Let ( X , B , μ ) {\displaystyle (X,{\mathcal {B}},\mu )} be a standard probability space, and let T {\displaystyle T} be an invertible, measure-preserving transformation. Then T {\displaystyle T} is called a K-automorphism, K-transform or K-shift, if there exists a sub-sigma algebra K ⊂ B {\displaystyle {\mathcal {K}}\subset {\mathcal {B}}} such that the following three properties hold:
Here, the symbol ∨ {\displaystyle \vee } is the join of sigma algebras, while ∩ {\displaystyle \cap } is set intersection. The equality should be understood as holding almost everywhere, that is, differing at most on a set of measure zero.
Assuming that the sigma algebra is not trivial, that is, if B ≠ { X , ∅ } {\displaystyle {\mathcal {B}}\neq \{X,\varnothing \}} , then K ≠ T K . {\displaystyle {\mathcal {K}}\neq T{\mathcal {K}}.} It follows that K-automorphisms are strong mixing.
All Bernoulli automorphisms are K-automorphisms, but not vice versa.
Kolmogorov automorphisms are precisely the natural extensions of exact endomorphisms,2 i.e. mappings T {\displaystyle T} for which ⋂ n = 0 ∞ T − n M {\displaystyle \bigcap _{n=0}^{\infty }T^{-n}{\mathcal {M}}} consists of measure-zero sets or their complements, where M {\displaystyle {\mathcal {M}}} is the sigma-algebra of measureable sets,.
Peter Walters, An Introduction to Ergodic Theory, (1982) Springer-Verlag ISBN 0-387-90599-5 /wiki/ISBN_(identifier) ↩
V. A. Rohlin, Exact endomorphisms of Lebesgue spaces, Amer. Math. Soc. Transl., Series 2, 39 (1964), 1-36. ↩