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We determine the phase diagram of strongly correlated fermions in thecrossover from Bose-Einstein condensates of molecules (BEC) to Cooper pairs offermions (BCS) utilizing an artificial neural network. By applying advancedimage recognition techniques to the momentum distribution of the fermions, aquantity which has been widely considered as featureless for providinginformation about the condensed state, we measure the critical temperature andshow that it exhibits a maximum on the bosonic side of the crossover.Additionally, we back-analyze the trained neural network and demonstrate thatit interprets physically relevant quantities.

Machine-learning the phase diagram of a strongly-interacting Fermi gas