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Stopped and stationary light with cold atomic ensembles and machine learning

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Authors

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

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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.

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Optics InfoBase Conference Papers

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Restricted until

2037-12-31
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