Josephson Oscillation and Transition to Self-Trapping for Bose-Einstein-Condensates in a Triple-Well Trap

We investigate the tunnelling dynamics of Bose-Einstein-Condensates(BECs) in a symmetric as well as in a tilted triple-well trap within the framework of mean-field treatment. The eigenenergies as the functions of the zero-point energy difference between the tilted wells show a striking entangled star structure when the atomic interaction is large. We then achieve insight into the oscillation solutions around the corresponding eigenstates and observe several new types of Josephson oscillations. With increasing the atomic interaction, the Josephson-type oscillation is blocked and the self-trapping solution emerges. The condensates are self-trapped either in one well or in two wells but no scaling-law is observed near transition points. In particular, we find that the transition from the Josephson-type oscillation to the self-trapping is accompanied with some irregular regime where tunnelling dynamics is dominated by chaos. The above analysis is facilitated with the help of the Poicar\'{e} section method that visualizes the motions of BECs in a reduced phase plane.Comment: 10 pages, 11 figure

9-Phenyl-4,5-diaza-9H-fluoren-9-ol monohydrate

The title compound, C17H12N2O·H2O, was synthesized by the reaction of 4,5-diaza­fluoren-9-one with a Grignard reagent in ether (the reaction mixture being hydrolysed with saturated NH4Cl solution), and crystallizes with two organic mol­ecules and two water mol­ecules in the asymmetric unit. The 4,5-diaza­fluorene fragment is approximately planar, with r.m.s. deviations of 0.0448 and 0.0198 Å in the two mol­ecules. The dihedral angles between the 4,5-diaza­fluorene planes and the phenyl ring are 80.49 (6) and 76.57 (7)°. The crystal packing features O—H⋯N and O—H⋯O hydrogen bonds involving the bridging solvent water mol­ecules, which link the mol­ecules into a three-dimensional network

Critical onset in coherent oscillations between two weakly coupled Bose-Einstein condensates

The Josephson effects in two weakly linked Bose-Einstein condensates have been studied recently. In this letter, we study the equations derived by Giovanazzi et. al. [Phys. Rev. Lett. 84, 4521 (2000)] focusing on the effects of the initial acceleration and the velocity of the barrier on the ``dc'' current. We find that the dc current has lifetime which critically depends on the moving velocity of the barrier. Moreover, the influence of the initial acceleration is also investigated and found to be crucial for the experimental realization of the effects.Comment: 4 pages, 4 figure

BOURNE: Bootstrapped Self-supervised Learning Framework for Unified Graph Anomaly Detection

Graph anomaly detection (GAD) has gained increasing attention in recent years due to its critical application in a wide range of domains, such as social networks, financial risk management, and traffic analysis. Existing GAD methods can be categorized into node and edge anomaly detection models based on the type of graph objects being detected. However, these methods typically treat node and edge anomalies as separate tasks, overlooking their associations and frequent co-occurrences in real-world graphs. As a result, they fail to leverage the complementary information provided by node and edge anomalies for mutual detection. Additionally, state-of-the-art GAD methods, such as CoLA and SL-GAD, heavily rely on negative pair sampling in contrastive learning, which incurs high computational costs, hindering their scalability to large graphs. To address these limitations, we propose a novel unified graph anomaly detection framework based on bootstrapped self-supervised learning (named BOURNE). We extract a subgraph (graph view) centered on each target node as node context and transform it into a dual hypergraph (hypergraph view) as edge context. These views are encoded using graph and hypergraph neural networks to capture the representations of nodes, edges, and their associated contexts. By swapping the context embeddings between nodes and edges and measuring the agreement in the embedding space, we enable the mutual detection of node and edge anomalies. Furthermore, we adopt a bootstrapped training strategy that eliminates the need for negative sampling, enabling BOURNE to handle large graphs efficiently. Extensive experiments conducted on six benchmark datasets demonstrate the superior effectiveness and efficiency of BOURNE in detecting both node and edge anomalies

Over-Sampling Strategy in Feature Space for Graphs based Class-imbalanced Bot Detection

The presence of a large number of bots in Online Social Networks (OSN) leads to undesirable social effects. Graph neural networks (GNNs) have achieved state-of-the-art performance in bot detection since they can effectively utilize user interaction. In most scenarios, the distribution of bots and humans is imbalanced, resulting in under-represent minority class samples and sub-optimal performance. However, previous GNN-based methods for bot detection seldom consider the impact of class-imbalanced issues. In this paper, we propose an over-sampling strategy for GNN (OS-GNN) that can mitigate the effect of class imbalance in bot detection. Compared with previous over-sampling methods for GNNs, OS-GNN does not call for edge synthesis, eliminating the noise inevitably introduced during the edge construction. Specifically, node features are first mapped to a feature space through neighborhood aggregation and then generated samples for the minority class in the feature space. Finally, the augmented features are fed into GNNs to train the classifiers. This framework is general and can be easily extended into different GNN architectures. The proposed framework is evaluated using three real-world bot detection benchmark datasets, and it consistently exhibits superiority over the baselines

Euler-Euler LES of bubble column bubbly flows by considering sub-grid scale turbulent dispersion effect on modulating bubble transport

It has now been recognised and generally accepted that turbulent dispersion may be modelled using the time average of the fluctuating part of the interphase momentum, employing the drag the Favre averaged drag model for turbulent dispersion in Eulerian multi-phase flows. As the turbulent eddies in the surrounding of bubbles interact strongly with the bubbles in bubbly flow, the bubble trajectories and bubble oscillation take place accordingly as the consequence of continuous deformation of the bubble surfaces. When using large eddy simulation for modelling bubbly flow, the sub-grid scale (SGS) filtered velocity fluctuations of liquid phase can be interpreted as many small eddies that may act on the surface of bubbles, consequently giving rise to bubble shape variations and the dispersion of bubbles. This study employs Euler/Euler large-eddy simulation (LES) modelling to demonstrate that the turbulent dispersion force model can be used to effectively indicate the influence of turbulent eddies on bubble dynamics, in particular the bubble cluster oscillations, which leads to remarkable improvements in the prediction of bubble lateral dispersion behaviour. The use of spatial filtering to model the SGS bubble dispersion is proposed with a modification on SGS eddy viscosity to reflect turbulent dispersion due to bubble induced turbulence. The results of the time-averaged LES modelled bubble velocities and bubble volume fraction profiles are in good agreement with the experimental data while the turbulent kinetic energy spectrum obtained at different locations on the centreline of the bubble column still exhibits the conventional −5/3 scaling for shear induced turbulence and a −3 scaling for bubble induced turbulence

Study on candidate gene for fecundity traits in Xingjiang Cele black sheep

The aim of the present study is to find a potential candidate gene for high fecundity in Cele black sheep. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technology was used to detect single nuclear polymorphism (SNP) of four candidate genes (BMPR-IB, BMP15, GDF9, and ESRα) in Cele black sheep. The results showed that (i) A-G mutation was found at 746 bp in BMPR-IB in which the frequencies of homozygote (BB), heterozygote (B+) and wild type (++) were 0.113, 0.471, and 0.416, respectively. Significant differences were observed in litter size between ++ and B+ (P < 0.01) and between ++ and BB of individuals (P < 0.05). (ii) C-G mutation was found at exon 1 of ESRα in which the frequencies of homozygote, heterozygote and wild type were 0.047, 0.321 and 0.631, respectively. No significant difference was observed in litter size among the genotypes of ESRα (P > 0.05). (iii) No polymorphism was found in four mutation sites (FecXG, FecXB, FecXI, FecXH) of BMP15 and in one mutation site (FecGH) of GDF9 gene. The results indicate that fecundity characteristic was positively correlated to BMPR-IB. However, there was no relation between fecundity characteristic and detected SNP sites of ESRα, BMP15 and GDF9 genes. These preliminary results showed that the BMPR-IB gene is either a major gene that influences the prolificacy in Cele black sheep or a molecular genetic marker in close linkage with such a gene.Key words: Cele black sheep, fecundity candidate gene, BMPR-IB, BMP15, GDF9, ESRα

Ethyl 2-(4-chloro­phenyl)-3-(3,5-di­fluoro­phenoxy)acrylate

In the title compound, C17H13ClF2O3, a multifunctional aromatic compound, the dihedral angle between the two benzene rings is 51.8 (3)°