13,561 research outputs found
Sharp benefit-to-cost rules for the evolution of cooperation on regular graphs
We study two of the simple rules on finite graphs under the death-birth
updating and the imitation updating discovered by Ohtsuki, Hauert, Lieberman
and Nowak [Nature 441 (2006) 502-505]. Each rule specifies a payoff-ratio
cutoff point for the magnitude of fixation probabilities of the underlying
evolutionary game between cooperators and defectors. We view the Markov chains
associated with the two updating mechanisms as voter model perturbations. Then
we present a first-order approximation for fixation probabilities of general
voter model perturbations on finite graphs subject to small perturbation in
terms of the voter model fixation probabilities. In the context of regular
graphs, we obtain algebraically explicit first-order approximations for the
fixation probabilities of cooperators distributed as certain uniform
distributions. These approximations lead to a rigorous proof that both of the
rules of Ohtsuki et al. are valid and are sharp.Comment: Published in at http://dx.doi.org/10.1214/12-AAP849 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Exact Pseudofermion Action for Monte Carlo Simulation of Domain-Wall Fermion
We present an exact pseudofermion action for hybrid Monte Carlo simulation
(HMC) of one-flavor domain-wall fermion (DWF), with the effective 4-dimensional
Dirac operator equal to the optimal rational approximation of the overlap-Dirac
operator with kernel , where and are constants. Using this exact pseudofermion action, we perform HMC of
one-flavor QCD, and compare its characteristics with the widely used rational
hybrid Monte Carlo algorithm (RHMC). Moreover, to demonstrate the practicality
of the exact one-flavor algorithm (EOFA), we perform the first dynamical
simulation of the (1+1)-flavors QCD with DWF.Comment: 13 pages, 4 figures, v2: Simulation of (1+1)-flavors QCD with DWF,
and references added. To appear in Phys. Lett.
Smaller population size at the MRCA time for stationary branching processes
We present an elementary model of random size varying population given by a
stationary continuous state branching process. For this model we compute the
joint distribution of: the time to the most recent common ancestor, the size of
the current population and the size of the population just before the most
recent common ancestor (MRCA). In particular we show a natural mild bottleneck
effect as the size of the population just before the MRCA is stochastically
smaller than the size of the current population. We also compute the number of
old families which corresponds to the number of individuals involved in the
last coalescent event of the genealogical tree. By studying more precisely the
genealogical structure of the population, we get asymptotics for the number of
ancestors just before the current time. We give explicit computations in the
case of the quadratic branching mechanism. In this case, the size of the
population at the MRCA is, in mean, less by 1/3 than size of the current
population size. We also provide in this case the fluctuations for the
renormalized number of ancestors
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