Dynamical Josephson Effects in NbSe2_2

The study of superconducting materials that also possess nontrivial correlations or interactions remains an active frontier of condensed matter physics. NbSe$_2$ belongs to this class of superconductors and recent research has focused on the two-dimensional properties of this layered material. Here an investigation of the superconducting-to-normal-state transition in NbSe$_2$ is detailed, and found to be driven by dynamically-created vortices. Under the application of RF radiation, these vortices allow for two novel Josephson effects to be observed. The first is a coupling between Josephson currents and charge density waves in phase-slip junctions. The second is the Josephson detection of multi-band superconductivity, which is revealed in an anomalous magnetic field and RF frequency response of the AC Josephson effect. Our results shed light on the nature of superconductivity in this material, unearthing exotic phenomena by exploiting nonequilibrium superconducting effects in atomically-thin materials

The Recurrent Temporal Discriminative Restricted Boltzmann Machines

Classification of sequence data is the topic of interest for dynamic Bayesian models and Recurrent Neural Networks (RNNs). While the former can explicitly model the temporal dependencies between class variables, the latter have a capability of learning representations. Several attempts have been made to improve performance by combining these two approaches or increasing the processing capability of the hidden units in RNNs. This often results in complex models with a large number of learning parameters. In this paper, a compact model is proposed which offers both representation learning and temporal inference of class variables by rolling Restricted Boltzmann Machines (RBMs) and class variables over time. We address the key issue of intractability in this variant of RBMs by optimising a conditional distribution, instead of a joint distribution. Experiments reported in the paper on melody modelling and optical character recognition show that the proposed model can outperform the state-of-the-art. Also, the experimental results on optical character recognition, part-of-speech tagging and text chunking demonstrate that our model is comparable to recurrent neural networks with complex memory gates while requiring far fewer parameters

Fast acoustic tweezers for the two-dimensional manipulation of individual particles in microfluidic channels

This paper presents a microfluidic device that implements standing surface acoustic waves in order to handle single cells, droplets, and generally particles. The particles are moved in a very controlled manner by the two-dimensional drifting of a standing wave array, using a slight frequency modulation of two ultrasound emitters around their resonance. These acoustic tweezers allow any type of motion at velocities up to few 10mm/s, while the device transparency is adapted for optical studies. The possibility of automation provides a critical step in the development of lab-on-a-chip cell sorters and it should find applications in biology, chemistry, and engineering domains

Fish and fisheries in the Sesan River Basin: catchment baseline, fisheries section

The present report was prepared for the Water and Food Challenge Program project “Optimizing the management of a cascade of reservoirs at the catchment level” (MK3). It constitutes the baseline assessment of fish and fisheries in the Sesan River Basin. The objective of the MK3 project is to contribute knowledge and recommendations so that cascades of reservoirs corresponding to hydropower dams in the Mekong Basin are managed in ways that are more fair and equitable for all water users. This project seeks to understand at the catchment scale the cumulative upstream and downstream consequences of management decisions taken for multiple reservoirs. Revised rules for water storage infrastructure management will in particular take into account fisheries and agricultural potential as well as hydropower ge

Optical analogue of spontaneous symmetry breaking induced by tachyon condensation in amplifying plasmonic arrays

We study analytically and numerically an optical analogue of tachyon condensation in amplifying plasmonic arrays. Optical propagation is modeled through coupled-mode equations, which in the continuous limit can be converted into a nonlinear one-dimensional Dirac-like equation for fermionic particles with imaginary mass, i.e. fermionic tachyons. We demonstrate that the vacuum state is unstable and acquires an expectation value with broken chiral symmetry, corresponding to the homogeneous nonlinear stationary solution of the system. The quantum field theory analogue of this process is the condensation of unstable fermionic tachyons into massive particles. This paves the way for using amplifying plasmonic arrays as a classical laboratory for spontaneous symmetry breaking effects in quantum field theory.Comment: 5 pages, 5 figure