6,545 research outputs found
Soft singularity and the fundamental length
It is shown that some regular solutions in 5D Kaluza-Klein gravity may have
interesting properties if one from the parameters is in the Planck region. In
this case the Kretschman metric invariant runs up to a maximal reachable value
in nature, i.e. practically the metric becomes singular. This observation
allows us to suppose that in this situation the problems with such soft
singularity will be much easier resolved in the future quantum gravity then by
the situation with the ordinary hard singularity (Reissner-Nordstr\"om
singularity, for example). It is supposed that the analogous consideration can
be applied for the avoiding the hard singularities connected with the gauge
charges.Comment: 5 page
Bootstrap Percolation on Complex Networks
We consider bootstrap percolation on uncorrelated complex networks. We obtain
the phase diagram for this process with respect to two parameters: , the
fraction of vertices initially activated, and , the fraction of undamaged
vertices in the graph. We observe two transitions: the giant active component
appears continuously at a first threshold. There may also be a second,
discontinuous, hybrid transition at a higher threshold. Avalanches of
activations increase in size as this second critical point is approached,
finally diverging at this threshold. We describe the existence of a special
critical point at which this second transition first appears. In networks with
degree distributions whose second moment diverges (but whose first moment does
not), we find a qualitatively different behavior. In this case the giant active
component appears for any and , and the discontinuous transition is
absent. This means that the giant active component is robust to damage, and
also is very easily activated. We also formulate a generalized bootstrap
process in which each vertex can have an arbitrary threshold.Comment: 9 pages, 3 figure
Effective action in DSR1 quantum field theory
We present the one-loop effective action of a quantum scalar field with DSR1
space-time symmetry as a sum over field modes. The effective action has real
and imaginary parts and manifest charge conjugation asymmetry, which provides
an alternative theoretical setting to the study of the particle-antiparticle
asymmetry in nature.Comment: 8 page
Inventário de mamíferos de médio e grande porte no município de São Pedro do Ivaí, estado do Paraná.
EVINCI. Resumo 024
Heterogeneous-k-core versus Bootstrap Percolation on Complex Networks
We introduce the heterogeneous--core, which generalizes the -core, and
contrast it with bootstrap percolation. Vertices have a threshold which
may be different at each vertex. If a vertex has less than neighbors it
is pruned from the network. The heterogeneous--core is the sub-graph
remaining after no further vertices can be pruned. If the thresholds are
with probability or with probability , the process
forms one branch of an activation-pruning process which demonstrates
hysteresis. The other branch is formed by ordinary bootstrap percolation. We
show that there are two types of transitions in this heterogeneous--core
process: the giant heterogeneous--core may appear with a continuous
transition and there may be a second, discontinuous, hybrid transition. We
compare critical phenomena, critical clusters and avalanches at the
heterogeneous--core and bootstrap percolation transitions. We also show that
network structure has a crucial effect on these processes, with the giant
heterogeneous--core appearing immediately at a finite value for any
when the degree distribution tends to a power law with
.Comment: 10 pages, 4 figure
Region-Based Classification of PolSAR Data Using Radial Basis Kernel Functions With Stochastic Distances
Region-based classification of PolSAR data can be effectively performed by
seeking for the assignment that minimizes a distance between prototypes and
segments. Silva et al (2013) used stochastic distances between complex
multivariate Wishart models which, differently from other measures, are
computationally tractable. In this work we assess the robustness of such
approach with respect to errors in the training stage, and propose an extension
that alleviates such problems. We introduce robustness in the process by
incorporating a combination of radial basis kernel functions and stochastic
distances with Support Vector Machines (SVM). We consider several stochastic
distances between Wishart: Bhatacharyya, Kullback-Leibler, Chi-Square,
R\'{e}nyi, and Hellinger. We perform two case studies with PolSAR images, both
simulated and from actual sensors, and different classification scenarios to
compare the performance of Minimum Distance and SVM classification frameworks.
With this, we model the situation of imperfect training samples. We show that
SVM with the proposed kernel functions achieves better performance with respect
to Minimum Distance, at the expense of more computational resources and the
need of parameter tuning. Code and data are provided for reproducibility.Comment: Accepted for publication in the International Journal of Digital
Eart
Rotated multifractal network generator
The recently introduced multifractal network generator (MFNG), has been shown
to provide a simple and flexible tool for creating random graphs with very
diverse features. The MFNG is based on multifractal measures embedded in 2d,
leading also to isolated nodes, whose number is relatively low for realistic
cases, but may become dominant in the limiting case of infinitely large network
sizes. Here we discuss the relation between this effect and the information
dimension for the 1d projection of the link probability measure (LPM), and
argue that the node isolation can be avoided by a simple transformation of the
LPM based on rotation.Comment: Accepted for publication in JSTA
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