33,177 research outputs found
First- and second-order phase transitions in Ising models on small world networks, simulations and comparison with an effective field theory
We perform simulations of random Ising models defined over small-world
networks and we check the validity and the level of approximation of a recently
proposed effective field theory. Simulations confirm a rich scenario with the
presence of multicritical points with first- or second-order phase transitions.
In particular, for second-order phase transitions, independent of the dimension
d_0 of the underlying lattice, the exact predictions of the theory in the
paramagnetic regions, such as the location of critical surfaces and correlation
functions, are verified. Quite interestingly, we verify that the
Edwards-Anderson model with d_0=2 is not thermodynamically stable under graph
noise.Comment: 12 pages, 12 figures, 1 tabl
A Framework for Dynamic Web Services Composition
Dynamic composition of web services is a promising approach and at the same time a challenging research area for the dissemination of service-oriented applications. It is widely recognised that service semantics is a key element for the dynamic composition of Web services, since it allows the unambiguous descriptions of a service's capabilities and parameters. This paper introduces a framework for performing dynamic service composition by exploiting the semantic matchmaking between service parameters (i.e., outputs and inputs) to enable their interconnection and interaction. The basic assumption of the framework is that matchmaking enables finding semantic compatibilities among independently defined service descriptions. We also developed a composition algorithm that follows a semantic graph-based approach, in which a graph represents service compositions and the nodes of this graph represent semantic connections between services. Moreover, functional and non-functional properties of services are considered, to enable the computation of relevant and most suitable service compositions for some service request. The suggested end-to-end functional level service composition framework is illustrated with a realistic application scenario from the IST SPICE project
Mean-field analysis of the majority-vote model broken-ergodicity steady state
We study analytically a variant of the one-dimensional majority-vote model in
which the individual retains its opinion in case there is a tie among the
neighbors' opinions. The individuals are fixed in the sites of a ring of size
and can interact with their nearest neighbors only. The interesting feature
of this model is that it exhibits an infinity of spatially heterogeneous
absorbing configurations for whose statistical properties we
probe analytically using a mean-field framework based on the decomposition of
the -site joint probability distribution into the -contiguous-site joint
distributions, the so-called -site approximation. To describe the
broken-ergodicity steady state of the model we solve analytically the
mean-field dynamic equations for arbitrary time in the cases n=3 and 4. The
asymptotic limit reveals the mapping between the statistical
properties of the random initial configurations and those of the final
absorbing configurations. For the pair approximation () we derive that
mapping using a trick that avoids solving the full dynamics. Most remarkably,
we find that the predictions of the 4-site approximation reduce to those of the
3-site in the case of expectations involving three contiguous sites. In
addition, those expectations fit the Monte Carlo data perfectly and so we
conjecture that they are in fact the exact expectations for the one-dimensional
majority-vote model
A mass-transportation approach to a one dimensional fluid mechanics model with nonlocal velocity
We consider a one dimensional transport model with nonlocal velocity given by
the Hilbert transform and develop a global well-posedness theory of probability
measure solutions. Both the viscous and non-viscous cases are analyzed. Both in
original and in self-similar variables, we express the corresponding equations
as gradient flows with respect to a free energy functional including a singular
logarithmic interaction potential. Existence, uniqueness, self-similar
asymptotic behavior and inviscid limit of solutions are obtained in the space
of probability measures with finite second
moments, without any smallness condition. Our results are based on the abstract
gradient flow theory developed in \cite{Ambrosio}. An important byproduct of
our results is that there is a unique, up to invariance and translations,
global in time self-similar solution with initial data in
, which was already obtained in
\textrm{\cite{Deslippe,Biler-Karch}} by different methods. Moreover, this
self-similar solution attracts all the dynamics in self-similar variables. The
crucial monotonicity property of the transport between measures in one
dimension allows to show that the singular logarithmic potential energy is
displacement convex. We also extend the results to gradient flow equations with
negative power-law locally integrable interaction potentials
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