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Ariel Rapaport

Publications and source records attributed to Ariel Rapaport.

21 records · Page 2Linked to original sources

On the Hausdorff and packing measures of slices of dynamically defined sets

Let $1\le m m$. We study the a.s. values of the $s-m$-dimensional Hausdorff and packing measures of $K\cap V$, where $V$ is a typical $n-m$-dimensional affine subspace. For $0<ρ<\frac{1}{2}$ let $C_ρ\subset[0,1]$ be the attractor of the IFS $\{f_{ρ,1},f_{ρ,2}\}$, where $f_{ρ,1}(t)=ρ\cdot t$ and $f_{ρ,2}(t)=ρ\cdot t+1-ρ$ for each $t\in\mathbb{R}$. We show that for certain numbers $0<a,b<\frac{1}{2}$, for instance $a=\frac{1}{4}$ and $b=\frac{1}{3}$, if $K=C_{a}\times C_{b}$ then typically we have $\mathcal{H}^{s-m}(K\cap V)=0$.

math.DS↗

Compound Poisson statistics in conventional and nonconventional setups

Given a periodic point $ω$ in a $ψ$-mixing shift with countable alphabet, the sequence $\{S_{n}\}$ of random variables counting the number of multiple returns to shrinking cylindrical neighborhoods of $ω$ is considered. Necessary and sufficient conditions for the convergence in distribution of $\{S_{n}\}$ are obtained, and it is shown that the limit is a Polya-Aeppli distribution. A global condition on the shift system, which guarantees the convergence in distribution of $\{S_{n}\}$ for every periodic point, is introduced. This condition is used to derive results for $f$-expansions and Gibbs measures. Results are also obtained concerning the possible limit distribution of sub-sequences $\{S_{n_{k}}\}$. A family of examples in which there is no convergence is presented. We exhibit also an example for which the limit distribution is pure Poissonian.

math.PR↗

Poisson and Compound Poisson Approximations in a Nonconventional Setup

We show that for all $ψ$-mixing shifts distributions of the numbers of multiple recurrencies to shrinking cylindrical neighborhoods of all points are close either to Poisson or to compound Poisson distributions. We also describe completely the asymptotic behavior of these distributions.

math.PR↗