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Record link: 
http://hdl.handle.net/20.500.12708/139100
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Title: 
Optimized observable readout from single-shot images of ultracold atoms via machine learning
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Citation: 
Lode, A. U. J., Lin, R., Büttner, M., Papariello, L., Lévêque, C., Chitra, R., Tsatsos, M. C., Jaksch, D., & Molignini, P. (2021). Optimized observable readout from single-shot images of ultracold atoms via machine learning. Physical Review A, 104(L041301). https://doi.org/10.1103/physreva.104.l041301
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Publisher DOI: 
10.1103/physreva.104.l041301
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Publication Type: 
Article - Original Research Article
en
Authors: 
Lode, Axel U. J. 
Lin, Rui 
Büttner, Miriam 
Papariello, Luca 
Lévêque, Camille 
Chitra, R. 
Tsatsos, Marios C. 
Jaksch, Dieter 
Molignini, Paolo 
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Organisational Unit: 
E141-02 - Forschungsbereich Atom Physics and Quantum Optics 
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Journal: 
Physical Review A 
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ISSN: 
2469-9926
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Date (published): 
2021
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Number of Pages: 
7
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Peer reviewed: 
Yes
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Research Areas: 
Quantum Modelling and Simulation: 100%
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Science Branch: 
Physik, Astronomie
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Appears in Collections:
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