Measure-preserving Dynamical System

In mathematics, a measure-preserving dynamical system is an object of study in the abstract formulation of ergodic theory. It is defined as a probability space and a measure-preserving transformation on it. In more detail, it is a system
(X, \mathcal{B}, T, m)
with the following structure:
X is a set,
\mathcal{B} is a \sigma-algebra over X,
m:\mathcal{B}\rightarrow0,1 is a probability measure, so that m(X)=1, and
T:X\rightarrow X is a measurable transformation which preserves the measure m, i. e. each measurable A\subseteq X satisfies
m(T^{-1}A)=m(A).
For example, m could be the normalised angle measure dθ/2π on the unit circle, and T a rotation. One may wonder why the seemingly simpler identity
m(T(A))=m(A)
is not used. Here is the problem: suppose T : 11 is defined by T(x) = (4x mod 1), i.e., T(x) is the "fractional part" of 4x. Then the interval 0.02 is mapped to an interval four times as long as itself, but nonetheless the measure of T −1( 0.08 ) = 0.020.2520.5020.752 is no different from the measure of 0.08. That hypothesis suffices for the proofs of ergodic theorems. This transformation is measure-preserving.

 

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