Robust entanglement control between two atoms in a cavity using sampling-based learning control

Mohamed A. Mabrok, Daoyi Dong, Chunlin Chen, Ian R. Petersen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publication53rd IEEE Conference on Decision and Control,CDC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5802-5807
Number of pages6
EditionFebruary
ISBN (Electronic)9781479977468
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States
Duration: 15 Dec 201417 Dec 2014

Publication series

NameProceedings of the IEEE Conference on Decision and Control
NumberFebruary
Volume2015-February
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Country/TerritoryUnited States
CityLos Angeles
Period15/12/1417/12/14

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