Stopped and stationary light with cold atomic ensembles and machine learning

Ben Buchler; Jesse Everett; Young Wook Cho; Aaron Tranter; Harry Slatyer; Michael Hush; Karun Paul; Pierre Vernaz-Gris; Anthony Leung; Daniel Higginbottom; Ping Koy Lam; Geoff Campbell

Stopped and stationary light with cold atomic ensembles and machine learning

Ben Buchler, Jesse Everett, Young Wook Cho, Aaron Tranter, Harry Slatyer, Michael Hush, Karun Paul, Pierre Vernaz-Gris, Anthony Leung, Daniel Higginbottom, Ping Koy Lam, Geoff Campbell

Department of Physics

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

Abstract

Quantum information systems demand methods for the storage and manipulation of qubits. For optical qubits, atomic ensembles provide a potential platform for such operations. In this work, we demonstrate a stopped light optical quantum memory with efficiency up to 87%. We also demonstrate and visualise stationary light, which could potentially enhance weak optical nonlinearities. At the heart of our experiments is a laser-cooled atomic ensemble, which has recently been optimised with the help of a machine learning system that uses an artificial neural network.

Original language	English
Title of host publication	2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781943580422
Publication status	Published - 2018 Aug 6
Event	2018 Conference on Lasers and Electro-Optics, CLEO 2018 - San Jose, United States Duration: 2018 May 13 → 2018 May 18

Publication series

Name	2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings

Other

Other	2018 Conference on Lasers and Electro-Optics, CLEO 2018
Country/Territory	United States
City	San Jose
Period	18/5/13 → 18/5/18

Bibliographical note

Publisher Copyright:
© 2018 OSA.

All Science Journal Classification (ASJC) codes

Instrumentation
Atomic and Molecular Physics, and Optics

Cite this

Buchler, B., Everett, J., Cho, Y. W., Tranter, A., Slatyer, H., Hush, M., Paul, K., Vernaz-Gris, P., Leung, A., Higginbottom, D., Lam, P. K., & Campbell, G. (2018). Stopped and stationary light with cold atomic ensembles and machine learning. In 2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings [8426522] (2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc..

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title = "Stopped and stationary light with cold atomic ensembles and machine learning",

abstract = "Quantum information systems demand methods for the storage and manipulation of qubits. For optical qubits, atomic ensembles provide a potential platform for such operations. In this work, we demonstrate a stopped light optical quantum memory with efficiency up to 87%. We also demonstrate and visualise stationary light, which could potentially enhance weak optical nonlinearities. At the heart of our experiments is a laser-cooled atomic ensemble, which has recently been optimised with the help of a machine learning system that uses an artificial neural network.",

author = "Ben Buchler and Jesse Everett and Cho, {Young Wook} and Aaron Tranter and Harry Slatyer and Michael Hush and Karun Paul and Pierre Vernaz-Gris and Anthony Leung and Daniel Higginbottom and Lam, {Ping Koy} and Geoff Campbell",

note = "Publisher Copyright: {\textcopyright} 2018 OSA.; 2018 Conference on Lasers and Electro-Optics, CLEO 2018 ; Conference date: 13-05-2018 Through 18-05-2018",

year = "2018",

month = aug,

day = "6",

language = "English",

isbn = "9781943580422",

series = "2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings",

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Buchler, B, Everett, J, Cho, YW, Tranter, A, Slatyer, H, Hush, M, Paul, K, Vernaz-Gris, P, Leung, A, Higginbottom, D, Lam, PK & Campbell, G 2018, Stopped and stationary light with cold atomic ensembles and machine learning. in 2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings., 8426522, 2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2018 Conference on Lasers and Electro-Optics, CLEO 2018, San Jose, United States, 18/5/13.

Stopped and stationary light with cold atomic ensembles and machine learning. / Buchler, Ben; Everett, Jesse; Cho, Young Wook et al.

2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8426522 (2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings).

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

TY - GEN

T1 - Stopped and stationary light with cold atomic ensembles and machine learning

AU - Buchler, Ben

AU - Everett, Jesse

AU - Cho, Young Wook

AU - Tranter, Aaron

AU - Slatyer, Harry

AU - Hush, Michael

AU - Paul, Karun

AU - Vernaz-Gris, Pierre

AU - Leung, Anthony

AU - Higginbottom, Daniel

AU - Lam, Ping Koy

AU - Campbell, Geoff

PY - 2018/8/6

Y1 - 2018/8/6

N2 - Quantum information systems demand methods for the storage and manipulation of qubits. For optical qubits, atomic ensembles provide a potential platform for such operations. In this work, we demonstrate a stopped light optical quantum memory with efficiency up to 87%. We also demonstrate and visualise stationary light, which could potentially enhance weak optical nonlinearities. At the heart of our experiments is a laser-cooled atomic ensemble, which has recently been optimised with the help of a machine learning system that uses an artificial neural network.

AB - Quantum information systems demand methods for the storage and manipulation of qubits. For optical qubits, atomic ensembles provide a potential platform for such operations. In this work, we demonstrate a stopped light optical quantum memory with efficiency up to 87%. We also demonstrate and visualise stationary light, which could potentially enhance weak optical nonlinearities. At the heart of our experiments is a laser-cooled atomic ensemble, which has recently been optimised with the help of a machine learning system that uses an artificial neural network.

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M3 - Conference contribution

AN - SCOPUS:85052566889

SN - 9781943580422

T3 - 2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings

BT - 2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 Conference on Lasers and Electro-Optics, CLEO 2018

Y2 - 13 May 2018 through 18 May 2018

ER -

Stopped and stationary light with cold atomic ensembles and machine learning

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