29] Parameters identification of chaotic systems by quantum-behaved particle swarm optimization
    Yang, Kaiqiao
    Maginu, Kenjiro
    Nomura, Hirosato
    INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2009, 86 (12) : 2225 - 2235
  • [30] A modified Quantum-behaved Particle Swarm Optimization
    Sun, Jun
    Lai, C. -H.
    Xu, Wenbo
    Ding, Yanrui
    Chai, Zhilei
    COMPUTATIONAL SCIENCE - ICCS 2007, PT 1, PROCEEDINGS, 2007, 4487 : 294 - +