Approaching the adiabatic timescale with machine-learning

The control and manipulation of quantum systems without excitation is challenging, due to the complexities in fully modeling such systems accurately and the difficulties in controlling these inherently fragile systems experimentally. For example, while protocols to decompress Bose-Einstein condensates (BEC) faster than the adiabatic timescale (without excitation or loss) have been well developed theoretically, experimental implementations of these protocols have yet to reach speeds faster than the adiabatic timescale. In this work, we experimentally demonstrate an alternative approach based on a machine learning algorithm which makes progress towards this goal. The algorithm is given control of the coupled decompression and transport of a metastable helium condensate, with its performance determined after each experimental iteration by measuring the excitations of the resultant BEC. After each iteration the algorithm adjusts its internal model of the system to create an improved control output for the next iteration. Given sufficient control over the decompression, the algorithm converges to a novel solution that sets the current speed record in relation to the adiabatic timescale, beating out other experimental realizations based on theoretical approaches. This method presents a feasible approach for implementing fast state preparations or transformations in other quantum systems, without requiring a solution to a theoretical model of the system. Implications for fundamental physics and cooling are discussed.Comment: 7 pages main text, 2 pages supporting informatio

Production of a highly degenerate Fermi gas of metastable helium-3 atoms

We report on the achievement of quantum degeneracy in both components of a Bose-Fermi mixture of metastable helium atoms, $^4$He* and $^3$He*. Degeneracy is achieved via Doppler cooling and forced evaporation for $^4$He*, and sympathetically cooling $^3$He* with $^4$He*. We discuss our simplified implementation, along with the high versatility of our system. This technique is able to produce a degenerate Fermi gas with a minimum reduced temperature of $T/T_F=0.14(1)$, consisting of $2.5 \times 10^4$ $^3$He* atoms. Due to the high internal energy of both isotopes single atom detection is possible, opening the possibility of a large number of experiments into Bose-Fermi mixtures.Comment: 13 pages, 8 figure

Recreating the OSIRIS-REx Slingshot Manoeuvre from a Network of Ground-Based Sensors

Optical tracking systems typically trade-off between astrometric precision and field-of-view. In this work, we showcase a networked approach to optical tracking using very wide field-of-view imagers that have relatively low astrometric precision on the scheduled OSIRIS-REx slingshot manoeuvre around Earth on September 22nd, 2017. As part of a trajectory designed to get OSIRIS-REx to NEO 101955 Bennu, this flyby event was viewed from 13 remote sensors spread across Australia and New Zealand to promote triangulatable observations. Each observatory in this portable network was constructed to be as lightweight and portable as possible, with hardware based off the successful design of the Desert Fireball Network. Over a 4 hour collection window, we gathered 15,439 images of the night sky in the predicted direction of the OSIRIS-REx spacecraft. Using a specially developed streak detection and orbit determination data pipeline, we detected 2,090 line-of-sight observations. Our fitted orbit was determined to be within about 10~km of orbital telemetry along the observed 109,262~km length of OSIRIS-REx trajectory, and thus demonstrating the impressive capability of a networked approach to SSA

A matter-wave Rarity–Tapster interferometer to demonstrate non-locality

We present an experimentally viable approach to demonstrate quantum non-locality in a matter-wave system via a Rarity–Tapster interferometer using two $$s$$-wave scattering halos generated by colliding helium Bose–Einstein condensates. The theoretical basis for this method is discussed, and its suitability is experimentally quantified. As a proof of concept, we demonstrate an interferometric visibility of $$V=0.42(9)$$, corresponding to a maximum CSHS-Bell parameter of $$S=1.1(1)$$, for the Clauser–Horne–Shimony–Holt (CHSH) version of the Bell inequality, between atoms separated by $$\sim 4$$ correlation lengths. This constitutes a significant step toward a demonstration of a Bell inequality violation for motional degrees of freedom of massive particles and possible measurements of quantum effects in a gravitationally sensitive system

Recreating the OSIRIS-REx slingshot manoeuvre from a network of ground-based sensors

Optical tracking systems typically trade off between astrometric precision and field of view. In this work, we showcase a networked approach to optical tracking using very wide field-of-view imagers that have relatively low astrometric precision on the scheduled OSIRIS-REx slingshot manoeuvre around Earth on 22 Sep 2017. As part of a trajectory designed to get OSIRIS-REx to NEO 101955 Bennu, this flyby event was viewed from 13 remote sensors spread across Australia and New Zealand to promote triangulatable observations. Each observatory in this portable network was constructed to be as lightweight and portable as possible, with hardware based off the successful design of the Desert Fireball Network. Over a 4-h collection window, we gathered 15 439 images of the night sky in the predicted direction of the OSIRIS-REx spacecraft. Using a specially developed streak detection and orbit determination data pipeline, we detected 2 090 line-of-sight observations. Our fitted orbit was determined to be within about 10 km of orbital telemetry along the observed 109 262 km length of OSIRIS-REx trajectory, and thus demonstrating the impressive capability of a networked approach to Space Surveillance and Tracking.This work was funded by the Australian Research Council as part of the Australian Discovery Project scheme, with funding from the Australian Government and the Government of Western Australia. This work was also supported by an Australian Government Research Training Program (RTP) Scholarship. This research made use of Astropy, a communitydeveloped core Python package for Astronomy (The Astropy Collaboration et al. 2013). Some figures in this work were generated using Matplotlib, another community-developed Python package (Hunter 2007)