30 research outputs found

    On the positive eigenvalues and eigenvectors of a non-negative matrix

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    The paper develops the general theory for the items in the title, assuming that the matrix is countable and cofinal.Comment: Version 2 allows the matrix to have zero row(s) and rows with infinitely many non-zero entries. In addition the introduction has been rewritte

    Hausdorff dimension of operator semistable L\'evy processes

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    Let X={X(t)}t0X=\{X(t)\}_{t\geq0} be an operator semistable L\'evy process in \rd with exponent EE, where EE is an invertible linear operator on \rd and XX is semi-selfsimilar with respect to EE. By refining arguments given in Meerschaert and Xiao \cite{MX} for the special case of an operator stable (selfsimilar) L\'evy process, for an arbitrary Borel set B\subseteq\rr_+ we determine the Hausdorff dimension of the partial range X(B)X(B) in terms of the real parts of the eigenvalues of EE and the Hausdorff dimension of BB.Comment: 23 page

    Convergence of the all-time supremum of a L\'evy process in the heavy-traffic regime

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    In this paper we derive a technique of obtaining limit theorems for suprema of L\'evy processes from their random walk counterparts. For each a>0a>0, let {Yn(a):n1}\{Y^{(a)}_n:n\ge 1\} be a sequence of independent and identically distributed random variables and {Xt(a):t0}\{X^{(a)}_t:t\ge 0\} be a L\'evy processes such that X1(a)=dY1(a)X_1^{(a)}\stackrel{d}{=} Y_1^{(a)}, EX1(a)<0\mathbb E X_1^{(a)}<0 and EX1(a)0\mathbb E X_1^{(a)}\uparrow0 as a0a\downarrow0. Let Sn(a)=k=1nYk(a)S^{(a)}_n=\sum_{k=1}^n Y^{(a)}_k. Then, under some mild assumptions, Δ(a)maxn0Sn(a)dR    Δ(a)supt0Xt(a)dR\Delta(a)\max_{n\ge 0} S_n^{(a)}\stackrel{d}{\to} R\iff\Delta(a)\sup_{t\ge 0} X^{(a)}_t\stackrel{d}{\to} R, for some random variable RR and some function Δ()\Delta(\cdot). We utilize this result to present a number of limit theorems for suprema of L\'evy processes in the heavy-traffic regime

    On infinite-volume mixing

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    In the context of the long-standing issue of mixing in infinite ergodic theory, we introduce the idea of mixing for observables possessing an infinite-volume average. The idea is borrowed from statistical mechanics and appears to be relevant, at least for extended systems with a direct physical interpretation. We discuss the pros and cons of a few mathematical definitions that can be devised, testing them on a prototypical class of infinite measure-preserving dynamical systems, namely, the random walks.Comment: 34 pages, final version accepted by Communications in Mathematical Physics (some changes in Sect. 3 -- Prop. 3.1 in previous version was partially incorrect
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