Fourier series
We have seen that a measure-preserving transformation on a probability space induces an isometry of the space by composition. That is, if belongs to then so too does
and moreover .
We restrict now our attention to the special case where our probability space is equipped with Lebesgue measure . By paying the small price of working with complex instead of real-valued functions, we will produce an orthonormal basis of that will allow us to more easily verify dynamical properties of measure-preserving transformations on the unit interval.
An orthonormal basis
Write for the collection of functions that are Borel measurable and for which
where we identify two complex-valued functions if
holds. Next, define for each the function
for each . Since for each and each of the functions belongs to .
In dealing with complex-valued functions we must modify slightly the inner product we work with. Define
whenever belong to . With respect to this inner product we have
which is to say that the collection of functions is an orthonormal system. In fact it is a basis of in the sense that
for every in . Note that this is distinct from the meaning of basis in linear algebra: we are not asserting that every is a finite linear combination of functions from our orthonormal family; instead we are using the norm to say that
for every in .
Theorem
The form a basis of .
Proof:
We will take this for granted. The key ingredients in the proof are Bessel's inequality, the fact the continuous functions are dense in , and the fact that every continuous function on is a uniform limit of linear combinations of our orthonormal system. ▮
Ergodicity via Fourier series
Proposition
Every irrational rotation is ergodic.
Proof:
Write for some irrational . Fix in that is invariant. We can write
and calculate that
and conclude that for all . As is irrational we must have for all non-zero . Thus is constant. ▮
Proposition
The map on is ergodic.
Proof:
Fix in that is invariant. We can write
and calculate that
and conclude that for all . Calculating
it is not possible for to take the same non-zero value infinitely often. Thus for all and is constant. ▮
Discrete spectrum and mixing
For the irrational rotation each of the functions is an eigenfunction. We define the class of dynamical systems with this property.
Definition
A measure-preserving transformation on a probability space has discrete spectrum when has an orthonormal basis consisting of eigenfunctions.
Ergodic transformations with discrete spectrum can be modelled by systems that look like irrational rotations.
Theorem
If a measure-preserving transformation is ergodic and has discrete spectrum then it is isomorphic to a measure-preserving transformation on a compact, Abelian group defined by for some in with the property that is dense.
Can the doubling map be modelled by an irrational rotation? Perhaps it is, in disguise, a system with discrete spectrum. In fact, the doubling map is mixing and systems that are ergodic and mixing cannot have non-constant eigenfunctions.
Proposition
The doubling map on is mixing.
Proof:
Fix in . Write
and fix . There are such that
both hold. Write and respectively for the truncated sums above. Now
for all using the Hölder inequality. Choose with . For all we have
because only happens when and . Thus
for all and we are done. ▮
We can now distinguish the irrational rotation and the doubling map using the Koopman operator. Indeed, suppose that is an eigenfunction for the doubling map with eigenvalue . Then
whereas mixing gives
if because eigenfunctions with distinct eigenvalues are orthogonal. Thus which is not possible and has no eigenfunctions.