Equidistribution Measures of infinite entropy for Transcendental Functions

Abstract

In the 1980s Lyubich and Freire-Lopes-Mañé proved that for any rational function of degree d \geq 2, both preimages and periodic points equidistribute to the unique measure of maximal entropy log(d). Their results provide a fundamental understanding of the dynamics of iterated rational functions, and have since been generalized to many different contexts, including classes of higher-dimensional polynomial and rational maps. In the current paper we depart from the algebraic category and aim to prove analogous statements for transcendental functions in the complex plane, which have infinite topological entropy. We introduce two different methods for constructing invariant measures in the transcendental setting, namely via embedded symbolic dynamical systems and via transfer operators associated to suitably chosen weights. In the latter case we isolate three properties of the weights -normality, tightness, and irreducibility- which together imply convergence to an invariant measure. We provide examples for each method, given by three classes of transcendental entire functions: disjoint-type maps, strongly polynomial-like maps, and a class of maps inspired by Baker's construction of multiply connected wandering domains and by Bishop's construction of Julia sets of Hausdorff dimension 1, which we call Baker-Bishop maps. For each of these classes we prove that with respect to carefully chosen weights, preimages equidistribute to an invariant mixing probability measure of infinite entropy. For Baker-Bishop maps and disjoint-type maps we also prove equidistribution of periodic points. In contrast to the rational setting, the measures we construct are not unique: by varying the weights one obtains infinitely many distinct measures.