Rotating binary Bose-Einstein condensates and vortex clusters in quantum droplets

Quantum droplets may form out of a gaseous Bose-Einstein condensate, stabilized by quantum fluctuations beyond mean field. We show that multiple singly-quantized vortices may form in these droplets at moderate angular momenta in two dimensions. Droplets carrying these precursors of an Abrikosov lattice remain self-bound for certain timescales after switching off an initial harmonic confinement. Furthermore, we examine how these vortex-carrying droplets can be formed in a more pertubation-resistant setting, by starting from a rotating binary Bose-Einstein condensate and inducing a metastable persistent current via a non-monotonic trapping potential.Comment: 5 page, 4 figure

Phase diagram of a rapidly-rotating two-component Bose gas

We derive analytically the phase diagram of a two-component Bose gas confined in an anharmonic potential, which becomes exact and universal in the limit of weak interactions and small anharmonicity of the trapping potential. The transitions between the different phases, which consist of vortex states of single and multiple quantization, are all continuous because of the addition of the second component.Comment: 5 pages, 3 figure

Rotational properties of non-dipolar and dipolar Bose-Einstein condensates confined in annular potentials

We investigate the rotational response of both non-dipolar and dipolar Bose-Einstein condensates confined in an annular potential. For the non-dipolar case we identify certain critical rotational frequencies associated with the formation of vortices. For the dipolar case, assuming that the dipoles are aligned along some arbitrary and tunable direction, we study the same problem as a function of the orientation angle of the dipole moment of the atoms.Comment: 5 pages, 4 figure

An Analysis of Machine Learning-Based Semantic Matchmaking

Interoperability remains to be one of the main challenges in the Internet of Things. The increasing number of IoT data sources from various vendors augments the complexity of integrating different sensors and actuators on the existing platforms, requiring human involvement and becoming error prone. To improve this situation, devices are usually coupled with a semantic description of their attributes. Such semantic descriptions, Things Descriptions, TD, are therefore an abstraction of devices, that is helpful to achieve a smoother integration of devices into IoT platforms. However, TD are usually vendor-based, so for large-scale IoT infrastructures, the integration complexity increases, as there will be different descriptions of similar sensors, provided by different vendors to be interconnected into IoT platforms. In this context, the paper assesses different ML-based semantic matchmaking approaches, against a sentence-based statistical similarity approach. For the ML approaches, the paper focuses on clustering and Natural Language Processing. The three approaches have been implemented on a realistic testbed, and experiments carried out show that the best performance achieved in terms of accuracy, time to completion of a matchmaking request, and memory usage is the NLP-based approach

Finite-size effects in the dynamics of few bosons in a ring potential

We study the temporal evolution of a small number $N$ of ultra-cold bosonic atoms confined in a ring potential. Assuming that initially the system is in a solitary-wave solution of the corresponding mean-field problem, we identify significant differences in the time evolution of the density distribution of the atoms when it instead is evaluated with the many-body Schr\"odinger equation. Three characteristic timescales are derived: the first is the period of rotation of the wave around the ring, the second is associated with a "decay" of the density variation, and the third is associated with periodic "collapses" and "revivals" of the density variations, with a factor of $\sqrt N$ separating each of them. The last two timescales tend to infinity in the appropriate limit of large $N$, in agreement with the mean-field approximation. These findings are based on the assumption of the initial state being a mean-field state. We confirm this behavior by comparison to the exact solutions for a few-body system stirred by an external potential. We find that the exact solutions of the driven system exhibit similar dynamical features.Comment: To appear in Journal of Physics

Spin-orbit-coupled Bose-Einstein-condensed atoms confined in annular potentials

A spin-orbit-coupled Bose-Einstein-condensed cloud of atoms confined in an annular trapping potential shows a variety of phases that we investigate in the present study. Starting with the non-interacting problem, the homogeneous phase that is present in an untrapped system is replaced by a sinusoidal density variation in the limit of a very narrow annulus. In the case of an untrapped system there is another phase with a striped-like density distribution, and its counterpart is also found in the limit of a very narrow annulus. As the width of the annulus increases, this picture persists qualitatively. Depending on the relative strength between the inter- and the intra-components, interactions either favor the striped phase, or suppress it, in which case either a homogeneous, or a sinusoidal-like phase appears. Interactions also give rise to novel solutions with a nonzero circulation.Comment: Final, slightly revised versio

Aerobic Stability and Nutritive Value of Low Dry Matter Maize Silage Treated with a Formic Acid-Based Preservative

Aerobic stability is one of the major problems of the ensiling process, especially in warm climates. Ashbell et al. (2002) have shown that at 30°C, the development of aerobic yeast and moulds in silages is most intensive. In Turkey all silages are susceptible to air penetration during storage and unloading with a large proportion of the silage spoiled and in extreme cases all the silage is spoiled. The purpose of the present work was to study the effects of formic acid-based preservative (FAB; Kemisile® 2000, Kemira Oyj-Industrial Chemicals, Finland) on the aerobic stability and nutritive value of maize silage

Improving the Aerobic Stability of Whole-Crop Cereal Silages

Whole-crop cereal silages, such as wheat, sorghum, and maize are susceptible to aerobic deterioration, especially in warm climates. This is because aerobic yeasts are the most active at 20-30°C (Ashbell et al., 2002). Therefore, it is very important to find suitable additives that inhibit fungi and protect the silage upon aerobic exposure. Propionibacterium acidipropionici is propionic acid bacteria (PAB), which produce propionic and acetic acid in silage. Results with these micro-organisms in laboratory studies were promising with regard to aerobic stability. The purpose of the present work was to study the effects of PAB, lactic acid bacteria (LAB) and combinations of PAB + LAB on the fermentation and aerobic stability of whole-crop cereal silages

Semantic Association Rule Learning from Time Series Data and Knowledge Graphs

Digital Twins (DT) are a promising concept in cyber-physical systems research due to their advanced features including monitoring and automated reasoning. Semantic technologies such as Knowledge Graphs (KG) are recently being utilized in DTs especially for information modelling. Building on this move, this paper proposes a pipeline for semantic association rule learning in DTs using KGs and time series data. In addition to this initial pipeline, we also propose new semantic association rule criterion. The approach is evaluated on an industrial water network scenario. Initial evaluation shows that the proposed approach is able to learn a high number of association rules with semantic information whichare more generalizable. The paper aims to set a foundation for further work on using semantic association rule learning especially in the context of industrial applications