English

Overlap functions for measures in conformal iterated function systems

Dynamical Systems 2016-01-27 v1 Metric Geometry Probability

Abstract

We study conformal iterated function systems (IFS) S={ϕi}iI\mathcal S = \{\phi_i\}_{i \in I} with arbitrary overlaps, and measures μ\mu on limit sets Λ\Lambda, which are projections of equilibrium measures μ^\hat \mu with respect to a certain lift map Φ\Phi on ΣI+×Λ\Sigma_I^+ \times \Lambda. No type of Open Set Condition is assumed. We introduce a notion of overlap function and overlap number for such a measure μ^\hat \mu with respect to S\mathcal S; and, in particular a notion of (topological) overlap number o(S)o(\mathcal S). These notions take in consideration the nn-chains between points in the limit set. We prove that o(S,μ^)o(\mathcal S, \hat \mu) is related to a conditional entropy of μ^\hat \mu with respect to the lift Φ\Phi. Various types of projections to Λ\Lambda of invariant measures are studied. We obtain upper estimates for the Hausdorff dimension HD(μ)HD(\mu) of μ\mu on Λ\Lambda, by using pressure functions and o(S,μ^)o(\mathcal S, \hat \mu). In particular, this applies to projections of Bernoulli measures on ΣI+\Sigma_I^+. Next, we apply the results to Bernoulli convolutions νλ\nu_\lambda for λ(12,1)\lambda \in (\frac 12, 1), which correspond to self-similar measures determined by composing, with equal probabilities, the contractions of an IFS with overlaps Sλ\mathcal S_\lambda. We prove that for all λ(12,1)\lambda \in (\frac 12, 1), there exists a relation between HD(νλ)HD(\nu_\lambda) and the overlap number o(Sλ)o(\mathcal S_\lambda). The number o(Sλ)o(\mathcal S_\lambda) is approximated with integrals on Σ2+\Sigma_2^+ with respect to the uniform Bernoulli measure ν(12,12)\nu_{(\frac 12, \frac 12)}. We also estimate o(Sλ)o(\mathcal S_\lambda) for certain values of λ\lambda.

Keywords

Cite

@article{arxiv.1507.08871,
  title  = {Overlap functions for measures in conformal iterated function systems},
  author = {Eugen Mihailescu and Mariusz Urbanski},
  journal= {arXiv preprint arXiv:1507.08871},
  year   = {2016}
}
R2 v1 2026-06-22T10:23:24.987Z