High-performance cavity-enhanced quantum memory with warm atomic cell

Lixia Ma, Xing Lei, Jieli Yan, Ruiyang Li, Ting Chai, Zhihui Yan (), Xiaojun Jia (), Changde Xie and Kunchi Peng
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Lixia Ma: Institute of Opto-Electronics, Shanxi University
Xing Lei: Institute of Opto-Electronics, Shanxi University
Jieli Yan: Institute of Opto-Electronics, Shanxi University
Ruiyang Li: Institute of Opto-Electronics, Shanxi University
Ting Chai: Institute of Opto-Electronics, Shanxi University
Zhihui Yan: Institute of Opto-Electronics, Shanxi University
Xiaojun Jia: Institute of Opto-Electronics, Shanxi University
Changde Xie: Institute of Opto-Electronics, Shanxi University
Kunchi Peng: Institute of Opto-Electronics, Shanxi University

Nature Communications, 2022, vol. 13, issue 1, 1-6

Abstract: Abstract High-performance quantum memory for quantized states of light is a prerequisite building block of quantum information technology. Despite great progresses of optical quantum memories based on interactions of light and atoms, physical features of these memories still cannot satisfy requirements for applications in practical quantum information systems, since all of them suffer from trade-off between memory efficiency and excess noise. Here, we report a high-performance cavity-enhanced electromagnetically-induced-transparency memory with warm atomic cell in which a scheme of optimizing the spatial and temporal modes based on the time-reversal approach is applied. The memory efficiency up to 67 ± 1% is directly measured and a noise level close to quantum noise limit is simultaneously reached. It has been experimentally demonstrated that the average fidelities for a set of input coherent states with different phases and amplitudes within a Gaussian distribution have exceeded the classical benchmark fidelities. Thus the realized quantum memory platform has been capable of preserving quantized optical states, and is ready to be applied in quantum information systems, such as distributed quantum logic gates and quantum-enhanced atomic magnetometry.

Date: 2022
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DOI: 10.1038/s41467-022-30077-1

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