49,103 research outputs found
The formation of spiral arms and rings in barred galaxies
In this and in a previous paper (Romero-Gomez et al. 2006) we propose a
theory to explain the formation of both spirals and rings in barred galaxies
using a common dynamical framework. It is based on the orbital motion driven by
the unstable equilibrium points of the rotating bar potential. Thus, spirals,
rings and pseudo-rings are related to the invariant manifolds associated to the
periodic orbits around these equilibrium points. We examine the parameter space
of three barred galaxy models and discuss the formation of the different
morphological structures according to the properties of the bar model. We also
study the influence of the shape of the rotation curve in the outer parts, by
making families of models with rising, flat, or falling rotation curves in the
outer parts. The differences between spiral and ringed structures arise from
differences in the dynamical parameters of the host galaxies. The results
presented here will be discussed and compared with observations in a
forthcoming paper.Comment: 16 pages, 13 figures, accepted in A&A. High resolution version
available at http://www.oamp.fr/dynamique/pap/merce.htm
Perturbative evolution of far off-resonance driven two-level systems: Coherent population trapping, localization, and harmonic generation
The time evolution of driven two-level systems in the far off-resonance
regime is studied analytically. We obtain a general first-order perturbative
expression for the time-dependent density operator which is applicable
regardless of the coupling strength value. In the strong field regime, our
perturbative expansion remains valid even when the far off-resonance condition
is not fulfilled. We find that, in the absence of dissipation, driven two-level
systems exhibit coherent population trapping in a certain region of parameter
space, a property which, in the particular case of a symmetric double-well
potential, implies the well-known localization of the system in one of the two
wells. Finally, we show how the high-order harmonic generation that this kind
of systems display can be obtained as a straightforward application of our
formulation.Comment: 14 pages, LaTeX, 2 figures, acknowledgments adde
Gamma-ray signatures of classical novae
The role of classical novae as potential gamma-ray emitters is reviewed, on
the basis of theoretical models of the gamma-ray emission from different nova
types. The interpretation of the up to now negative results of the gamma-ray
observations of novae, as well as the prospects for detectability with future
instruments (specially onboard INTEGRAL) are also discussed.Comment: 10 pages, 7 figures. Invited talk at the "Gamma 2001" Symposium,
April 4-6, 2001, Baltimore, Maryland. To be published by AI
Truncating the loop series expansion for Belief Propagation
Recently, M. Chertkov and V.Y. Chernyak derived an exact expression for the
partition sum (normalization constant) corresponding to a graphical model,
which is an expansion around the Belief Propagation solution. By adding
correction terms to the BP free energy, one for each "generalized loop" in the
factor graph, the exact partition sum is obtained. However, the usually
enormous number of generalized loops generally prohibits summation over all
correction terms. In this article we introduce Truncated Loop Series BP
(TLSBP), a particular way of truncating the loop series of M. Chertkov and V.Y.
Chernyak by considering generalized loops as compositions of simple loops. We
analyze the performance of TLSBP in different scenarios, including the Ising
model, regular random graphs and on Promedas, a large probabilistic medical
diagnostic system. We show that TLSBP often improves upon the accuracy of the
BP solution, at the expense of increased computation time. We also show that
the performance of TLSBP strongly depends on the degree of interaction between
the variables. For weak interactions, truncating the series leads to
significant improvements, whereas for strong interactions it can be
ineffective, even if a high number of terms is considered.Comment: 31 pages, 12 figures, submitted to Journal of Machine Learning
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