7,130 research outputs found
On existence of mini-boson stars
We prove the existence of a countable family of globally regular solutions of
spherically symmetric Einstein-Klein-Gordon equations. These solutions, known
as mini-boson stars, were discovered numerically many years ago.Comment: 15 pages, 1 eps figure, LaTe
Self-similar solutions of semilinear wave equations with a focusing nonlinearity
We prove that in three space dimensions a nonlinear wave equation
with being an odd integer has a countable
family of regular spherically symmetric self-similar solutions.Comment: 12 pages, 3 figures, minor corrections to match the published versio
Analysis of relative influence of nodes in directed networks
Many complex networks are described by directed links; in such networks, a
link represents, for example, the control of one node over the other node or
unidirectional information flows. Some centrality measures are used to
determine the relative importance of nodes specifically in directed networks.
We analyze such a centrality measure called the influence. The influence
represents the importance of nodes in various dynamics such as synchronization,
evolutionary dynamics, random walk, and social dynamics. We analytically
calculate the influence in various networks, including directed multipartite
networks and a directed version of the Watts-Strogatz small-world network. The
global properties of networks such as hierarchy and position of shortcuts,
rather than local properties of the nodes, such as the degree, are shown to be
the chief determinants of the influence of nodes in many cases. The developed
method is also applicable to the calculation of the PageRank. We also
numerically show that in a coupled oscillator system, the threshold for
entrainment by a pacemaker is low when the pacemaker is placed on influential
nodes. For a type of random network, the analytically derived threshold is
approximately equal to the inverse of the influence. We numerically show that
this relationship also holds true in a random scale-free network and a neural
network.Comment: 9 figure
Relaxation dynamics of maximally clustered networks
We study the relaxation dynamics of fully clustered networks (maximal number
of triangles) to an unclustered state under two different edge dynamics---the
double-edge swap, corresponding to degree-preserving randomization of the
configuration model, and single edge replacement, corresponding to full
randomization of the Erd\H{o}s--R\'enyi random graph. We derive expressions for
the time evolution of the degree distribution, edge multiplicity distribution
and clustering coefficient. We show that under both dynamics networks undergo a
continuous phase transition in which a giant connected component is formed. We
calculate the position of the phase transition analytically using the
Erd\H{o}s--R\'enyi phenomenology
On the existence of self-similar spherically symmetric wave maps coupled to gravity
We present a detailed analytical study of spherically symmetric self-similar
solutions in the SU(2) sigma model coupled to gravity. Using a shooting
argument we prove that there is a countable family of solutions which are
analytic inside the past self-similarity horizon. In addition, we show that for
sufficiently small values of the coupling constant these solutions possess a
regular future self-similarity horizon and thus are examples of naked
singularities. One of the solutions constructed here has been recently found as
the critical solution at the threshold of black hole formation.Comment: 15 pages, LaTe
Social dynamics in conferences: analyses of data from the Live Social Semantics application
Popularity and spread of online social networking in recent years has given a great momentum to the study of dynamics and patterns of social interactions. However, these studies have often been confined to the online world, neglecting its interdependencies with the offline world. This is mainly due to the lack of real data that spans across this divide. The Live Social Semantics application is a novel platform that dissolves this divide, by collecting and integrating data about people from (a) their online social networks and tagging activities from popular social networking sites, (b) their publications and co-authorship networks from semantic repositories, and (c) their real-world face-to-face contacts with other attendees collected via a network of wearable active sensors. This paper investigates the data collected by this application during its deployment at three major conferences, where it was used by more than 400 people. Our analyses show the robustness of the patterns of contacts at various conferences, and the influence of various personal properties (e.g. seniority, conference attendance) on social networking patterns
Centrality scaling in large networks
Betweenness centrality lies at the core of both transport and structural
vulnerability properties of complex networks, however, it is computationally
costly, and its measurement for networks with millions of nodes is near
impossible. By introducing a multiscale decomposition of shortest paths, we
show that the contributions to betweenness coming from geodesics not longer
than L obey a characteristic scaling vs L, which can be used to predict the
distribution of the full centralities. The method is also illustrated on a
real-world social network of 5.5*10^6 nodes and 2.7*10^7 links
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