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Autor:
Jörg Schmiedmayer, Federica Cataldini, Mohammadamin Tajik, Thomas Schweigler, Si-Cong Ji, Frederik Skovbo Møller, Jo{ã}o Sabino
Publikováno v:
Physical Review A. 104
We design a neural network to extract and process features from absorption images taken of one-dimensional Bose gases in the quasi-condensate regime. Specifically, the network is trained to predict both the temperature of single realizations of the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::260ecb0de07e2e376a1c468bd631dadc
https://doi.org/10.1103/physreva.104.043305
https://doi.org/10.1103/physreva.104.043305
