A corollary of the ergodic theorem

What's new 2018-08-02

Let ${(X,T,\mu)}$ be a measure-preserving system – a probability space ${(X,\mu)}$ equipped with a measure-preserving translation ${T}$ (which for simplicity of discussion we shall assume to be invertible). We will informally think of two points ${x,y}$ in this space as being “close” if ${y = T^n x}$ for some ${n}$ that is not too large; this allows one to distinguish between “local” structure at a point ${x}$ (in which one only looks at nearby points ${T^n x}$ for moderately large ${n}$ ) and “global” structure (in which one looks at the entire space ${X}$ ). The local/global distinction is also known as the time-averaged/space-averaged distinction in ergodic theory.

A measure-preserving system is said to be ergodic if all the invariant sets are either zero measure or full measure. An equivalent form of this statement is that any measurable function ${f: X \rightarrow {\bf R}}$ which is locally essentially constant in the sense that ${f(Tx) = f(x)}$ for ${\mu}$ -almost every ${x}$ , is necessarily globally essentially constant in the sense that there is a constant ${c}$ such that ${f(x) = c}$ for ${\mu}$ -almost every ${x}$ . A basic consequence of ergodicity is the mean ergodic theorem: if ${f \in L^2(X,\mu)}$ , then the averages ${x \mapsto \frac{1}{N} \sum_{n=1}^N f(T^n x)}$ converge in ${L^2}$ norm to the mean ${\int_X f\ d\mu}$ . (The mean ergodic theorem also applies to other ${L^p}$ spaces with ${1 < p < \infty}$ , though it is usually proven first in the Hilbert space ${L^2}$ .) Informally: in ergodic systems, time averages are asymptotically equal to space averages. Specialising to the case of indicator functions, this implies in particular that ${\frac{1}{N} \sum_{n=1}^N \mu( E \cap T^n E)}$ converges to ${\mu(E)^2}$ for any measurable set ${E}$ .

In this short note I would like to use the mean ergodic theorem to show that ergodic systems also have the property that “somewhat locally constant” functions are necessarily “somewhat globally constant”; this is not a deep observation, and probably already in the literature, but I found it a cute statement that I had not previously seen. More precisely:

Corollary 1 Let ${(X,T,\mu)}$ be an ergodic measure-preserving system, and let ${f: X \rightarrow {\bf R}}$ be measurable. Suppose that

$\displaystyle \limsup_{N \rightarrow \infty} \frac{1}{N} \sum_{n=1}^N \mu( \{ x \in X: f(T^n x) = f(x) \} ) \geq \delta \ \ \ \ \ (1)$
for some ${0 \leq \delta \leq 1}$ . Then there exists a constant ${c}$ such that ${f(x)=c}$ for ${x}$ in a set of measure at least ${\delta}$ .

Informally: if ${f}$ is locally constant on pairs ${x, T^n x}$ at least ${\delta}$ of the time, then ${f}$ is globally constant at least ${\delta}$ of the time. Of course the claim fails if the ergodicity hypothesis is dropped, as one can simply take ${f}$ to be an invariant function that is not essentially constant, such as the indicator function of an invariant set of intermediate measure. This corollary can be viewed as a manifestation of the general principle that ergodic systems have the same “global” (or “space-averaged”) behaviour as “local” (or “time-averaged”) behaviour, in contrast to non-ergodic systems in which local properties do not automatically transfer over to their global counterparts.

Proof: By composing ${f}$ with (say) the tangent function, we may assume without loss of generality that ${f}$ is bounded. Let ${k>0}$ , and partition ${X}$ as ${\bigcup_{m \in {\bf Z}} E_{m,k}}$ , where ${E_{m,k}}$ is the level set

$\displaystyle E_{m,k} := \{ x \in X: m 2^{-k} \leq f(x) < (m+1) 2^{-k} \}.$

For each ${k}$ , only finitely many of the ${E_{m,k}}$ are non-empty. By (1), one has

$\displaystyle \limsup_{N \rightarrow \infty} \sum_m \frac{1}{N} \sum_{n=1}^N \mu( E_{m,k} \cap T^n E_{m,k} ) \geq \delta.$

Using the ergodic theorem, we conclude that

$\displaystyle \sum_m \mu( E_{m,k} )^2 \geq \delta.$

On the other hand, ${\sum_m \mu(E_{m,k}) = 1}$ . Thus there exists ${m_k}$ such that ${\mu(E_{m_k,k}) \geq \delta}$ , thus

$\displaystyle \mu( \{ x \in X: m_k 2^{-k} \leq f(x) < (m_k+1) 2^{-k} \} ) \geq \delta.$

By the Bolzano-Weierstrass theorem, we may pass to a subsequence where ${m_k 2^{-k}}$ converges to a limit ${c}$ , then we have

$\displaystyle \mu( \{ x \in X: c-2^{-k} \leq f(x) \leq c+2^{-k} \}) \geq \delta$

for infinitely many ${k}$ , and hence

$\displaystyle \mu( \{ x \in X: f(x) = c \}) \geq \delta.$

The claim follows. $\Box$