In Lecture 11, we studied compact measure-preserving systems – those systems in which every function was almost periodic, which meant that their orbit was precompact in the topology. Among other things, we were able to easily establish the Furstenberg recurrence theorem (Theorem 1 from Lecture 11) for such systems.
In this lecture, we generalise these results to a “relative” or “conditional” setting, in which we study systems which are compact relative to some factor of . Such systems are to compact systems as isometric extensions are to isometric systems in topological dynamics. The main result we establish here is that the Furstenberg recurrence theorem holds for such compact extensions whenever the theorem holds for the base. The proof is essentially the same as in the compact case; the main new trick is to not to work in the Hilbert spaces over the complex numbers, but rather in the Hilbert module over the (commutative) von Neumann algebra . (Modules are to rings as vector spaces are to fields.) Because of the compact nature of the extension, it turns out that results from topological dynamics (and in particular, van der Waerden’s theorem) can be exploited to good effect in this argument.
[Note: this operator-algebraic approach is not the only way to understand these extensions; one can also proceed by disintegrating into fibre measures for almost every and working fibre by fibre. We will discuss the connection between the two approaches below.]
— Hilbert modules —
Let be a measure-preserving system, and let be a factor map, i.e. a morphism from X to another system . The algebra can be viewed (using ) as a subalgebra of ; indeed, it is isomorphic to , where is the pullback of by .
Example 1. Throughout these notes we shall use the skew shift as our running example. Thus, in this example, with shift for some fixed (which can be either rational or irrational), with shift , with factor map . In this case, can be thought of (modulo equivalence on null sets, of course) as the space of bounded functions on which depend only on the first variable.
Example 2. Another (rather trivial) example is when the factor system Y is simply a point. In this case, is the space of constants and can be identified with . At the opposite extreme, another example is when Y is equal to X. It is instructive to see how all of the concepts behave in each of these two extreme cases, as well as the typical intermediate case presented in Example 1.
The idea here will be to try to “relativise” the machinery of Hilbert spaces over to that of Hilbert modules over . Roughly speaking, all concepts which used to be complex or real-valued (e.g. inner products, norms, coefficients, etc.) will now take values in the algebra . The following table depicts the various concepts that will be relativised:
|Absolute / unconditional||Relative / conditional|
|Inner product||Conditional inner product|
|Hilbert space||Hilbert module|
|Finite-dimensional subspace||Finitely generated module|
|Almost periodic function||Conditionally almost periodic function|
|Compact system||Compact extension|
|Hilbert-Schmidt operator||Conditionally Hilbert-Schmidt operator|
|Weakly mixing function||Conditionally weakly mixing function|
|Weakly mixing system||Weakly mixing extension|
(The last few notions in this table will be covered in the next lecture, rather than this one.)
Remark 1. In information-theoretic terms, one can view Y as representing all the observables in the system X that have already been “measured” in some sense, so that it is now permissible to allow one’s “constants” to depend on that data, and only study the remaining information present in X conditioning on the observed values in Y. Note though that once we activate the shift map T, the data in Y will similarly shift (by S), and so the various fibres of can interact with each other in a non-trivial manner, so one should take some caution in applying information-theoretic intuition to this setting.
We have already seen that the factor Y induces a sub--algebra of . We therefore have a conditional expectation map defined for all absolutely integrable f by the formula
In general, this expectation only lies in , though for the functions we shall eventually study, the expectation will always lie in when needed.
As stated in the table, conditional expectation will play the role in the conditional setting that the unconditional expectation plays in the unconditional setting. Note though that the conditional expectation takes values in the algebra rather than in the complex numbers. We recall that conditional expectation is linear over this algebra, thus
for all absolutely integrable f, g and all .
Example 3. Continuing Example 1, we see that for any absolutely integrable f on , we have almost everywhere.
Let be the space of all such that the conditional norm
lies in (rather than merely in , which it does automatically). Thus for instance we have the inclusions
The space is easily seen to be a vector space over , and moreover (thanks to (2)) is a module over .
Exercise 1. If we introduce the inner product
(which, initially, is only in ), establish the pointwise Cauchy-Schwarz inequality
Example 4. Continuing Examples 1 and 3, consists (modulo null set equivalence) of all measurable functions such that is bounded a.e. in y, with the relative inner product
defined a.e. in y. Observe in this case that the relative Cauchy-Schwarz inequality (6) follows easily from the standard Cauchy-Schwarz inequality.
Exercise 2. Show that the function is a norm on , which turns that space into a Banach space. (Hint: you may need to “relativise” one of the standard proofs that is complete. You may also want to start with the skew shift example to build some intuition.) Because of this completeness, we refer to as a Hilbert module over .
As is a morphism, one can easily check the intertwining relationship
for all and integers n. As a consequence we see that the map T (and all of its powers) preserves the space , and furthermore is conditionally unitary in the sense that
for all and integers n.
In the Hilbert space one can create finite dimensional subspaces for any . Inside such subspaces we can create the bounded finite-dimensional zonotopes . Observe (from the Heine-Borel theorem) that a subset E of is precompact if and only if it can be approximated by finite-dimensional zonotopes in the sense that for every , there exists a finite-dimensional zonotope Z of such that E lies within the neighbourhood of Z.
Remark 2. There is nothing special about zonotopes here; just about any family of bounded finite-dimensional objects would suffice for this purpose. In fact, it seems to be slightly better (for the purposes of quantitative analysis, and in particular in controlling the dependence on dimension d) to work instead with octahedra, in which the constraint is replaced by ; see this paper of mine in which this perspective is used.
Inspired by this, let us make some definitions. A finitely generated module of is any submodule of of the form , where . Inside such a module we can define a finitely generated module zonotope .
Definition 1. A subset E of is said to be conditionally precompact if for every , there exists a finitely generated module zonotope Z of such that E lies within the -neighbourhood of Z (using the norm from Exercise 2).
A function is said to be conditionally almost periodic if its orbit is conditionally precompact.
A function is said to be conditionally almost periodic in measure if every there exists a set E in Y of measure at most such that is conditionally almost periodic.
The system X is said to be a compact extension of Y if every function in is conditionally almost periodic in measure.
Example 5. Any bounded subset of is conditionally precompact (though note that it need not be precompact in the topological sense, using the topology from Exercise 2). In particular, every function in is conditionally almost periodic.
Example 6. Every system is a compact extension of itself. A system is a compact extension of a point if and only if it is a compact system.
Example 7. Consider the skew shift (Examples 1, 3, 4), and consider the orbit of the function . A computation shows that
which reveals (for irrational) that f is not almost periodic in the unconditional sense. However, observe that all the shifts lie in the zonotope generated by a single generator f, and so f is conditionally almost periodic.
Exercise 3. Consider the skew shift (Examples 1,3,4,7). Show that a sequence is conditionally precompact if and only if the sequences are precompact in (with the usual Lebesgue measure) for almost every y.
Exercise 4. Show that the space of conditionally almost periodic functions in is a shift-invariant module, i.e. it is closed under addition, under multiplication by elements of , and under powers of the shift operator.
Exercise 5. Consider the skew shift (Examples 1,3,4,7 and Exercise 3) with irrational, and let be the function defined by setting whenever and . Show that f is conditionally almost periodic in measure, but not conditionally almost periodic. Thus the two notions can be distinct even for bounded functions (a subtlety that does not arise in the unconditional setting).
Exercise 6. Let denote the collection of all measurable sets E in X such that is conditionally almost periodic in measure. Show that is a shift-invariant sub--algebra of that contains , and that a function is conditionally almost periodic in measure if and only if it is -measurable. (In particular, is the maximal compact extension of Y.) [Hint: you may need to truncate the generators of various module zonotopes to be in rather than .]
Exercise 7. Show that the skew shift (Examples 1, 3, 4, 7 and Exercises 3,5) is a compact extension of the circle shift. (Hint: Use Example 7 and Exercise 6. Alternatively, approximate a function on the skew torus by its vertical Fourier expansions. For each fixed horizontal coordinate y, the partial sums of these vertical Fourier series converge (in the vertical sense) to the original function, pointwise in y. Now apply Egorov’s theorem.)
Exercise 8. Show that each of the iterated skew shifts (Exercise 8 from Lecture 9) are compact extensions of the preceding skew shift.
Exercise 9. Let be a measure-preserving system, let G be a compact metrisable group with a closed subgroup H, let be measurable, and let be the extension of Y with underlying space , with measure equal to the product of and Haar measure, and shift map . Show that is a compact extension of Y.
— Multiple recurrence for compact extensions —
Let us say that a measure-preserving system obeys the uniform multiple recurrence (UMR) property if the conclusion of the Furstenberg multiple recurrence theorem holds for this system, thus for all and all non-negative with , we have
Thus in Lecture 11 we showed that all compact systems obey UMR, and in Lecture 12 we showed that all weakly mixing systems obey UMR. The Furstenberg multiple recurrence theorem asserts, of course, that all measure-preserving systems obey UMR.
We now establish an important further step (and, in many ways, the key step) towards proving that theorem:
Theorem 1. Suppose that is a compact extension of . If Y obeys UMR, then so does X.
Note that the converse implication is trivial: if a system obeys UMR, then all of its factors automatically do also.
Proof of Theorem 1. Fix , and fix a non-negative function with . Our objective is to show that (10) holds. As X is a compact extension, f is conditionally almost periodic in measure; by definition (and uniform integrability), this implies that f can be bounded from below by another conditionally almost periodic function which is non-negative with positive mean. Thus we may assume without loss of generality that f is conditionally almost periodic.
We may normalise and for some . The reader may wish to follow this proof using the skew shift example as a guiding model.
Let be a small number (depending on k and ) to be chosen later. If we set , then E must have measure at least .
Since f is almost periodic, we can find a finitely generated module zonotope whose -neighbourhood contains the orbit of f. In other words, we have an identity of the form
for all n, where with norm at most 1, and is an error with almost everywhere.
By splitting into real and imaginary parts (and doubling d if necessary) we may assume that the are real-valued. By further duplication we can also assume that for each i. By rounding off to the nearest multiple of for each y (and absorbing the error into the term) we may assume that is always a multiple of . Thus each only takes on values.
Let K be a large integer (depending on k, d, , ) to be chosen later. Since the factor space Y obeys UMR, and E has positive measure in Y, we know that
In other words, there exists a constant such that
for a set of n of positive lower density, where is the set
Let n be as above. By definition of and (and (8)), we see that
for all and . Meanwhile, from (11) we have
for all and .
Fix y. For each , the d-tuple ranges over a set of cardinality . One can view this as a colouring of into colours. Applying van der Waerden’s theorem (Exercise 3 from Lecture 4), we can thus find (if K is sufficiently large depending on ) an arithmetic progression in for each y such that
The quantities a(y) and r(y) can of course be chosen to be measurable in y. By the pigeonhole principle, we can thus find a subset of of measure at least for some depending on c, K, d, but independent of n, and an arithmetic progression in such that
for all . (The quantities a and r can still depend on n, but this will not be of concern to us.)
Fix these values of a, r. From (16), (18) and the triangle inequality we see that
for all and . Recalling that f was normalised to have norm 1, it is then not hard to conclude (by induction on k and the relative Cauchy-Schwarz inequality) that
and thus (by another application of relative Cauchy-Schwarz)
But from (15) we have
and so by several more applications of relative Cauchy-Schwarz we have
for some positive quantity . From (21), (23) we conclude that
for , if is small enough. Integrating this in y and using the shift-invariance we conclude that
The quantity r depends on n, but ranges between 1 and K-1, and so (by the non-negativity of f)
for a set of n of positive lower density. Averaging this for n from 1 to N (say) one obtains (10) as desired.
Thus for instance we have now established UMR for the skew shift as well as higher iterates of that shift, thanks to Exercises 7 and 8.
Remark 3. One can avoid the use of Hilbert modules, etc. by instead appealing to the theory of disintegration of measures (Theorem 4 from Lecture 9). We sketch the details as follows. First, one has to restrict attention to those spaces X which are regular, though an inspection of the Furstenberg correspondence principle (Lecture 10) shows that this is in fact automatic for the purposes of such tasks as proving Szemerédi’s theorem. Once one disintegrates with respect to , the situation now resembles the concrete example of the skew shift, with the fibre measures playing the role of integration along vertical fibers . It is then not difficult (and somewhat instructive) to convert the above proof to one using norms such as rather than the module norm . We leave the details to the reader (who can also get them from Furstenberg’s book).
Remark 4. It is an intriguing question as to whether there is any interesting non-commutative extension of the above theory, in which the underlying von Neumann algebra is replaced by a non-commutative von Neumann algebra. While some of the theory seems to extend relatively easily, there does appear to be some genuine difficulties with other parts of the theory, particularly those involving multiple products such as .
Remark 5. Just as ergodic compact systems can be described as group rotation systems (Kronecker systems), it turns out that ergodic compact extensions can be described as (inverse limits of) group quotient extensions, somewhat analogously to Lemma 2 from Lecture 6. Roughly speaking, the idea is to first use some spectral theory to approximate conditionally almost periodic functions by conditionally quasiperiodic functions – those functions whose orbit lies on a finitely generated module zonotope (as opposed to merely being close to one). One can then use the generators of that zonotope as a basis from which to build the group quotient extension, and then use some further trickery to make the group consistent across all fibres. The precise machinery for this is known as Mackey theory; it is of particular importance in the deeper structural theory of dynamical systems, but we will not describe it in detail here, instead referring the reader to the papers of Furstenberg and of Zimmer.
[Update, Mar 5: Exercise added.]
[Update, Mar 12: Definition of conditionally almost periodic measure tweaked (to an equivalent definition) in order to simplify the proof of Theorem 1.]