Related papers: Maximizing the capture velocity of molecular magne…
Here, we report the development and working of a compact rubidium (Rb) atom magneto-optical trap (MOT) operated with a hollow pyramidal mirror and a single laser beam. This type of compact MOT is suitable for developing portable atom-optic…
We report studies of photon-stimulated desorption (PSD), also known as light-induced atomic desorption(LIAD), of sodium atoms from a vacuum cell glass surface used for loading a magneto-optical trap (MOT). Fluorescence detection was used to…
The capture of a moving atom by a non-dissipative trap, such as an optical dipole trap, requires the removal of the excessive kinetic energy of the atom. In this article we develop a mechanism to harvest ultra cold atoms from a guided atom…
We report on a scheme for loading dysprosium atoms into a narrow-line three-dimensional magneto-optical trap (3D MOT). Our innovative approach replaces the conventional Zeeman slower with a 2D MOT operating on the broad 421-nm line to…
We exploit red- and blue-detuned magneto optical trapping (MOT) of $^{87}$Rb benefitting from a simplified setup based on liquid crystal variable retarders (LCVR). To maintain the trapping forces when switching from a red- to a blue-detuned…
Bayesian optimization (BO) is a powerful approach for optimizing black-box, expensive-to-evaluate functions. To enable a flexible trade-off between the cost and accuracy, many applications allow the function to be evaluated at different…
One of the consequences of network densification is more frequent handovers (HO). HO failures have a direct impact on the quality of service and are undesirable, especially in scenarios with strict latency, reliability, and robustness…
Multiobject tracking (MOT) is an important task in applications including autonomous driving, ocean sciences, and aerospace surveillance. Traditional MOT methods are model-based and combine sequential Bayesian estimation with data…
We report on the design, implementation, and performance of a compact two-dimensional magneto-optical trap (2D MOT) for cesium. In a small-volume vacuum chamber, the setup uses cesium dispensers in close proximity to the trapping region of…
A hybrid ion-neutral trap provides an ideal system to study collisional dynamics between ions and neutrals. This system provides a general cooling method that can be applied to optically inaccessible species and can also potentially cool…
We demonstrate an efficient scheme for continuous trap loading based upon spatially selective optical pumping. We discuss the case of $^{1}$S$_{0}$ calcium atoms in an optical dipole trap (ODT), however, similar strategies should be…
We study a novel repumping transition for $^{88}$Sr atoms trapped in a 'blue' magneto-optical trap. We show that, while the repumping efficiency is about three orders of magnitude smaller than for traditional schemes, it is sufficient for…
Scanning Tunneling microscopy (STM) is a widely used tool for atomic imaging of novel materials and its surface energetics. However, the optimization of the imaging conditions is a tedious process due to the extremely sensitive tip-surface…
We present a realization of a magneto-optical trap of mercury atoms on the intercombination line. We report on trapping of all stable mercury isotopes. We characterize the effect of laser detuning, laser intensity, and gradient field on the…
We study several new magneto-optical trapping configurations in $^{87}$Rb. These unconventional MOTs all use type-II transitions, where the angular momentum of the ground state is greater than or equal to that of the excited state, and they…
Cross-modal video retrieval aims to retrieve the semantically relevant videos given a text as a query, and is one of the fundamental tasks in Multimedia. Most of top-performing methods primarily leverage Visual Transformer (ViT) to extract…
We report on the first realization of a two-species magneto-optical trap (MOT) for erbium and dysprosium. The MOT operates on an intercombination line for the respective species. Owing to the narrow-line character of such a cooling…
Bayesian optimization (BO) is a class of sample-efficient global optimization methods, where a probabilistic model conditioned on previous observations is used to determine future evaluations via the optimization of an acquisition function.…
Many scientific and industrial applications require the joint optimization of multiple, potentially competing objectives. Multi-objective Bayesian optimization (MOBO) is a sample-efficient framework for identifying Pareto-optimal solutions.…
Bayesian Optimisation has gained much popularity lately, as a global optimisation technique for functions that are expensive to evaluate or unknown a priori. While classical BO focuses on where to gather an observation next, it does not…