Title :
Robust entanglement control between two atoms in a cavity using sampling-based learning control
Author :
Mabrok, Mohamed A. ; Daoyi Dong ; Chunlin Chen ; Petersen, Ian R.
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
Abstract :
In this paper, a sampling-based learning control (SLC) algorithm is used to find a robust control law that can steer a quantum system with uncertainties into a maximally entangled state. The quantum system under consideration consists of two two-level atoms interacting with a quantized electromagnetic field. In the sampling-based learning control method, an artificial system is constructed based on the quantum system with uncertainties and an optimal control law is learned for the artificial system. Some additional samples which are generated by sampling the uncertainty parameters are used to test the performance of the optimal control law. Numerical results demonstrate the effectiveness of the SLC method in finding a robust control law for entanglement generation between two atoms in a cavity in the presence of a quantized field.
Keywords :
atoms; learning systems; optimal control; robust control; sampling methods; uncertain systems; SLC algorithm; artificial system; cavity; optimal control law; quantum system; robust entanglement control; sampling-based learning control; two-level atoms; uncertainty parameters; Atomic clocks; Optimal control; Quantum entanglement; Robust control; Testing; Training; Uncertainty; maximum entanglement; quantum control; sampling-based learning control; uncertainties;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7040297