ERGODIC MEASURES WITH INFINITE ENTROPY

In Section 3 we present the proof that in the case which is of relevance to this paper this determinantal process converges to the discrete sine-process, and using the

In [17] and later in [6–8] the existence of such measures was investigated for topological Markov chains and Markov expanding dynamical systems with holes.. More recently,

invariant and ergodic by suitable linear subspaces. Thus the dichotomy d) is a special case of our

Let E f denote the set of ergodic, f -invariant Borel probability mea- sures, Per f the set of invariant measures supported on a single periodic orbit, and O f denote the set

Using the work of Olshanski and Vershik [6] and Rabaoui [10], [11], we give a sufficient condition, called “radial boundedness” of a matrix, for weak pre- compactness of its family

In the natural context of ergodic optimization, we provide a short proof of the assertion that the maximizing measure of a generic continuous function has zero

Two main ingredients for proving the ergodicity of µ s are: the mutual singularity between all measures µ s ’s (derived from the strong law of large numbers) and an a priori

Structure of the paper After this introduction, Section 2 presents the main well-known tools from optimal transport theory (Wasserstein distances, geodesic interpolation.. The