2,346 research outputs found
Finite-Size Scaling Exponents in the Dicke Model
We consider the finite-size corrections in the Dicke model and determine the
scaling exponents at the critical point for several quantities such as the
ground state energy or the gap. Therefore, we use the Holstein-Primakoff
representation of the angular momentum and introduce a nonlinear transformation
to diagonalize the Hamiltonian in the normal phase. As already observed in
several systems, these corrections turn out to be singular at the transition
point and thus lead to nontrivial exponents. We show that for the atomic
observables, these exponents are the same as in the Lipkin-Meshkov-Glick model,
in agreement with numerical results. We also investigate the behavior of the
order parameter related to the radiation mode and show that it is driven by the
same scaling variable as the atomic one.Comment: 4 pages, published versio
Mycoplasma Mastitis in Dairy Cattle
Mastitis is defined as inflammation of the mammary gland, usually due to microbial infection. Many organisms have been known to cause mastitis including bacteria, fungi, and yeast. Mastitis is the most economically important disease of the dairy industry, the condition has been estimated to cause as much as two billion dollars in lost income for United States dairy producers at a cost of $181 per cow per year. The biggest losses are due to lowered production, but discarded milk, drugs, veterinary costs, and premature culling also contribute to the losses. More than 130 different microorganisms have been isolated from the mammary gland of the bovine with the majority of infections due to staphylococci, streptococci, and coliforms. However, mycoplasmas have begun to cause significant problems in some dairies. The first reported cases of mycoplasma mastitis were in Europe in 1960. Since that time it has been found all around the world, including the United States. Traditionally, California was most affected, but the disease has now become a problem across the entire country
Simultaneous Embeddability of Two Partitions
We study the simultaneous embeddability of a pair of partitions of the same
underlying set into disjoint blocks. Each element of the set is mapped to a
point in the plane and each block of either of the two partitions is mapped to
a region that contains exactly those points that belong to the elements in the
block and that is bounded by a simple closed curve. We establish three main
classes of simultaneous embeddability (weak, strong, and full embeddability)
that differ by increasingly strict well-formedness conditions on how different
block regions are allowed to intersect. We show that these simultaneous
embeddability classes are closely related to different planarity concepts of
hypergraphs. For each embeddability class we give a full characterization. We
show that (i) every pair of partitions has a weak simultaneous embedding, (ii)
it is NP-complete to decide the existence of a strong simultaneous embedding,
and (iii) the existence of a full simultaneous embedding can be tested in
linear time.Comment: 17 pages, 7 figures, extended version of a paper to appear at GD 201
Detection of Complex Networks Modularity by Dynamical Clustering
Based on cluster de-synchronization properties of phase oscillators, we
introduce an efficient method for the detection and identification of modules
in complex networks. The performance of the algorithm is tested on computer
generated and real-world networks whose modular structure is already known or
has been studied by means of other methods. The algorithm attains a high level
of precision, especially when the modular units are very mixed and hardly
detectable by the other methods, with a computational effort on
a generic graph with nodes and links.Comment: 5 pages, 2 figures. Version accepted for publication on PRE Rapid
Communications: figures changed and text adde
ORGANIZATIONAL CYNICISM.
What is the nature of the extremely negative attitudes expressed by so many employees toward their organizations? To respond to this question, we introduce the concept of organizational cynicism. We review the literature from several disciplines on this concept and suggest that organizational cynicism is an attitude composed of beliefs, affect, and behavioral tendencies toward an organization. Following our review and conceptualization, we derive implications of this concept and propose a research agenda for organizational cynicis
Preservation of Positivity by Dynamical Coarse-Graining
We compare different quantum Master equations for the time evolution of the
reduced density matrix. The widely applied secular approximation (rotating wave
approximation) applied in combination with the Born-Markov approximation
generates a Lindblad type master equation ensuring for completely positive and
stable evolution and is typically well applicable for optical baths. For phonon
baths however, the secular approximation is expected to be invalid. The usual
Markovian master equation does not generally preserve positivity of the density
matrix. As a solution we propose a coarse-graining approach with a dynamically
adapted coarse graining time scale. For some simple examples we demonstrate
that this preserves the accuracy of the integro-differential Born equation. For
large times we analytically show that the secular approximation master equation
is recovered. The method can in principle be extended to systems with a
dynamically changing system Hamiltonian, which is of special interest for
adiabatic quantum computation. We give some numerical examples for the
spin-boson model of cases where a spin system thermalizes rapidly, and other
examples where thermalization is not reached.Comment: 18 pages, 7 figures, reviewers suggestions included and tightened
presentation; accepted for publication in PR
A Method to Find Community Structures Based on Information Centrality
Community structures are an important feature of many social, biological and
technological networks. Here we study a variation on the method for detecting
such communities proposed by Girvan and Newman and based on the idea of using
centrality measures to define the community boundaries (M. Girvan and M. E. J.
Newman, Community structure in social and biological networks Proc. Natl. Acad.
Sci. USA 99, 7821-7826 (2002)). We develop an algorithm of hierarchical
clustering that consists in finding and removing iteratively the edge with the
highest information centrality. We test the algorithm on computer generated and
real-world networks whose community structure is already known or has been
studied by means of other methods. We show that our algorithm, although it runs
to completion in a time O(n^4), is very effective especially when the
communities are very mixed and hardly detectable by the other methods.Comment: 13 pages, 13 figures. Final version accepted for publication in
Physical Review
Quantum transfer matrix method for one-dimensional disordered electronic systems
We develop a novel quantum transfer matrix method to study thermodynamic
properties of one-dimensional (1D) disordered electronic systems. It is shown
that the partition function can be expressed as a product of local
transfer matrices. We demonstrate this method by applying it to the 1D
disordered Anderson model. Thermodynamic quantities of this model are
calculated and discussed.Comment: 7 pages, 10 figure
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