We study the geometric properties of random multiplicative cascade measures defined on self-similar sets. We show that such measures and their projections and sections are almost surely exact dimensional, generalizing a result of Feng and Hu's for self-similar measures. This, together with a compact group extension argument, enables us to generalize Hochman and Shmerkin's theorems on projections of deterministic self-similar measures to these random measures without requiring any separation conditions on the underlying sets. We give applications to self-similar sets and fractal percolation, including new results on projections, C1-images and distance sets
We show that for families of measures on Euclidean space which satisfy an ergodic-theoretic form of ...
New metrics are introduced in the space of random measures and are applied, with various modificatio...
The authors define a class of random measures, spatially independent martingales, which we view as a...
We study the geometric properties of random multiplicative cascade measures defined on self-similar ...
We survey some recent results on the dimension of orthogonal projections of self-similar sets and of...
AbstractFractals and measures are often defined in a constructive way. In this paper, we give the co...
A contractive similarity is a function which preserves the geometry of a object but shrinks it down ...
We prove preservation of L q dimensions (for 1 < q ≤ 2) under all orthogonal projections for a class...
We survey some recent results on the dimension of orthogonal projections of self-similar sets and of...
We introduce a technique that uses projection properties of fractal percolation to establish dimensi...
We introduce a technique that uses projection properties of fractal percolation to establish dimensi...
AbstractWe have given several necessary and sufficient conditions for statistically self-similar set...
We show that for families of measures on Euclidean space which satisfy an ergodic-theoretic form of ...
Abstract. The purpose of this note is to calculate the almost sure Hausdorff dimension of uniformly ...
We show that for families of measures on Euclidean space which satisfy an ergodic-theoretic form of ...
We show that for families of measures on Euclidean space which satisfy an ergodic-theoretic form of ...
New metrics are introduced in the space of random measures and are applied, with various modificatio...
The authors define a class of random measures, spatially independent martingales, which we view as a...
We study the geometric properties of random multiplicative cascade measures defined on self-similar ...
We survey some recent results on the dimension of orthogonal projections of self-similar sets and of...
AbstractFractals and measures are often defined in a constructive way. In this paper, we give the co...
A contractive similarity is a function which preserves the geometry of a object but shrinks it down ...
We prove preservation of L q dimensions (for 1 < q ≤ 2) under all orthogonal projections for a class...
We survey some recent results on the dimension of orthogonal projections of self-similar sets and of...
We introduce a technique that uses projection properties of fractal percolation to establish dimensi...
We introduce a technique that uses projection properties of fractal percolation to establish dimensi...
AbstractWe have given several necessary and sufficient conditions for statistically self-similar set...
We show that for families of measures on Euclidean space which satisfy an ergodic-theoretic form of ...
Abstract. The purpose of this note is to calculate the almost sure Hausdorff dimension of uniformly ...
We show that for families of measures on Euclidean space which satisfy an ergodic-theoretic form of ...
We show that for families of measures on Euclidean space which satisfy an ergodic-theoretic form of ...
New metrics are introduced in the space of random measures and are applied, with various modificatio...
The authors define a class of random measures, spatially independent martingales, which we view as a...