Extending Gradient Echo Memory Using Machine Learning and Single Photons

Anthony Leung; Aaron Tranter; Karun Paul; Jesse Everett; Pierre Vernaz-Gris; Daniel Higginbottom; Geoff Campbell; Ping Koy Lam; Ben Buchler

Extending Gradient Echo Memory Using Machine Learning and Single Photons

Anthony Leung, Aaron Tranter, Karun Paul, Jesse Everett, Pierre Vernaz-Gris, Daniel Higginbottom, Geoff Campbell, Ping Koy Lam, Ben Buchler

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

1 Citation (Scopus)

Abstract

Gradient echo memory is the most efficient quantum memory protocol to date. Recent additions of machine learning and compatible single photons can raise its performance and the possibility of using it as a quantum gate.

Original language	English
Title of host publication	2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781943580453
Publication status	Published - 2 Jul 2018
Event	2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018 - Wanchai, Hong Kong Duration: 29 Jul 2018 → 3 Aug 2018

Publication series

Name	2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018

Conference

Conference	2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018
Country/Territory	Hong Kong
City	Wanchai
Period	29/07/18 → 3/08/18

Cite this

Leung, A., Tranter, A., Paul, K., Everett, J., Vernaz-Gris, P., Higginbottom, D., Campbell, G., Lam, P. K., & Buchler, B. (2018). Extending Gradient Echo Memory Using Machine Learning and Single Photons. In 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018 Article 8699532 (2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018). Institute of Electrical and Electronics Engineers Inc..

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title = "Extending Gradient Echo Memory Using Machine Learning and Single Photons",

abstract = "Gradient echo memory is the most efficient quantum memory protocol to date. Recent additions of machine learning and compatible single photons can raise its performance and the possibility of using it as a quantum gate.",

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

note = "Publisher Copyright: {\textcopyright} 2018 OSA.; 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018 ; Conference date: 29-07-2018 Through 03-08-2018",

year = "2018",

month = jul,

day = "2",

language = "English",

series = "2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018",

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

booktitle = "2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018",

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Leung, A, Tranter, A, Paul, K, Everett, J, Vernaz-Gris, P, Higginbottom, D, Campbell, G, Lam, PK & Buchler, B 2018, Extending Gradient Echo Memory Using Machine Learning and Single Photons. in 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018., 8699532, 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018, Institute of Electrical and Electronics Engineers Inc., 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018, Wanchai, Hong Kong, 29/07/18.

Extending Gradient Echo Memory Using Machine Learning and Single Photons. / Leung, Anthony; Tranter, Aaron; Paul, Karun et al.
2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8699532 (2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018).

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

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T1 - Extending Gradient Echo Memory Using Machine Learning and Single Photons

AU - Leung, Anthony

AU - Tranter, Aaron

AU - Paul, Karun

AU - Everett, Jesse

AU - Vernaz-Gris, Pierre

AU - Higginbottom, Daniel

AU - Campbell, Geoff

AU - Lam, Ping Koy

AU - Buchler, Ben

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Gradient echo memory is the most efficient quantum memory protocol to date. Recent additions of machine learning and compatible single photons can raise its performance and the possibility of using it as a quantum gate.

AB - Gradient echo memory is the most efficient quantum memory protocol to date. Recent additions of machine learning and compatible single photons can raise its performance and the possibility of using it as a quantum gate.

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M3 - Conference contribution

T3 - 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018

BT - 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018

Y2 - 29 July 2018 through 3 August 2018

ER -

Extending Gradient Echo Memory Using Machine Learning and Single Photons

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