Statistical Properties of Interacting Bose Gases in Quasi-2D Harmonic Traps

The analytical probability distribution of the quasi-2D (and purely 2D) ideal and interacting Bose gas are investigated by using a canonical ensemble approach. Using the analytical probability distribution of the condensate, the statistical properties such as the mean occupation number and particle number fluctuations of the condensate are calculated. Researches show that there is a continuous crossover of the statistical properties from a quasi-2D to a purely 2D ideal or interacting gases. Different from the case of a 3D Bose gas, the interaction between atoms changes in a deep way the nature of the particle number fluctuations.Comment: RevTex, 10pages, 4 figures, E-mail: [email protected]

The Microsoft 2017 Conversational Speech Recognition System

We describe the 2017 version of Microsoft's conversational speech recognition system, in which we update our 2016 system with recent developments in neural-network-based acoustic and language modeling to further advance the state of the art on the Switchboard speech recognition task. The system adds a CNN-BLSTM acoustic model to the set of model architectures we combined previously, and includes character-based and dialog session aware LSTM language models in rescoring. For system combination we adopt a two-stage approach, whereby subsets of acoustic models are first combined at the senone/frame level, followed by a word-level voting via confusion networks. We also added a confusion network rescoring step after system combination. The resulting system yields a 5.1\% word error rate on the 2000 Switchboard evaluation set

Collective spin waves in arrays of Permalloy nanowires with single-side periodically modulated width

We have experimentally and numerically investigated the dispersion of collective spin waves prop-agating through arrays of longitudinally magnetized nanowires with periodically modulated width. Two nanowire arrays with single-side modulation and different periodicity of modulation were studied and compared to the nanowires with homogeneous width. The spin-wave dispersion, meas-ured up to the third Brillouin zone of the reciprocal space, revealed the presence of two dispersive modes for the width-modulated NWs, whose amplitude of magnonic band depends on the modula-tion periodicity, and a set of nondispersive modes at higher frequency. These findings are different from those observed in homogeneous width NWs where only the lowest mode exhibits sizeable dis-persion. The measured spin-wave dispersion has been satisfactorily reproduced by means of dynam-ical matrix method. Results presented in this work are important in view of the possible realization of frequency tunable magnonic device

Entropy, Dynamics and Instantaneous Normal Modes in a Random Energy Model

It is shown that the fraction f of imaginary frequency instantaneous normal modes (INM) may be defined and calculated in a random energy model(REM) of liquids. The configurational entropy S and the averaged hopping rate among the states R are also obtained and related to f, with the results R~f and S=a+b*ln(f). The proportionality between R and f is the basis of existing INM theories of diffusion, so the REM further confirms their validity. A link to S opens new avenues for introducing INM into dynamical theories. Liquid 'states' are usually defined by assigning a configuration to the minimum to which it will drain, but the REM naturally treats saddle-barriers on the same footing as minima, which may be a better mapping of the continuum of configurations to discrete states. Requirements of a detailed REM description of liquids are discussed

A Hessenberg Markov chain for fast fibre delay line length optimization

In this paper we present an approach to compute the invariant vector of the N + 1 state Markov chain P presented in (Rogiest et al., Lecture Notes in Computer Science, NET-COOP 2007 Special Issue, pp. 4465:185-194) to determine the loss rate of an FDL buffer consisting of N lines, by solving a related Hessenberg system (i.e., a Markov chain skip-free in one direction). This system is obtained by inserting additional time instants in the sample paths of P and allows us to compute the loss rate for various FDL lengths by solving a single system. This is shown to be especially effective in reducing the computation time of the heuristic LRA algorithm presented in (Lambert et al., Proc. NAEC 2005, pp. 545-555) to optimize the FDL lengths, where improvements of several orders of magnitude can be realized

The Microsoft 2016 Conversational Speech Recognition System

We describe Microsoft's conversational speech recognition system, in which we combine recent developments in neural-network-based acoustic and language modeling to advance the state of the art on the Switchboard recognition task. Inspired by machine learning ensemble techniques, the system uses a range of convolutional and recurrent neural networks. I-vector modeling and lattice-free MMI training provide significant gains for all acoustic model architectures. Language model rescoring with multiple forward and backward running RNNLMs, and word posterior-based system combination provide a 20% boost. The best single system uses a ResNet architecture acoustic model with RNNLM rescoring, and achieves a word error rate of 6.9% on the NIST 2000 Switchboard task. The combined system has an error rate of 6.2%, representing an improvement over previously reported results on this benchmark task

Measurement of the spin polarization of the magnetic semiconductor EuS with zero-field and Zeeman-split Andreev reflection spectroscopy

We report measurements of the spin polarization (\textbf{\textit{P}}) of the concentrated magnetic semiconductor EuS using both zero-field and Zeeman-split Andreev reflection spectroscopy (ARS) with EuS/Al planar junctions. The zero-field ARS spectra are well described by the modified (spin-polarized) BTK model with expected superconducting energy gap and actual measurement temperature (no additional spectral broadening). The fittings consistently yield \textbf{\textit{P}} close to 80% regardless of the barrier strength. Moreover, we performed ARS in the presence of a Zeeman-splitting of the quasiparticle density of states in Al. To describe the Zeeman-split ARS spectra, we develop a theoretical model which incorporates the solution to the Maki-Fulde equations into the modified BTK analysis. The method enables the determination of the magnitude as well as the sign of \textbf{\textit{P}} with ARS, and the results are consistent with those from the zero-field ARS. The experiments extend the utility of field-split superconducting spectroscopy from tunnel junctions to Andreev junctions of arbitrary barrier strengths.Comment: 6 pages, 4 figure