K. S. Hardman

TL;DR: In this article, an online optimization process based on machine learning is applied to the production of Bose-Einstein condensates (BEC), which is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely suboptimal for real experiments.

TL;DR: The solitonic matter wave is found to significantly increase fringe visibility even compared with a noninteracting cloud and across a range of s-wave scattering values including repulsive, attractive and nonInteracting values.

TL;DR: It is demonstrated that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique.

TL;DR: In this paper, a precision gravimeter based on coherent Bragg diffraction of freely falling cold atoms is presented. But it is not suitable for beamforming and subsequent separation of momentum states for detection due to the inherently multi-state nature of atom diffraction.

TL;DR: In this article, the authors demonstrate phase sensitivity in a horizontally guided, acceleration-sensitive atom interferometer with a momentum separation of $80\ensuremath{hbar}k$ between its arms.