Entropy of probability kernels from the backwards tail boundary
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 . 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.
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