Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme

Wei Zhang; Daoyi Dong; Ian R. Petersen

doi:10.1109/IJCNN.2016.7727709

Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme

Wei Zhang, Daoyi Dong, Ian R. Petersen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

An adaptive target scheme is implemented for learning control of population transfer between subspaces of quantum systems. In this control scheme, the target state is updated according to the renormalized yield in the desired subspace throughout the learning iterations, to obtain the desired laser control field. In the numerical experiments, we perform learning control simulations based on a V-type three-subspace quantum system. The field obtained by learning control can transfer the population to the target subspace with high probability. In comparison with a fixed target state, this adaptive target scheme proves to be more efficient for the quantum control problem under consideration.

Original language	English
Title of host publication	2016 International Joint Conference on Neural Networks, IJCNN 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3930-3934
Number of pages	5
ISBN (Electronic)	9781509006199
DOIs	https://doi.org/10.1109/IJCNN.2016.7727709
Publication status	Published - 31 Oct 2016
Externally published	Yes
Event	2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	2016-October

Conference

Conference	2016 International Joint Conference on Neural Networks, IJCNN 2016
Country/Territory	Canada
City	Vancouver
Period	24/07/16 → 29/07/16

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10.1109/IJCNN.2016.7727709

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Zhang, W., Dong, D., & Petersen, I. R. (2016). Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme. In 2016 International Joint Conference on Neural Networks, IJCNN 2016 (pp. 3930-3934). Article 7727709 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2016-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2016.7727709

Zhang, Wei ; Dong, Daoyi ; Petersen, Ian R. / Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme. 2016 International Joint Conference on Neural Networks, IJCNN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 3930-3934 (Proceedings of the International Joint Conference on Neural Networks).

@inproceedings{310dc066bbdb4439a87a2ccac9c9db49,

title = "Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme",

abstract = "An adaptive target scheme is implemented for learning control of population transfer between subspaces of quantum systems. In this control scheme, the target state is updated according to the renormalized yield in the desired subspace throughout the learning iterations, to obtain the desired laser control field. In the numerical experiments, we perform learning control simulations based on a V-type three-subspace quantum system. The field obtained by learning control can transfer the population to the target subspace with high probability. In comparison with a fixed target state, this adaptive target scheme proves to be more efficient for the quantum control problem under consideration.",

author = "Wei Zhang and Daoyi Dong and Petersen, {Ian R.}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Joint Conference on Neural Networks, IJCNN 2016 ; Conference date: 24-07-2016 Through 29-07-2016",

year = "2016",

month = oct,

day = "31",

doi = "10.1109/IJCNN.2016.7727709",

language = "English",

series = "Proceedings of the International Joint Conference on Neural Networks",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3930--3934",

booktitle = "2016 International Joint Conference on Neural Networks, IJCNN 2016",

address = "United States",

}

Zhang, W, Dong, D & Petersen, IR 2016, Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme. in 2016 International Joint Conference on Neural Networks, IJCNN 2016., 7727709, Proceedings of the International Joint Conference on Neural Networks, vol. 2016-October, Institute of Electrical and Electronics Engineers Inc., pp. 3930-3934, 2016 International Joint Conference on Neural Networks, IJCNN 2016, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/IJCNN.2016.7727709

Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme. / Zhang, Wei; Dong, Daoyi ; Petersen, Ian R.
2016 International Joint Conference on Neural Networks, IJCNN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3930-3934 7727709 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2016-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - An adaptive target scheme is implemented for learning control of population transfer between subspaces of quantum systems. In this control scheme, the target state is updated according to the renormalized yield in the desired subspace throughout the learning iterations, to obtain the desired laser control field. In the numerical experiments, we perform learning control simulations based on a V-type three-subspace quantum system. The field obtained by learning control can transfer the population to the target subspace with high probability. In comparison with a fixed target state, this adaptive target scheme proves to be more efficient for the quantum control problem under consideration.

AB - An adaptive target scheme is implemented for learning control of population transfer between subspaces of quantum systems. In this control scheme, the target state is updated according to the renormalized yield in the desired subspace throughout the learning iterations, to obtain the desired laser control field. In the numerical experiments, we perform learning control simulations based on a V-type three-subspace quantum system. The field obtained by learning control can transfer the population to the target subspace with high probability. In comparison with a fixed target state, this adaptive target scheme proves to be more efficient for the quantum control problem under consideration.

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M3 - Conference contribution

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BT - 2016 International Joint Conference on Neural Networks, IJCNN 2016

PB - Institute of Electrical and Electronics Engineers Inc.

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Zhang W, Dong D , Petersen IR. Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme. In 2016 International Joint Conference on Neural Networks, IJCNN 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3930-3934. 7727709. (Proceedings of the International Joint Conference on Neural Networks). doi: 10.1109/IJCNN.2016.7727709

Learning control of population transfer between subspaces of quantum systems using an adaptive target scheme

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