15,179 research outputs found
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
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