489 research outputs found
Computing the distribution of the maximum in balls-and-boxes problems, with application to clusters of disease cases
We present a rapid method for the exact calculation of the cumulative
distribution function of the maximum of multinomially distributed random
variables. The method runs in time , where is the desired maximum
and is the number of variables. We apply the method to the analysis of two
situations where an apparent clustering of cases of a disease in some locality
has raised the possibility that the disease might be communicable, and this
possibility has been discussed in the recent literature. We conclude that one
of these clusters may be explained on purely random grounds, whereas the other
may not
Uniform asymptotics of the coefficients of unitary moment polynomials
Keating and Snaith showed that the absolute moment of the
characteristic polynomial of a random unitary matrix evaluated on the unit
circle is given by a polynomial of degree . In this article, uniform
asymptotics for the coefficients of that polynomial are derived, and a maximal
coefficient is located. Some of the asymptotics are given in explicit form.
Numerical data to support these calculations are presented. Some apparent
connections between random matrix theory and the Riemann zeta function are
discussed.Comment: 31 pages, 1 figure, 2 tables. A few minor misprints fixe
Absence of pre-classical solutions in Bianchi I loop quantum cosmology
Loop quantum cosmology, the symmetry reduction of quantum geometry for the
study of various cosmological situations, leads to a difference equation for
its quantum evolution equation. To ensure that solutions of this equation act
in the expected classical manner far from singularities, additional
restrictions are imposed on the solution. In this paper, we consider the
Bianchi I model, both the vacuum case and the addition of a cosmological
constant, and show using generating function techniques that only the zero
solution satisfies these constraints. This implies either that there are
technical difficulties with the current method of quantizing the evolution
equation, or else loop quantum gravity imposes strong restrictions on the
physically allowed solutions.Comment: 4 pages, no figures, version to appear in PR
Hidden Variables in Bipartite Networks
We introduce and study random bipartite networks with hidden variables. Nodes
in these networks are characterized by hidden variables which control the
appearance of links between node pairs. We derive analytic expressions for the
degree distribution, degree correlations, the distribution of the number of
common neighbors, and the bipartite clustering coefficient in these networks.
We also establish the relationship between degrees of nodes in original
bipartite networks and in their unipartite projections. We further demonstrate
how hidden variable formalism can be applied to analyze topological properties
of networks in certain bipartite network models, and verify our analytical
results in numerical simulations
Propagation on networks: an exact alternative perspective
By generating the specifics of a network structure only when needed
(on-the-fly), we derive a simple stochastic process that exactly models the
time evolution of susceptible-infectious dynamics on finite-size networks. The
small number of dynamical variables of this birth-death Markov process greatly
simplifies analytical calculations. We show how a dual analytical description,
treating large scale epidemics with a Gaussian approximations and small
outbreaks with a branching process, provides an accurate approximation of the
distribution even for rather small networks. The approach also offers important
computational advantages and generalizes to a vast class of systems.Comment: 8 pages, 4 figure
Predicting the size and probability of epidemics in a population with heterogeneous infectiousness and susceptibility
We analytically address disease outbreaks in large, random networks with
heterogeneous infectivity and susceptibility. The transmissibility
(the probability that infection of causes infection of ) depends on the
infectivity of and the susceptibility of . Initially a single node is
infected, following which a large-scale epidemic may or may not occur. We use a
generating function approach to study how heterogeneity affects the probability
that an epidemic occurs and, if one occurs, its attack rate (the fraction
infected). For fixed average transmissibility, we find upper and lower bounds
on these. An epidemic is most likely if infectivity is homogeneous and least
likely if the variance of infectivity is maximized. Similarly, the attack rate
is largest if susceptibility is homogeneous and smallest if the variance is
maximized. We further show that heterogeneity in infectious period is
important, contrary to assumptions of previous studies. We confirm our
theoretical predictions by simulation. Our results have implications for
control strategy design and identification of populations at higher risk from
an epidemic.Comment: 5 pages, 3 figures. Submitted to Physical Review Letter
Optimization in task--completion networks
We discuss the collective behavior of a network of individuals that receive,
process and forward to each other tasks. Given costs they store those tasks in
buffers, choosing optimally the frequency at which to check and process the
buffer. The individual optimizing strategy of each node determines the
aggregate behavior of the network. We find that, under general assumptions, the
whole system exhibits coexistence of equilibria and hysteresis.Comment: 18 pages, 3 figures, submitted to JSTA
Combinatorics and Boson normal ordering: A gentle introduction
We discuss a general combinatorial framework for operator ordering problems
by applying it to the normal ordering of the powers and exponential of the
boson number operator. The solution of the problem is given in terms of Bell
and Stirling numbers enumerating partitions of a set. This framework reveals
several inherent relations between ordering problems and combinatorial objects,
and displays the analytical background to Wick's theorem. The methodology can
be straightforwardly generalized from the simple example given herein to a wide
class of operators.Comment: 8 pages, 1 figur
Heterogeneous Bond Percolation on Multitype Networks with an Application to Epidemic Dynamics
Considerable attention has been paid, in recent years, to the use of networks
in modeling complex real-world systems. Among the many dynamical processes
involving networks, propagation processes -- in which final state can be
obtained by studying the underlying network percolation properties -- have
raised formidable interest. In this paper, we present a bond percolation model
of multitype networks with an arbitrary joint degree distribution that allows
heterogeneity in the edge occupation probability. As previously demonstrated,
the multitype approach allows many non-trivial mixing patterns such as
assortativity and clustering between nodes. We derive a number of useful
statistical properties of multitype networks as well as a general phase
transition criterion. We also demonstrate that a number of previous models
based on probability generating functions are special cases of the proposed
formalism. We further show that the multitype approach, by naturally allowing
heterogeneity in the bond occupation probability, overcomes some of the
correlation issues encountered by previous models. We illustrate this point in
the context of contact network epidemiology.Comment: 10 pages, 5 figures. Minor modifications were made in figures 3, 4
and 5 and in the text. Explanations and references were adde
Counting, generating and sampling tree alignments
Pairwise ordered tree alignment are combinatorial objects that appear in RNA
secondary structure comparison. However, the usual representation of tree
alignments as supertrees is ambiguous, i.e. two distinct supertrees may induce
identical sets of matches between identical pairs of trees. This ambiguity is
uninformative, and detrimental to any probabilistic analysis.In this work, we
consider tree alignments up to equivalence. Our first result is a precise
asymptotic enumeration of tree alignments, obtained from a context-free grammar
by mean of basic analytic combinatorics. Our second result focuses on
alignments between two given ordered trees and . By refining our grammar
to align specific trees, we obtain a decomposition scheme for the space of
alignments, and use it to design an efficient dynamic programming algorithm for
sampling alignments under the Gibbs-Boltzmann probability distribution. This
generalizes existing tree alignment algorithms, and opens the door for a
probabilistic analysis of the space of suboptimal RNA secondary structures
alignments.Comment: ALCOB - 3rd International Conference on Algorithms for Computational
Biology - 2016, Jun 2016, Trujillo, Spain. 201
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