A CNN trained on simulated absorption images estimates Gaussian cold-atom cloud parameters as accurately as least-squares fitting, about 80 times faster, and from a single exposure.
Badurinaet al., Journal of Cosmology and Astropar- ticle Physics2020(05), 011
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Deep Learning for Absorption-Image Analysis
A CNN trained on simulated absorption images estimates Gaussian cold-atom cloud parameters as accurately as least-squares fitting, about 80 times faster, and from a single exposure.