Showing papers by "Amir Dembo published in 2003"

Spectral measure of large random Hankel, Markov and Toeplitz matrices

Abstract: We study the limiting spectral measure of large symmetric random matrices of linear algebraic structure. For Hankel and Toeplitz matrices generated by i.i.d. random variables $\{X_k\}$ of unit variance, and for symmetric Markov matrices generated by i.i.d. random variables $\{X_{ij}\}_{j>i}$ of zero mean and unit variance, scaling the eigenvalues by $\sqrt{n}$ we prove the almost sure, weak convergence of the spectral measures to universal, nonrandom, symmetric distributions $\gamma_H$, $\gamma_M$ and $\gamma_T$ of unbounded support. The moments of $\gamma_H$ and $\gamma_T$ are the sum of volumes of solids related to Eulerian numbers, whereas $\gamma_M$ has a bounded smooth density given by the free convolution of the semicircle and normal densities. For symmetric Markov matrices generated by i.i.d. random variables $\{X_{ij}\}_{j>i}$ of mean $m$ and finite variance, scaling the eigenvalues by ${n}$ we prove the almost sure, weak convergence of the spectral measures to the atomic measure at $-m$. If $m=0$, and the fourth moment is finite, we prove that the spectral norm of $\mathbf {M}_n$ scaled by $\sqrt{2n\log n}$ converges almost surely to 1.

Late points for random walks in two dimensions

Abstract: Let $\mathcal{T}_n(x)$ denote the time of first visit of a point $x$ on the lattice torus $\mathbb {Z}_n^2=\mathbb{Z}^2/n\mathbb{Z}^2$ by the simple random walk. The size of the set of $\alpha$, $n$-late points $\mathcal{L}_n(\alpha )=\{x\in \mathbb {Z}_n^2:\mathcal{T}_n(x)\geq \alpha \frac{4}{\pi}(n\log n)^2\}$ is approximately $n^{2(1-\alpha)}$, for $\alpha \in (0,1)$ [$\mathcal{L}_n(\alpha)$ is empty if $\alpha >1$ and $n$ is large enough]. These sets have interesting clustering and fractal properties: we show that for $\beta \in (0,1)$, a disc of radius $n^{\beta}$ centered at nonrandom $x$ typically contains about $n^{2\beta (1-\alpha /\beta ^2)}$ points from $\mathcal{L}_n(\alpha)$ (and is empty if $\beta <\sqrt{\alpha} $), whereas choosing the center $x$ of the disc uniformly in $\mathcal{L}_n(\alpha)$ boosts the typical number of $\alpha, n$-late points in it to $n^{2\beta (1-\alpha)}$. We also estimate the typical number of pairs of $\alpha$, $n$-late points within distance $n^{\beta}$ of each other; this typical number can be significantly smaller than the expected number of such pairs, calculated by Brummelhuis and Hilhorst [Phys. A 176 (1991) 387--408]. On the other hand, our results show that the number of ordered pairs of late points within distance $n^{\beta}$ of each other is larger than what one might predict by multiplying the total number of late points, by the number of late points in a disc of radius $n^{\beta}$ centered at a typical late point.

Late points for random walks in two dimensions

Abstract: Let $\mathscr{T}_{n}(x)$ denote the time of first visit of a point x on the lattice torus ℤn2=ℤ2/nℤ2 by the simple random walk. The size of the set of α, n-late points $ℒ_{n}(\alpha )=\{x\in \mathbb {Z}_{n}^{2}: \mathscr{T}_{n}(x)\geq \alpha \frac{4}{\pi}(n\log n)^{2}\}$ is approximately n2(1−α), for α∈(0,1) [ℒn(α) is empty if α>1 and n is large enough]. These sets have interesting clustering and fractal properties: we show that for β∈(0,1), a disc of radius nβ centered at nonrandom x typically contains about n2β(1−α/β2) points from ℒn(α) (and is empty if $\beta <\sqrt{ \alpha }$), whereas choosing the center x of the disc uniformly in ℒn(α) boosts the typical number of α,n-late points in it to n2β(1−α). We also estimate the typical number of pairs of α, n-late points within distance nβ of each other; this typical number can be significantly smaller than the expected number of such pairs, calculated by Brummelhuis and Hilhorst [Phys. A 176 (1991) 387–408]. On the other hand, our results show that the number of ordered pairs of late points within distance nβ of each other is larger than what one might predict by multiplying the total number of late points, by the number of late points in a disc of radius nβ centered at a typical late point.

Brownian Motion on Compact Manifolds: Cover Time and Late Points

Abstract: Let $M$ be a smooth, compact, connected Riemannian manifold of dimension $d>2$ and without boundary. Denote by $T(x,r)$ the hitting time of the ball of radius $r$ centered at $x$ by Brownian motion on $M$. Then, $C_r(M)=\sup_{x \in M} T(x,r)$ is the time it takes Brownian motion to come within $r$ of all points in $M$. We prove that $C_r(M)/(r^{2-d}|\log r|)$ tends to $\gamma_d V(M)$ almost surely as $r\to 0$, where $V(M)$ is the Riemannian volume of $M$. We also obtain the ``multi-fractal spectrum'' $f(\alpha)$ for ``late points'', i.e., the dimension of the set of $\alpha$-late points $x$ in $M$ for which $\limsup_{r\to 0} T(x,r)/ (r^{2-d}|\log r|) = \alpha >0$.

A large-deviation theorem for tree-indexed Markov chains

Abstract: Given a finite typed rooted tree $T$ with $n$ vertices, the {\em empirical subtree measure} is the uniform measure on the $n$ typed subtrees of $T$ formed by taking all descendants of a single vertex. We prove a large deviation principle in $n$, with explicit rate function, for the empirical subtree measures of multitype Galton-Watson trees conditioned to have exactly $n$ vertices. In the process, we extend the notions of shift-invariance and specific relative entropy--as typically understood for Markov fields on deterministic graphs such as $\mathbb Z^d$--to Markov fields on random trees. We also develop single-generation empirical measure large deviation principles for a more general class of random trees including trees sampled uniformly from the set of all trees with $n$ vertices.