4,555 research outputs found
Ising models on locally tree-like graphs
We consider ferromagnetic Ising models on graphs that converge locally to
trees. Examples include random regular graphs with bounded degree and uniformly
random graphs with bounded average degree. We prove that the "cavity"
prediction for the limiting free energy per spin is correct for any positive
temperature and external field. Further, local marginals can be approximated by
iterating a set of mean field (cavity) equations. Both results are achieved by
proving the local convergence of the Boltzmann distribution on the original
graph to the Boltzmann distribution on the appropriate infinite random tree.Comment: Published in at http://dx.doi.org/10.1214/09-AAP627 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Finite size scaling for the core of large random hypergraphs
The (two) core of a hypergraph is the maximal collection of hyperedges within
which no vertex appears only once. It is of importance in tasks such as
efficiently solving a large linear system over GF[2], or iterative decoding of
low-density parity-check codes used over the binary erasure channel. Similar
structures emerge in a variety of NP-hard combinatorial optimization and
decision problems, from vertex cover to satisfiability. For a uniformly chosen
random hypergraph of vertices and hyperedges, each consisting of
the same fixed number of vertices, the size of the core exhibits for
large a first-order phase transition, changing from for to a positive fraction of for , with
a transition window size around .
Analyzing the corresponding ``leaf removal'' algorithm, we determine the
associated finite-size scaling behavior. In particular, if is inside the
scaling window (more precisely, ), the
probability of having a core of size has a limit strictly between 0
and 1, and a leading correction of order . The correction
admits a sharp characterization in terms of the distribution of a Brownian
motion with quadratic shift, from which it inherits the scaling with . This
behavior is expected to be universal for a wide collection of combinatorial
problems.Comment: Published in at http://dx.doi.org/10.1214/07-AAP514 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Markovian perturbation, response and fluctuation dissipation theorem
We consider the Fluctuation Dissipation Theorem (FDT) of statistical physics
from a mathematical perspective. We formalize the concept of "linear response
function" in the general framework of Markov processes. We show that for
processes out of equilibrium it depends not only on the given Markov process
X(s) but also on the chosen perturbation of it. We characterize the set of all
possible response functions for a given Markov process and show that at
equilibrium they all satisfy the FDT. That is, if the initial measure is
invariant for the given Markov semi-group, then for any pair of times s<t and
nice functions f,g, the dissipation, that is, the derivative in s of the
covariance of g(X(t)) and f(X(s)) equals the infinitesimal response at time t
and direction g to any Markovian perturbation that alters the invariant measure
of X(.) in the direction of f at time s. The same applies in the so called FDT
regime near equilibrium, i.e. in the limit s going to infinity with t-s fixed,
provided X(s) converges in law to an invariant measure for its dynamics. We
provide the response function of two generic Markovian perturbations which we
then compare and contrast for pure jump processes on a discrete space, for
finite dimensional diffusion processes, and for stochastic spin systems
Oppen's Pragmatism
This article seeks to rethink the philosophical context of the modern American poet George Oppen's writing by resituating it with the tradition of American pragmatism championed by William James. It is, to my knowledge, the first article to make this case on both philosophical and formal grounds and therefore constitutes a significant intervention into the emerging field of Oppen studies
Slowdown estimates for one-dimensional random walks in random environment with holding times
We consider a one dimensional random walk in random environment that is
uniformly biased to one direction. In addition to the transition probability,
the jump rate of the random walk is assumed to be spatially inhomogeneous and
random. We study the probability that the random walk travels slower than its
typical speed and determine its decay rate asymptotic.Comment: 13 pages. There are corrections in the extreme value lemmas and the
quenched slowdown estimate
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