Alcuin's sequence

From formulasearchengine
Jump to navigation Jump to search

In mathematics, a Kolmogorov automorphism, K-automorphism, K-shift or K-system is an invertible, measure-preserving automorphism defined on a standard probability space that obeys Kolmogorov's zero-one law.[1] All Bernoulli automorphisms are K-automorphisms (one says they have the K-property), but not vice versa. Many ergodic dynamical systems have been shown to have the K-property, although more recent research has shown that many of these are in fact Bernoulli automorphisms.

Although the definition of the K-property seems reasonably general, it stands in sharp distinction to the Bernoulli automorphism. In particular, the Ornstein isomorphism theorem does not apply to K-systems, and so the entropy is not sufficient to classify such systems – there exist uncountably many non-isomorphic K-systems with the same entropy. In essence, the collection of K-systems is large, messy and uncategorized; whereas the B-automorphisms are 'completely' described by Ornstein theory.

Formal definition

Let (X,,μ) be a standard probability space, and let T be an invertible, measure-preserving transformation. Then T is called a K-automorphism, K-transform or K-shift, if there exists a sub-sigma algebra 𝒦 such that the following three properties hold:

(1) 𝒦T𝒦
(2) n=0Tn𝒦=
(3) n=0Tn𝒦={X,}

Here, the symbol is the join of sigma algebras, while is set intersection. The equality should be understood as holding almost everywhere, that is, differing at most on a set of measure zero.

Properties

Assuming that the sigma algebra is not trivial, that is, if {X,}, then 𝒦T𝒦. It follows that K-automorphisms are strong mixing.

All Bernoulli automorphisms are K-automorphisms, but not vice-versa.

References

43 year old Petroleum Engineer Harry from Deep River, usually spends time with hobbies and interests like renting movies, property developers in singapore new condominium and vehicle racing. Constantly enjoys going to destinations like Camino Real de Tierra Adentro.

Further reading

  1. Peter Walters, An Introduction to Ergodic Theory, (1982) Springer-Verlag ISBN 0-387-90599-5