2,811 research outputs found
The Contribution of the First Stars to the Cosmic Infrared Background
We calculate the contribution to the cosmic infrared background from very
massive metal-free stars at high redshift. We explore two plausible
star-formation models and two limiting cases for the reprocessing of the
ionizing stellar emission. We find that Population III stars may contribute
significantly to the cosmic near-infrared background if the following
conditions are met: (i) The first stars were massive, with M > ~100 M_sun. (ii)
Molecular hydrogen can cool baryons in low-mass haloes. (iii) Pop III star
formation is ongoing, and not shut off through negative feedback effects. (iv)
Virialized haloes form stars at about 40 per cent efficiency up to the redshift
of reionization, z~7. (v) The escape fraction of the ionizing radiation into
the intergalactic medium is small. (vi) Nearly all of the stars end up in
massive black holes without contributing to the metal enrichment of the
Universe.Comment: 11 pages, 6 figures, expanded discussion, added mid-IR to Fig 6,
MNRAS in pres
Percolation Critical Exponents in Scale-Free Networks
We study the behavior of scale-free networks, having connectivity
distribution P(k) k^-a, close to the percolation threshold. We show that for
networks with 3<a<4, known to undergo a transition at a finite threshold of
dilution, the critical exponents are different than the expected mean-field
values of regular percolation in infinite dimensions. Networks with 2<a<3
possess only a percolative phase. Nevertheless, we show that in this case
percolation critical exponents are well defined, near the limit of extreme
dilution (where all sites are removed), and that also then the exponents bear a
strong a-dependence. The regular mean-field values are recovered only for a>4.Comment: Latex, 4 page
Competition and Facilitation: a Synthetic Approach to Interactions in Plant Communities
Interactions among organisms take place within a complex milieu of abiotic and biotic processes, but we generally study them as solitary phenomena. Complex combinations of negative and positive interactions have been identified in a number of plant communities. The importance of these two processes in structuring plant communities can best be understood by comparing them along gradients of abiotic stress, consumer pressure, and among different life stages, sizes, and densities of the interacting species. Here, we discuss the roles of life stage, physiology, indirect interactions, and the physical environment on the balance of competition and facilitation in plant communities
Retrograde Tracing with Recombinant Rabies Virus Reveals Correlations Between Projection Targets and Dendritic Architecture in Layer 5 of Mouse Barrel Cortex
A recombinant rabies virus was used as a retrograde tracer to allow complete filling of the axonal and dendritic arbors of identified projection neurons in layer 5 of mouse primary somatosensory cortex (S1) in vivo. Previous studies have distinguished three types of layer 5 pyramids in S1: tall-tufted, tall-simple, and short. Layer 5 pyramidal neurons were retrogradely labeled from several known targets: contralateral S1, superior colliculus, and thalamus. The complete dendritic arbors of labeled cells were reconstructed to allow for unambiguous classification of cell type. We confirmed that the tall-tufted pyramids project to the superior colliculus and thalamus and that short layer 5 pyramidal neurons project to contralateral cortex, as previously described. We found that tall-simple pyramidal neurons contribute to corticocortical connections. Axonal reconstructions show that corticocortical projection neurons have a large superficial axonal arborization locally, while the subcortically projecting neurons limit axonal arbors to the deep layers. Furthermore, reconstructions of local axons suggest that tall-simple cell axons have extensive lateral spread while those of the short pyramids are more columnar. These differences were revealed by the ability to completely label dendritic and axonal arbors in vivo and have not been apparent in previous studies using labeling in brain slices
Evaluation of the optical conductivity tensor in terms of contour integrations
For the case of finite life-time broadening the standard Kubo-formula for the
optical conductivity tensor is rederived in terms of Green's functions by using
contour integrations, whereby finite temperatures are accounted for by using
the Fermi-Dirac distribution function. For zero life-time broadening, the
present formalism is related to expressions well-known in the literature.
Numerical aspects of how to calculate the corresponding contour integrals are
also outlined.Comment: 8 pages, Latex + 2 figure (Encapsulated Postscript
The architecture of complex weighted networks
Networked structures arise in a wide array of different contexts such as
technological and transportation infrastructures, social phenomena, and
biological systems. These highly interconnected systems have recently been the
focus of a great deal of attention that has uncovered and characterized their
topological complexity. Along with a complex topological structure, real
networks display a large heterogeneity in the capacity and intensity of the
connections. These features, however, have mainly not been considered in past
studies where links are usually represented as binary states, i.e. either
present or absent. Here, we study the scientific collaboration network and the
world-wide air-transportation network, which are representative examples of
social and large infrastructure systems, respectively. In both cases it is
possible to assign to each edge of the graph a weight proportional to the
intensity or capacity of the connections among the various elements of the
network. We define new appropriate metrics combining weighted and topological
observables that enable us to characterize the complex statistical properties
and heterogeneity of the actual strength of edges and vertices. This
information allows us to investigate for the first time the correlations among
weighted quantities and the underlying topological structure of the network.
These results provide a better description of the hierarchies and
organizational principles at the basis of the architecture of weighted
networks
Computational complexity arising from degree correlations in networks
We apply a Bethe-Peierls approach to statistical-mechanics models defined on
random networks of arbitrary degree distribution and arbitrary correlations
between the degrees of neighboring vertices. Using the NP-hard optimization
problem of finding minimal vertex covers on these graphs, we show that such
correlations may lead to a qualitatively different solution structure as
compared to uncorrelated networks. This results in a higher complexity of the
network in a computational sense: Simple heuristic algorithms fail to find a
minimal vertex cover in the highly correlated case, whereas uncorrelated
networks seem to be simple from the point of view of combinatorial
optimization.Comment: 4 pages, 1 figure, accepted in Phys. Rev.
Ising Model on Networks with an Arbitrary Distribution of Connections
We find the exact critical temperature of the nearest-neighbor
ferromagnetic Ising model on an `equilibrium' random graph with an arbitrary
degree distribution . We observe an anomalous behavior of the
magnetization, magnetic susceptibility and specific heat, when is
fat-tailed, or, loosely speaking, when the fourth moment of the distribution
diverges in infinite networks. When the second moment becomes divergent,
approaches infinity, the phase transition is of infinite order, and size effect
is anomalously strong.Comment: 5 page
Are randomly grown graphs really random?
We analyze a minimal model of a growing network. At each time step, a new
vertex is added; then, with probability delta, two vertices are chosen
uniformly at random and joined by an undirected edge. This process is repeated
for t time steps. In the limit of large t, the resulting graph displays
surprisingly rich characteristics. In particular, a giant component emerges in
an infinite-order phase transition at delta = 1/8. At the transition, the
average component size jumps discontinuously but remains finite. In contrast, a
static random graph with the same degree distribution exhibits a second-order
phase transition at delta = 1/4, and the average component size diverges there.
These dramatic differences between grown and static random graphs stem from a
positive correlation between the degrees of connected vertices in the grown
graph--older vertices tend to have higher degree, and to link with other
high-degree vertices, merely by virtue of their age. We conclude that grown
graphs, however randomly they are constructed, are fundamentally different from
their static random graph counterparts.Comment: 8 pages, 5 figure
Matching conditions and Higgs mass upper bounds revisited
Matching conditions relate couplings to particle masses. We discuss the
importance of one-loop matching conditions in Higgs and top-quark sector as
well as the choice of the matching scale. We argue for matching scales
and . Using these
results, the two-loop Higgs mass upper bounds are reanalyzed. Previous results
for few TeV are found to be too stringent. For
GeV we find GeV, the first error
indicating the theoretical uncertainty, the second error reflecting the
experimental uncertainty due to GeV.Comment: 20 pages, 6 figures; uses epsf and rotate macro
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