7,706 research outputs found
Formation of Topological Defects with Explicit Symmetry Breaking
We demonstrate a novel mechanism for the formation of topological defects in
a first order phase transition for theories in the presence of small explicit
symmetry breaking terms. We carry out numerical simulations of collisions of
two bubbles in 2+1 dimensions for a field theory where U(1) global symmetry is
spontaneously as well as explicitly broken. In the coalesced region of bubble
walls, field oscillations result in the decay of the coalesced portion in a
large number of defects (e.g. ten vortices and anti-vortices). We discuss the
implications of our results for axionic strings in the early Universe, for
baryon formation in quark-gluon plasma, and for electric or magnetic field.Comment: Latex file, 8 pages, 6 uuencoded postscript figure
Analysis of generalized negative binomial distributions attached to hyperbolic Landau levels
To each hyperbolic Landau level of the Poincar\'e disc is attached a
generalized negative binomial distribution. In this paper, we compute the
moment generating function of this distribution and supply its decomposition as
a perturbation of the negative binomial distribution by a finitely-supported
measure. Using the Mandel parameter, we also discuss the nonclassical nature of
the associated coherent states. Next, we determine the L\'evy-Kintchine
decomposition its characteristic function when the latter does not vanish and
deduce that it is quasi-infinitely divisible except for the lowest hyperbolic
Landau level corresponding to the negative binomial distribution. By
considering the total variation of the obtained quasi-L\'evy measure, we
introduce a new infinitely-divisible distribution for which we derive the
characteristic function
Resonant Production of Topological Defects
We describe a novel phenomenon in which vortices are produced due to resonant
oscillations of a scalar field which is driven by a periodically varying
temperature T, with T remaining much below the critical temperature .
Also, in a rapid heating of a localized region to a temperature {\it below}
, far separated vortex and antivortex can form. We compare our results
with recent models of defect production during reheating after inflation. We
also discuss possible experimental tests of our predictions of topological
defect production {\it without} ever going through a phase transition.Comment: Revtex, 13 pages including 5 postscript figure
On viscous flow and azimuthal anisotropy of quark-gluon plasma in strong magnetic field
We calculate the viscous pressure tensor of the quark-gluon plasma in strong
magnetic field. It is azimuthally anisotropic and is characterized by five
shear viscosity coefficients, four of which vanish when the field strength eB
is much larger than the plasma temperature squared. We argue, that the
azimuthally anisotropic viscous pressure tensor generates the transverse flow
with asymmetry as large as 1/3, even not taking into account the collision
geometry. We conclude, that the magnitude of the shear viscosity extracted from
the experimental data ignoring the magnetic field must be underestimated.Comment: 10 page
P05-10. Sequential Immunization with a Subtype B HIV-1 Envelope Quasispecies Elicits Broader Neutralization than Vaccination with a Single Envelope Clone
Large scale shell model calculations for odd-odd Mn isotopes
Large scale shell model calculations have been carried out for odd-odd
Mn isotopes in two different model spaces. First set of calculations
have been carried out in full shell valence space with two recently
derived shell interactions namely GXPF1A and KB3G treating Ca
as core. The second set of calculations have been performed in
valence space with the interaction treating Ca as core and
imposing a truncation by allowing up to a total of six particle excitations
from the 0f orbital to the upper orbitals for protons and
from the upper orbitals to the 0g orbital for neutron. For
low-lying states in Mn, the KB3G and GXPF1A both predicts good results
and for Mn, KB3G is much better than GXPF1A. For negative parity and
high-spin positive parity states in both isotopes interaction is
required. Experimental data on Mn is sparse and therefore it is not
possible to make any definite conclusions. More experimental data on negative
parity states is needed to ascertain the importance of 0g and higher
orbitals in neutron rich Mn isotopes.Comment: 5 pages, 4 figures, Submitted to Eur. Phys. J.
The WiFeS S7 AGN survey: Current status and recent results on NGC 6300
The Siding Spring Southern Seyfert Spectroscopic Snapshot Survey (S7) is a
targeted survey probing the narrow-line regions (NLRs) of a representative
sample of ~140 nearby (z<0.02) Seyfert galaxies by means of optical integral
field spectroscopy. The survey is based on a homogeneous data set observed
using the Wide Field Spectrograph WiFeS. The data provide a 25x38 arcsec
field-of-view around the galaxy centre at typically ~1.5 arcsec spatial
resolution and cover a wavelength range between ~3400 - 7100 at spectral
resolutions of ~100 km s and ~50 km s in the blue and red parts,
respectively. The survey is primarily designed to study gas excitation and star
formation around AGN, with a special focus on the shape of the AGN ionising
continuum, the interaction between radio jets and the NLR gas, and the nature
of nuclear LINER emission. We provide an overview of the current status of
S7-based results and present new results for NGC 6300.Comment: 5 pages, 1 figure, Refereed Proceeding of the "The Universe of
Digital Sky Surveys" conference held at the INAF - Observatory of
Capodimonte, Naples, on 25th-28th november 2014, to be published on
Astrophysics and Space Science Proceedings, edited by Longo, Napolitano,
Marconi, Paolillo, Iodic
A two‐stage Bayesian network model for corporate bankruptcy prediction
We develop a Bayesian network (LASSO-BN) model for firm bankruptcy prediction. We select fnancial ratios via the Least Absolute Shrinkage Selection Operator (LASSO), establish the BN topology, and estimate model parameters. Our empirical results, based on 32,344 US firms from 1961-2018, show that the LASSO-BN model outperforms most alternative methods except the deep neural network. Crucially, the model provides a clear interpretation of its internal functionality by describing the logic of how conditional default probabilities are obtained from selected variables. Thus our model represents a major step towards interpretable machine learning models with strong performance and is relevant to investors and policymakers
Neural Networks for Information Retrieval
Machine learning plays a role in many aspects of modern IR systems, and deep
learning is applied in all of them. The fast pace of modern-day research has
given rise to many different approaches for many different IR problems. The
amount of information available can be overwhelming both for junior students
and for experienced researchers looking for new research topics and directions.
Additionally, it is interesting to see what key insights into IR problems the
new technologies are able to give us. The aim of this full-day tutorial is to
give a clear overview of current tried-and-trusted neural methods in IR and how
they benefit IR research. It covers key architectures, as well as the most
promising future directions.Comment: Overview of full-day tutorial at SIGIR 201
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