Quantum learning control using differential evolution with equally-mixed strategies

Learning control has been recognized as a powerful approach in quantum information technology. In this paper, we extend the application of differential evolution （DE） to design optimal control for various quantum systems. Various DE methods are introduced and analyzed, and EMSDE featuring in equally...

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Bibliographic Details
Published in:Control theory and technology 2017-08, Vol.15 (3), p.226-241
Main Authors: Ma, Hailan, Dong, Daoyi, Shu, Chuan-Cun, Zhu, Zhangqing, Chen, Chunlin
Format: Article
Language:English
Subjects:
Complexity
Computational Intelligence
Control
Control and Systems Theory
Control systems
Engineering
Evolutionary design method
Information technology
Learning
Mechatronics
Optimal control
Optimization
Quantum phenomena
Robotics
Superconductivity
System effectiveness
Systems Theory
学习控制
差分进化
开放量子系统
控制问题
最优控制
混合策略
进化理论
量子信息技术
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Summary:Learning control has been recognized as a powerful approach in quantum information technology. In this paper, we extend the application of differential evolution （DE） to design optimal control for various quantum systems. Various DE methods are introduced and analyzed, and EMSDE featuring in equally mixed strategies is employed for quantum control. Two classes of quantum control problems, including control of four-level open quantum ensembles and quantum superconducting systems, are investigated to demonstrate the performance of EMSDE for learning control of quantum systems. Numerical results verify the effectiveness of the FMSDE method for various quantum systems and show the potential for complex quantum control problems.
ISSN:2095-6983
2198-0942
DOI:10.1007/s11768-017-7069-y