Stopped and stationary light with cold atomic ensembles and machine learning

Date

2018

Authors

Buchler, Benjamin
Everett, Jesse
CHO, YOUNG-WOOK
Tranter, Aaron
Slatyer, Harry
Hush, Michael
Paul, Karun
Vernaz-Gris, Pierre
Leung, Anthony
Higginbottom, Daniel

Journal Title

Journal ISSN

Volume Title

Publisher

The Optical Society

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.

Description

Keywords

Citation

Source

Optics InfoBase Conference Papers

Type

Conference paper

Book Title

Entity type

Access Statement

License Rights

DOI

10.1364/CLEO_QELS.2018.FM1G.5

Restricted until

2037-12-31