Table of Contents Author Guidelines Submit a Manuscript
The Scientific World Journal
Volume 2013, Article ID 869285, 11 pages
http://dx.doi.org/10.1155/2013/869285
Review Article

Closed-Loop and Robust Control of Quantum Systems

1Department of Control and System Engineering, Nanjing University, Nanjing 210093, China
2School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024, China
3Institute of Cyber-Systems and Control, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China

Received 11 June 2013; Accepted 16 July 2013

Academic Editors: A. Mock and C.-L. Tien

Copyright © 2013 Chunlin Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [12 citations]

The following is the list of published articles that have cited the current article.

  • Shahid Qamar, Shuang Cong, and Bilal Riaz, “Lyapunov-based feedback control of two-level stochastic open quantum systems,” 2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), pp. 48–53, . View at Publisher · View at Google Scholar
  • Yingying Sun, Chengzhi Wu, Zhangqing Zhu, and Chunlin Chen, “Comparison of learning methods for landscape control of open quantum systems,” Proceeding of the 11th World Congress on Intelligent Control and Automation, pp. 1241–1246, . View at Publisher · View at Google Scholar
  • Stuart S. Szigeti, Andre R. R. Carvalho, James G. Morley, and Michael R. Hush, “Ignorance Is Bliss: General and Robust Cancellation of Decoherence via No-Knowledge Quantum Feedback,” Physical Review Letters, vol. 113, no. 2, 2014. View at Publisher · View at Google Scholar
  • Chunlin Chen, Daoyi Dong, Han-Xiong Li, Jian Chu, and Tzyh-Jong Tarn, “Fidelity-Based Probabilistic Q-Learning for Control of Quantum Systems,” IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 5, pp. 920–933, 2014. View at Publisher · View at Google Scholar
  • L. C. Wang, and X. X. Yi, “Lyapunov control on quantum systems,” International Journal Of Modern Physics B, vol. 28, no. 30, 2014. View at Publisher · View at Google Scholar
  • Jiang-Yu Cui, Zhao-Kai Li, Zhi-Huang Luo, Jian Pan, Qi Yu, Jun Li, Xiao-Dong Yang, Xin-Hua Peng, and Jiang-Feng Du, “Quantum control of nuclear magnetic resonance spin systems,” Wuli Xuebao/Acta Physica Sinica, vol. 64, no. 16, 2015. View at Publisher · View at Google Scholar
  • Wenbin Dong, Rebing Wu, Xiaohu Yuan, Chunwen Li, and Tzyh-Jong Tarn, “The modelling of quantum control systems,” Science Bulletin, 2015. View at Publisher · View at Google Scholar
  • Chang-Chun Ding, Qin-Sheng Zhu, Wei Lai, and Shao-Yi Wu, “Feedback of Non-Markovian Quantum Dynamics in Dimer System: The Effect of Correlated Environments and Temperature,” Communications in Theoretical Physics, vol. 64, no. 6, pp. 676–682, 2015. View at Publisher · View at Google Scholar
  • Tao Xin, Fei-Hao Zhang, Xing-Long Zhen, and Gui-Lu Long, “Experimental demonstration of concatenated composite pulses robustness to non-static errors,” Science China: Physics, Mechanics and Astronomy, vol. 59, no. 9, 2016. View at Publisher · View at Google Scholar
  • Tobias Brandes, and Clive Emary, “Feedback control of waiting times,” Physical Review E, vol. 93, no. 4, 2016. View at Publisher · View at Google Scholar
  • Daoyi Dong, Zhangqing Zhu, Chunlin Chen, Hailan Ma, and Chuan-Cun Shu, “Quantum learning control using differential evolution with equally-mixed strategies,” Control Theory and Technology, vol. 15, no. 3, pp. 226–241, 2017. View at Publisher · View at Google Scholar
  • Moritz August, and Xiaotong Ni, “Using recurrent neural networks to optimize dynamical decoupling for quantum memory,” Physical Review A, vol. 95, no. 1, 2017. View at Publisher · View at Google Scholar