*In Optics express*

^{87}Rb atoms. The evaporation trajectory was optimized to maximize the number of atoms cooled down to a Bose-Einstein condensate using Bayesian optimization. After 300 trials within 3 hours, Bayesian optimization discovered trajectories that achieved atom numbers comparable with those of manual tuning by a human expert. Analysis of the machine-learned trajectories revealed minimum requirements for successful evaporative cooling. We found that the manually obtained curve and the machine-learned trajectories were quite similar in terms of evaporation efficiency, although the manual and machine-learned evaporation ramps were significantly different.

*Nakamura Ippei, Kanemura Atsunori, Nakaso Takumi, Yamamoto Ryuta, Fukuhara Takeshi*

*2019-Jul-22*