Interior points and Lebesgue measure of overlapping Mandelbrot percolation sets

We consider a special one-parameter family of d -dimensional random, homogeneous self-similar iterated function systems (IFSs) satisfying the finite type condition. The object of our study is the positivity of Lebesgue measure and the existence of interior points in these random sets and in particular, the existence of an interesting parameter interval where the attractor has positive Lebesgue measure but empty interior, almost surely conditioned on the attractor not being empty. We give a sharp bound on the critical probability for the case of positive Lebesgue measure using the theory of multitype branching processes in random environments. Further, in some special cases, we give a bound on the critical probability for the existence of interior points. Using a recent result of Tom Rush, we also provide a family of such random sets where there exists a parameter interval for which the corresponding attractor has a positive Lebesgue measure, but empty interior almost surely conditioned on the attractor not being empty.

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Publication Details

Journal
Stochastic Processes and their Applications
Published
2026-02-26
DOI
https://doi.org/10.1016/j.spa.2026.104900
Primary Topic
Stochastic processes and statistical mechanics
Type
article
Field-Weighted Citation Impact
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article

Interior points and Lebesgue measure of overlapping Mandelbrot percolation sets

Vilma Orgoványi, Károly Simon
Stochastic Processes and their Applications
Stochastic processes and statistical mechanics
article

Interior points and Lebesgue measure of overlapping Mandelbrot percolation sets

Vilma Orgoványi, Károly Simon
article en

Abstract

We consider a special one-parameter family of d -dimensional random, homogeneous self-similar iterated function systems (IFSs) satisfying the finite type condition. The object of our study is the positivity of Lebesgue measure and the existence of interior points in these random sets and in particular, the existence of an interesting parameter interval where the attractor has positive Lebesgue measure but empty interior, almost surely conditioned on the attractor not being empty. We give a sharp bound on the critical probability for the case of positive Lebesgue measure using the theory of multitype branching processes in random environments. Further, in some special cases, we give a bound on the critical probability for the existence of interior points. Using a recent result of Tom Rush, we also provide a family of such random sets where there exists a parameter interval for which the corresponding attractor has a positive Lebesgue measure, but empty interior almost surely conditioned on the attractor not being empty.

Stochastic Processes and their ApplicationsVol. 196
Budapest University of Technology and Economics (HU)
Openalex Percentile: Top 36%
Stochastic processes and statistical mechanics
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