English

Entropy of probability kernels from the backwards tail boundary

Dynamical Systems 2015-08-25 v2 Probability

Abstract

A number of recent works have sought to generalize the Kolmogorov-Sinai entropy of probability-preserving transformations to the setting of Markov operators acting on the integrable functions on a probability space (X,μ)(X,\mu). These have culminated in a proof by Downarovicz and Frej that these definitions all coincide, and that the resulting quantity is uniquely characterized by certain properties. On the other hand, Makarov has shown that this `operator entropy' is always dominated by the Kolmogorov-Sinai entropy of a classical system that may be constructed from a Markov operator, and that these numbers coincide under certain extra assumptions. This note proves that equality in all cases.

Keywords

Cite

@article{arxiv.1405.5121,
  title  = {Entropy of probability kernels from the backwards tail boundary},
  author = {Tim Austin},
  journal= {arXiv preprint arXiv:1405.5121},
  year   = {2015}
}

Comments

10 pages; [v2:] slight corrections based on referee suggestions

R2 v1 2026-06-22T04:19:03.657Z