10,330 research outputs found

    Growth fluctuations in a class of deposition models

    Get PDF
    We compute the growth fluctuations in equilibrium of a wide class of deposition models. These models also serve as general frame to several nearest-neighbor particle jump processes, e.g. the simple exclusion or the zero range process, where our result turns to current fluctuations of the particles. We use martingale technique and coupling methods to show that, rescaled by time, the variance of the growth as seen by a deterministic moving observer has the form |V-C|*D, where V and C is the speed of the observer and the second class particle, respectively, and D is a constant connected to the equilibrium distribution of the model. Our main result is a generalization of Ferrari and Fontes' result for simple exclusion process. Law of large numbers and central limit theorem are also proven. We need some properties of the motion of the second class particle, which are known for simple exclusion and are partly known for zero range processes, and which are proven here for a type of deposition models and also for a type of zero range processes.Comment: A minor mistake in lemma 5.1 is now correcte

    Measure concentration for Euclidean distance in the case of dependent random variables

    Full text link
    Let q^n be a continuous density function in n-dimensional Euclidean space. We think of q^n as the density function of some random sequence X^n with values in \BbbR^n. For I\subset[1,n], let X_I denote the collection of coordinates X_i, i\in I, and let \bar X_I denote the collection of coordinates X_i, i\notin I. We denote by Q_I(x_I|\bar x_I) the joint conditional density function of X_I, given \bar X_I. We prove measure concentration for q^n in the case when, for an appropriate class of sets I, (i) the conditional densities Q_I(x_I|\bar x_I), as functions of x_I, uniformly satisfy a logarithmic Sobolev inequality and (ii) these conditional densities also satisfy a contractivity condition related to Dobrushin and Shlosman's strong mixing condition.Comment: Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Probability (http://www.imstat.org/aop/) at http://dx.doi.org/10.1214/00911790400000070

    Framing the Game: Objections to Bapat’s Game-Theoretic Modeling of the Afghan Surge

    Get PDF
    In a recently published article in the prestigious journal Foreign Policy Analysis, Navin A. Bapat uses a rationalist approach to explain key bargaining processes related to the Afghanistan conflict, concluding that “the Afghan mission may continue for political reasons until it is impossible to sustain militarily.” The article captures the essence of the strategic situation in Afghanistan: the losing dynamic involved. This brief commentary in response is an attempt to shed light on where the tenets of Bapat’s game-theoretic model may be erroneous, even while the model does produce conclusions that appear valid overall

    A National Model Faces New Challenges: The New York City Campaign Finance System and the 2013 Elections

    Get PDF
    • 

    corecore