2,682 research outputs found

    On the scaling of the chemical distance in long-range percolation models

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    We consider the (unoriented) long-range percolation on Z^d in dimensions d\ge1, where distinct sites x,y\in Z^d get connected with probability p_{xy}\in[0,1]. Assuming p_{xy}=|x-y|^{-s+o(1)} as |x-y|\to\infty, where s>0 and |\cdot| is a norm distance on Z^d, and supposing that the resulting random graph contains an infinite connected component C_{\infty}, we let D(x,y) be the graph distance between x and y measured on C_{\infty}. Our main result is that, for s\in(d,2d), D(x,y)=(\log|x-y|)^{\Delta+o(1)},\qquad x,y\in C_{\infty}, |x-y|\to\infty, where \Delta^{-1} is the binary logarithm of 2d/s and o(1) is a quantity tending to zero in probability as |x-y|\to\infty. Besides its interest for general percolation theory, this result sheds some light on a question that has recently surfaced in the context of ``small-world'' phenomena. As part of the proof we also establish tight bounds on the probability that the largest connected component in a finite box contains a positive fraction of all sites in the box.Comment: Published at http://dx.doi.org/10.1214/009117904000000577 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Scaling limit for a class of gradient fields with nonconvex potentials

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    We consider gradient fields (Ο•x:x∈Zd)(\phi_x:x\in \mathbb{Z}^d) whose law takes the Gibbs--Boltzmann form Zβˆ’1exp⁑{βˆ’βˆ‘V(Ο•yβˆ’Ο•x)}Z^{-1}\exp\{-\sum_{}V(\phi_y-\phi_x)\}, where the sum runs over nearest neighbors. We assume that the potential VV admits the representation V(\eta):=-\log\int\varrho({d}\kappa)\exp\biggl[-{1/2}\kappa\et a^2\biggr], where Ο±\varrho is a positive measure with compact support in (0,∞)(0,\infty). Hence, the potential VV is symmetric, but nonconvex in general. While for strictly convex VV's, the translation-invariant, ergodic gradient Gibbs measures are completely characterized by their tilt, a nonconvex potential as above may lead to several ergodic gradient Gibbs measures with zero tilt. Still, every ergodic, zero-tilt gradient Gibbs measure for the potential VV above scales to a Gaussian free field.Comment: Published in at http://dx.doi.org/10.1214/10-AOP548 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Eigenvalue order statistics for random Schr\"odinger operators with doubly-exponential tails

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    We consider random Schr\"odinger operators of the form Ξ”+ΞΎ\Delta+\xi, where Ξ”\Delta is the lattice Laplacian on Zd\mathbb Z^d and ΞΎ\xi is an i.i.d. random field, and study the extreme order statistics of the eigenvalues for this operator restricted to large but finite subsets of Zd\mathbb Z^d. We show that for ΞΎ\xi with a doubly-exponential type of upper tail, the upper extreme order statistics of the eigenvalues falls into the Gumbel max-order class. The corresponding eigenfunctions are exponentially localized in regions where ΞΎ\xi takes large, and properly arranged, values. A new and self-contained argument is thus provided for Anderson localization at the spectral edge which permits a rather explicit description of the shape of the potential and the eigenfunctions. Our study serves as an input into the analysis of an associated parabolic Anderson problem.Comment: 36 page

    Forbidden gap argument for phase transitions proved by means of chessboard estimates

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    Chessboard estimates are one of the standard tools for proving phase coexistence in spin systems of physical interest. In this note we show that the method not only produces a point in the phase diagram where more than one Gibbs states coexist, but that it can also be used to rule out the existence of shift-ergodic states that differ significantly from those proved to exist. For models depending on a parameter (say, the temperature), this shows that the values of the conjugate thermodynamic quantity (the energy) inside the "transitional gap" are forbidden in all shift-ergodic Gibbs states. We point out several models where our result provides useful additional information concerning the set of possible thermodynamic equilibria.Comment: 26 page

    Quenched invariance principle for simple random walk on percolation clusters

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    We consider the simple random walk on the (unique) infinite cluster of super-critical bond percolation in Zd\Z^d with dβ‰₯2d\ge2. We prove that, for almost every percolation configuration, the path distribution of the walk converges weakly to that of non-degenerate, isotropic Brownian motion. Our analysis is based on the consideration of a harmonic deformation of the infinite cluster on which the random walk becomes a square-integrable martingale. The size of the deformation, expressed by the so called corrector, is estimated by means of ergodicity arguments.Comment: 38 pages (PTRF format) 4 figures. Version to appear in PTR

    Subdiffusive heat-kernel decay in four-dimensional i.i.d. random conductance models

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    We study the diagonal heat-kernel decay for the four-dimensional nearest-neighbor random walk (on Z4\Z^4) among i.i.d. random conductances that are positive, bounded from above but can have arbitrarily heavy tails at zero. It has been known that the quenched return probability \cmss P_\omega^{2n}(0,0) after 2n2n steps is at most C(Ο‰)nβˆ’2log⁑nC(\omega) n^{-2} \log n, but the best lower bound till now has been C(Ο‰)nβˆ’2C(\omega) n^{-2}. Here we will show that the log⁑n\log n term marks a real phenomenon by constructing an environment, for each sequence Ξ»nβ†’βˆž\lambda_n\to\infty, such that \cmss P_\omega^{2n}(0,0)\ge C(\omega)\log(n)n^{-2}/\lambda_n, with C(Ο‰)>0C(\omega)>0 a.s., along a deterministic subsequence of nn's. Notably, this holds simultaneously with a (non-degenerate) quenched invariance principle. As for the dβ‰₯5d\ge5 cases studied earlier, the source of the anomalous decay is a trapping phenomenon although the contribution is in this case collected from a whole range of spatial scales.Comment: 28 pages, version to appear in J. Lond. Math. So
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