3,398 research outputs found
Observation of polarization domain wall solitons in weakly birefringent cavity fiber lasers
We report on the experimental observation of two types of phase-locked vector
soliton in weakly birefringent cavity erbium-doped fiber lasers. While a
phase-locked dark-dark vector soliton was only observed in fiber lasers of
positive dispersion, a phase-locked dark-bright vector soliton was obtained in
fiber lasers of either positive or negative dispersion. Numerical simulations
confirmed the experimental observations, and further showed that the observed
vector solitons are the two types of phase-locked polarization domain-wall
solitons theoretically predicted.Comment: 14 pages, 4 Figure
Tests of Bayesian Model Selection Techniques for Gravitational Wave Astronomy
The analysis of gravitational wave data involves many model selection
problems. The most important example is the detection problem of selecting
between the data being consistent with instrument noise alone, or instrument
noise and a gravitational wave signal. The analysis of data from ground based
gravitational wave detectors is mostly conducted using classical statistics,
and methods such as the Neyman-Pearson criteria are used for model selection.
Future space based detectors, such as the \emph{Laser Interferometer Space
Antenna} (LISA), are expected to produced rich data streams containing the
signals from many millions of sources. Determining the number of sources that
are resolvable, and the most appropriate description of each source poses a
challenging model selection problem that may best be addressed in a Bayesian
framework. An important class of LISA sources are the millions of low-mass
binary systems within our own galaxy, tens of thousands of which will be
detectable. Not only are the number of sources unknown, but so are the number
of parameters required to model the waveforms. For example, a significant
subset of the resolvable galactic binaries will exhibit orbital frequency
evolution, while a smaller number will have measurable eccentricity. In the
Bayesian approach to model selection one needs to compute the Bayes factor
between competing models. Here we explore various methods for computing Bayes
factors in the context of determining which galactic binaries have measurable
frequency evolution. The methods explored include a Reverse Jump Markov Chain
Monte Carlo (RJMCMC) algorithm, Savage-Dickie density ratios, the Schwarz-Bayes
Information Criterion (BIC), and the Laplace approximation to the model
evidence. We find good agreement between all of the approaches.Comment: 11 pages, 6 figure
Detection of OH absorption against PSR B1849+00
We have searched for OH absorption against seven pulsars using the Arecibo
telescope. In both OH mainlines (at 1665 and 1667 MHz), deep and narrow
absorption features were detected toward PSR B1849+00. In addition, we have
detected several absorption and emission features against B33.6+0.1, a nearby
supernova remnant (SNR). The most interesting result of this study is that a
pencil-sharp absorption sample against the PSR differs greatly from the
large-angle absorption sample observed against the SNR. If both the PSR and the
SNR probe the same molecular cloud then this finding has important implications
for absorption studies of the molecular medium, as it shows that the statistics
of absorbing OH depends on the size of the background source. We also show that
the OH absorption against the PSR most likely originates from a small (<30
arcsec) and dense (>10^5 cm^-3) molecular clump.Comment: 12 pages, 8 figures. Accepted for publication in Ap
Dressing Technique for Intermediate Hierarchies
A generalized AKNS systems introduced and discussed recently in \cite{dGHM}
are considered. It was shown that the dressing technique both in matrix
pseudo-differential operators and formal series with respect to the spectral
parameter can be developed for these hierarchies.Comment: 16 pages, LaTeX Report/no: DFTUZ/94/2
Satellite Evidence of Hurricane-Induced Phytoplankton Blooms in an Oceanic Desert
The physical effects of hurricanes include deepening of the mixed layer and decreasing of the sea surface temperature in response to entrainment, curl-induced upwelling, and increased upper ocean cooling. However, the biological effects of hurricanes remain relatively unexplored. In this paper, we examine the passages of 13 hurricanes through the Sargasso Sea region of the North Atlantic during the years 1998 through 2001. Remotely sensed ocean color shows increased concentrations of surface chlorophyll within the cool wakes of the hurricanes, apparently in response to the injection of nutrients and/or biogenic pigments into the oligotrophic surface waters. This increase in post-storm surface chlorophyll concentration usually lasted 2-3 weeks before it returned to its nominal pre-hurricane level
“Doctor my eyes” : A natural experiment on the demand for eye care services
This paper is dedicated to our friend Divine Ikenwilo, who passed away on the 27th November 2015. Divine was a gifted researcher who was taken from us too early and will be sorely missed by everyone in the team. Our thoughts are with his family. This research was funded by a research grant (CGZ/2/533) from the Chief Scientist Office of the Scottish Government. The Health Economics Research Unit is funded by the Scottish Government Health and Social Care Directorate. The usual disclaimer applies.Peer reviewedPostprin
Dispersionful analogues of Benney's equations and -wave systems
We recall Krichever's construction of additional flows to Benney's hierarchy,
attached to poles at finite distance of the Lax operator. Then we construct a
``dispersionful'' analogue of this hierarchy, in which the role of poles at
finite distance is played by Miura fields. We connect this hierarchy with
-wave systems, and prove several facts about the latter (Lax representation,
Chern-Simons-type Lagrangian, connection with Liouville equation,
-functions).Comment: 12 pages, latex, no figure
Neural Networks for Time Series Forecasting: Practical Implications of Theoretical Results
Research on the performance of neural networks in modeling nonlinear time series has produced mixed results. While neural networks have great potential because of their status as universal approximators When Faraway and Chatfield (1998) used an autoregressive neural network to forecast airline data, they found that the neural networks they specified frequently would not converge. When they did converge, they failed to find the global minimum of the objective function. In some cases, neural networks that fit the in-sample data well performed poorly on holdout samples. In conducting the NN3 competition, a time series forecasting competition designed to showcase autoregressive neural networks and other computationally-intensive methods of forecasting, standard methods such as ARIMA models still out-performed autoregressive neural networks (Crone et
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