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This week I have been at a Banff workshop “Combinatorics meets Ergodic theory“, focused on the combinatorics surrounding Szemerédi’s theorem and the Gowers uniformity norms on one hand, and the ergodic theory surrounding Furstenberg’s multiple recurrence theorem and the Host-Kra structure theory on the other. This was quite a fruitful workshop, and directly inspired the various posts this week on this blog. Incidentally, BIRS being as efficient as it is, videos for this week’s talks are already online.
As mentioned in the previous two posts, Ben Green, Tamar Ziegler, and myself proved the following inverse theorem for the Gowers norms:
Theorem 1 (Inverse theorem for Gowers norms) Let
and
be integers, and let
. Suppose that
is a function supported on
such that
Then there exists a filtered nilmanifold
of degree
and complexity
, a polynomial sequence
, and a Lipschitz function
of Lipschitz constant
such that
There is a higher dimensional generalisation, which first appeared explicitly (in a more general form) in this preprint of Szegedy (which used a slightly different argument than the one of Ben, Tammy, and myself; see also this previous preprint of Szegedy with related results):
Theorem 2 (Inverse theorem for multidimensional Gowers norms) Let
and
be integers, and let
. Suppose that
is a function supported on
such that
Then there exists a filtered nilmanifold
of degree
and complexity
, a polynomial sequence
, and a Lipschitz function
of Lipschitz constant
such that
The case of this theorem was recently used by Wenbo Sun. One can replace the polynomial sequence with a linear sequence if desired by using a lifting trick (essentially due to Furstenberg, but which appears explicitly in Appendix C of my paper with Ben and Tammy).
In this post I would like to record a very neat and simple observation of Ben Green and Nikos Frantzikinakis, that uses the tool of Freiman isomorphisms to derive Theorem 2 as a corollary of the one-dimensional theorem. Namely, consider the linear map defined by
that is to say is the digit string base
that has digits
. This map is a linear map from
to a subset of
of density
. Furthermore it has the following “Freiman isomorphism” property: if
lie in
with
in the image set
of
for all
, then there exist (unique) lifts
such that
and
for all . Indeed, the injectivity of
on
uniquely determines the sum
for each
, and one can use base
arithmetic to verify that the alternating sum of these sums on any
-facet of the cube
vanishes, which gives the claim. (In the language of additive combinatorics, the point is that
is a Freiman isomorphism of order (say)
on
.)
Now let be the function defined by setting
whenever
, with
vanishing outside of
. If
obeys (1), then from the above Freiman isomorphism property we have
Applying the one-dimensional inverse theorem (Theorem 1), with reduced by a factor of
and
replaced by
, this implies the existence of a filtered nilmanifold
of degree
and complexity
, a polynomial sequence
, and a Lipschitz function
of Lipschitz constant
such that
which by the Freiman isomorphism property again implies that
But the map is clearly a polynomial map from
to
(the composition of two polynomial maps is polynomial, see e.g. Appendix B of my paper with Ben and Tammy), and the claim follows.
Remark 3 This trick appears to be largely restricted to the case of boundedly generated groups such as
; I do not see any easy way to deduce an inverse theorem for, say,
from the
-inverse theorem by this method.
Remark 4 By combining this argument with the one in the previous post, one can obtain a weak ergodic inverse theorem for
-actions. Interestingly, the Freiman isomorphism argument appears to be difficult to implement directly in the ergodic category; in particular, there does not appear to be an obvious direct way to derive the Host-Kra inverse theorem for
actions (a result first obtained in the PhD thesis of Griesmer) from the counterpart for
actions.
Note: this post is of a particularly technical nature, in particular presuming familiarity with nilsequences, nilsystems, characteristic factors, etc., and is primarily intended for experts.
As mentioned in the previous post, Ben Green, Tamar Ziegler, and myself proved the following inverse theorem for the Gowers norms:
Theorem 1 (Inverse theorem for Gowers norms) Let
and
be integers, and let
. Suppose that
is a function supported on
such that
Then there exists a filtered nilmanifold
of degree
and complexity
, a polynomial sequence
, and a Lipschitz function
of Lipschitz constant
such that
This result was conjectured earlier by Ben Green and myself; this conjecture was strongly motivated by an analogous inverse theorem in ergodic theory by Host and Kra, which we formulate here in a form designed to resemble Theorem 1 as closely as possible:
Theorem 2 (Inverse theorem for Gowers-Host-Kra seminorms) Let
be an integer, and let
be an ergodic, countably generated measure-preserving system. Suppose that one has
for all non-zero
(all
spaces are real-valued in this post). Then
is an inverse limit (in the category of measure-preserving systems, up to almost everywhere equivalence) of ergodic degree
nilsystems, that is to say systems of the form
for some degree
filtered nilmanifold
and a group element
that acts ergodically on
.
It is a natural question to ask if there is any logical relationship between the two theorems. In the finite field category, one can deduce the combinatorial inverse theorem from the ergodic inverse theorem by a variant of the Furstenberg correspondence principle, as worked out by Tamar Ziegler and myself, however in the current context of -actions, the connection is less clear.
One can split Theorem 2 into two components:
Theorem 3 (Weak inverse theorem for Gowers-Host-Kra seminorms) Let
be an integer, and let
be an ergodic, countably generated measure-preserving system. Suppose that one has
for all non-zero
, where
. Then
is a factor of an inverse limit of ergodic degree
nilsystems.
Theorem 4 (Pro-nilsystems closed under factors) Let
be an integer. Then any factor of an inverse limit of ergodic degree
nilsystems, is again an inverse limit of ergodic degree
nilsystems.
Indeed, it is clear that Theorem 2 implies both Theorem 3 and Theorem 4, and conversely that the two latter theorems jointly imply the former. Theorem 4 is, in principle, purely a fact about nilsystems, and should have an independent proof, but this is not known; the only known proofs go through the full machinery needed to prove Theorem 2 (or the closely related theorem of Ziegler). (However, the fact that a factor of a nilsystem is again a nilsystem was established previously by Parry.)
The purpose of this post is to record a partial implication in reverse direction to the correspondence principle:
As mentioned at the start of the post, a fair amount of familiarity with the area is presumed here, and some routine steps will be presented with only a fairly brief explanation.
A few years ago, Ben Green, Tamar Ziegler, and myself proved the following (rather technical-looking) inverse theorem for the Gowers norms:
Theorem 1 (Discrete inverse theorem for Gowers norms) Let
and
be integers, and let
. Suppose that
is a function supported on
such that
Then there exists a filtered nilmanifold
of degree
and complexity
, a polynomial sequence
, and a Lipschitz function
of Lipschitz constant
such that
For the definitions of “filtered nilmanifold”, “degree”, “complexity”, and “polynomial sequence”, see the paper of Ben, Tammy, and myself. (I should caution the reader that this blog post will presume a fair amount of familiarity with this subfield of additive combinatorics.) This result has a number of applications, for instance to establishing asymptotics for linear equations in the primes, but this will not be the focus of discussion here.
The purpose of this post is to record the observation that this “discrete” inverse theorem, together with an equidistribution theorem for nilsequences that Ben and I worked out in a separate paper, implies a continuous version:
Theorem 2 (Continuous inverse theorem for Gowers norms) Let
be an integer, and let
. Suppose that
is a measurable function supported on
such that
Then there exists a filtered nilmanifold
of degree
and complexity
, a (smooth) polynomial sequence
, and a Lipschitz function
of Lipschitz constant
such that
The interval can be easily replaced with any other fixed interval by a change of variables. A key point here is that the bounds are completely uniform in the choice of
. Note though that the coefficients of
can be arbitrarily large (and this is necessary, as can be seen just by considering functions of the form
for some arbitrarily large frequency
).
It is likely that one could prove Theorem 2 by carefully going through the proof of Theorem 1 and replacing all instances of with
(and making appropriate modifications to the argument to accommodate this). However, the proof of Theorem 1 is quite lengthy. Here, we shall proceed by the usual limiting process of viewing the continuous interval
as a limit of the discrete interval
as
. However there will be some problems taking the limit due to a failure of compactness, and specifically with regards to the coefficients of the polynomial sequence
produced by Theorem 1, after normalising these coefficients by
. Fortunately, a factorisation theorem from a paper of Ben Green and myself resolves this problem by splitting
into a “smooth” part which does enjoy good compactness properties, as well as “totally equidistributed” and “periodic” parts which can be eliminated using the measurability (and thus, approximate smoothness), of
.
Szemerédi’s theorem asserts that any subset of the integers of positive upper density contains arbitrarily large arithmetic progressions. Here is an equivalent quantitative form of this theorem:
Theorem 1 (Szemerédi’s theorem) Let
be a positive integer, and let
be a function with
for some
, where we use the averaging notation
,
, etc.. Then for
we have
for some
depending only on
.
The equivalence is basically thanks to an averaging argument of Varnavides; see for instance Chapter 11 of my book with Van Vu or this previous blog post for a discussion. We have removed the cases as they are trivial and somewhat degenerate.
There are now many proofs of this theorem. Some time ago, I took an ergodic-theoretic proof of Furstenberg and converted it to a purely finitary proof of the theorem. The argument used some simplifying innovations that had been developed since the original work of Furstenberg (in particular, deployment of the Gowers uniformity norms, as well as a “dual” norm that I called the uniformly almost periodic norm, and an emphasis on van der Waerden’s theorem for handling the “compact extension” component of the argument). But the proof was still quite messy. However, as discussed in this previous blog post, messy finitary proofs can often be cleaned up using nonstandard analysis. Thus, there should be a nonstandard version of the Furstenberg ergodic theory argument that is relatively clean. I decided (after some encouragement from Ben Green and Isaac Goldbring) to write down most of the details of this argument in this blog post, though for sake of brevity I will skim rather quickly over arguments that were already discussed at length in other blog posts. In particular, I will presume familiarity with nonstandard analysis (in particular, the notion of a standard part of a bounded real number, and the Loeb measure construction), see for instance this previous blog post for a discussion.
In analytic number theory, there is a well known analogy between the prime factorisation of a large integer, and the cycle decomposition of a large permutation; this analogy is central to the topic of “anatomy of the integers”, as discussed for instance in this survey article of Granville. Consider for instance the following two parallel lists of facts (stated somewhat informally). Firstly, some facts about the prime factorisation of large integers:
- Every positive integer
has a prime factorisation
into (not necessarily distinct) primes
, which is unique up to rearrangement. Taking logarithms, we obtain a partition
of
.
- (Prime number theorem) A randomly selected integer
of size
will be prime with probability
when
is large.
- If
is a randomly selected large integer of size
, and
is a randomly selected prime factor of
(with each index
being chosen with probability
), then
is approximately uniformly distributed between
and
. (See Proposition 9 of this previous blog post.)
- The set of real numbers
arising from the prime factorisation
of a large random number
converges (away from the origin, and in a suitable weak sense) to the Poisson-Dirichlet process in the limit
. (See the previously mentioned blog post for a definition of the Poisson-Dirichlet process, and a proof of this claim.)
Now for the facts about the cycle decomposition of large permutations:
- Every permutation
has a cycle decomposition
into disjoint cycles
, which is unique up to rearrangement, and where we count each fixed point of
as a cycle of length
. If
is the length of the cycle
, we obtain a partition
of
.
- (Prime number theorem for permutations) A randomly selected permutation of
will be an
-cycle with probability exactly
. (This was noted in this previous blog post.)
- If
is a random permutation in
, and
is a randomly selected cycle of
(with each
being selected with probability
), then
is exactly uniformly distributed on
. (See Proposition 8 of this blog post.)
- The set of real numbers
arising from the cycle decomposition
of a random permutation
converges (in a suitable sense) to the Poisson-Dirichlet process in the limit
. (Again, see this previous blog post for details.)
See this previous blog post (or the aforementioned article of Granville, or the Notices article of Arratia, Barbour, and Tavaré) for further exploration of the analogy between prime factorisation of integers and cycle decomposition of permutations.
There is however something unsatisfying about the analogy, in that it is not clear why there should be such a kinship between integer prime factorisation and permutation cycle decomposition. It turns out that the situation is clarified if one uses another fundamental analogy in number theory, namely the analogy between integers and polynomials over a finite field
, discussed for instance in this previous post; this is the simplest case of the more general function field analogy between number fields and function fields. Just as we restrict attention to positive integers when talking about prime factorisation, it will be reasonable to restrict attention to monic polynomials
. We then have another analogous list of facts, proven very similarly to the corresponding list of facts for the integers:
- Every monic polynomial
has a factorisation
into irreducible monic polynomials
, which is unique up to rearrangement. Taking degrees, we obtain a partition
of
.
- (Prime number theorem for polynomials) A randomly selected monic polynomial
of degree
will be irreducible with probability
when
is fixed and
is large.
- If
is a random monic polynomial of degree
, and
is a random irreducible factor of
(with each
selected with probability
), then
is approximately uniformly distributed in
when
is fixed and
is large.
- The set of real numbers
arising from the factorisation
of a randomly selected polynomial
of degree
converges (in a suitable sense) to the Poisson-Dirichlet process when
is fixed and
is large.
The above list of facts addressed the large limit of the polynomial ring
, where the order
of the field is held fixed, but the degrees of the polynomials go to infinity. This is the limit that is most closely analogous to the integers
. However, there is another interesting asymptotic limit of polynomial rings to consider, namely the large
limit where it is now the degree
that is held fixed, but the order
of the field goes to infinity. Actually to simplify the exposition we will use the slightly more restrictive limit where the characteristic
of the field goes to infinity (again keeping the degree
fixed), although all of the results proven below for the large
limit turn out to be true as well in the large
limit.
The large (or large
) limit is technically a different limit than the large
limit, but in practice the asymptotic statistics of the two limits often agree quite closely. For instance, here is the prime number theorem in the large
limit:
Theorem 1 (Prime number theorem) The probability that a random monic polynomial
of degree
is irreducible is
in the limit where
is fixed and the characteristic
goes to infinity.
Proof: There are monic polynomials
of degree
. If
is irreducible, then the
zeroes of
are distinct and lie in the finite field
, but do not lie in any proper subfield of that field. Conversely, every element
of
that does not lie in a proper subfield is the root of a unique monic polynomial in
of degree
(the minimal polynomial of
). Since the union of all the proper subfields of
has size
, the total number of irreducible polynomials of degree
is thus
, and the claim follows.
Remark 2 The above argument and inclusion-exclusion in fact gives the well known exact formula
for the number of irreducible monic polynomials of degree
.
Now we can give a precise connection between the cycle distribution of a random permutation, and (the large limit of) the irreducible factorisation of a polynomial, giving a (somewhat indirect, but still connected) link between permutation cycle decomposition and integer factorisation:
Theorem 3 The partition
of a random monic polynomial
of degree
converges in distribution to the partition
of a random permutation
of length
, in the limit where
is fixed and the characteristic
goes to infinity.
We can quickly prove this theorem as follows. We first need a basic fact:
Lemma 4 (Most polynomials square-free in large
limit) A random monic polynomial
of degree
will be square-free with probability
when
is fixed and
(or
) goes to infinity. In a similar spirit, two randomly selected monic polynomials
of degree
will be coprime with probability
if
are fixed and
or
goes to infinity.
Proof: For any polynomial of degree
, the probability that
is divisible by
is at most
. Summing over all polynomials of degree
, and using the union bound, we see that the probability that
is not squarefree is at most
, giving the first claim. For the second, observe from the first claim (and the fact that
has only a bounded number of factors) that
is squarefree with probability
, giving the claim.
Now we can prove the theorem. Elementary combinatorics tells us that the probability of a random permutation consisting of
cycles of length
for
, where
are nonnegative integers with
, is precisely
since there are ways to write a given tuple of cycles
in cycle notation in nondecreasing order of length, and
ways to select the labels for the cycle notation. On the other hand, by Theorem 1 (and using Lemma 4 to isolate the small number of cases involving repeated factors) the number of monic polynomials of degree
that are the product of
irreducible polynomials of degree
is
which simplifies to
and the claim follows.
This was a fairly short calculation, but it still doesn’t quite explain why there is such a link between the cycle decomposition of permutations and the factorisation
of a polynomial. One immediate thought might be to try to link the multiplication structure of permutations in
with the multiplication structure of polynomials; however, these structures are too dissimilar to set up a convincing analogy. For instance, the multiplication law on polynomials is abelian and non-invertible, whilst the multiplication law on
is (extremely) non-abelian but invertible. Also, the multiplication of a degree
and a degree
polynomial is a degree
polynomial, whereas the group multiplication law on permutations does not take a permutation in
and a permutation in
and return a permutation in
.
I recently found (after some discussions with Ben Green) what I feel to be a satisfying conceptual (as opposed to computational) explanation of this link, which I will place below the fold.
I’ve just uploaded to the arXiv my paper “Inverse theorems for sets and measures of polynomial growth“. This paper was motivated by two related questions. The first question was to obtain a qualitatively precise description of the sets of polynomial growth that arise in Gromov’s theorem, in much the same way that Freiman’s theorem (and its generalisations) provide a qualitatively precise description of sets of small doubling. The other question was to obtain a non-abelian analogue of inverse Littlewood-Offord theory.
Let me discuss the former question first. Gromov’s theorem tells us that if a finite subset of a group
exhibits polynomial growth in the sense that
grows polynomially in
, then the group generated by
is virtually nilpotent (the converse direction also true, and is relatively easy to establish). This theorem has been strengthened a number of times over the years. For instance, a few years ago, I proved with Shalom that the condition that
grew polynomially in
could be replaced by
for a single
, as long as
was sufficiently large depending on
(in fact we gave a fairly explicit quantitative bound on how large
needed to be). A little more recently, with Breuillard and Green, the condition
was weakened to
, that is to say it sufficed to have polynomial relative growth at a finite scale. In fact, the latter paper gave more information on
in this case, roughly speaking it showed (at least in the case when
was a symmetric neighbourhood of the identity) that
was “commensurate” with a very structured object known as a coset nilprogression. This can then be used to establish further control on
. For instance, it was recently shown by Breuillard and Tointon (again in the symmetric case) that if
for a single
that was sufficiently large depending on
, then all the
for
have a doubling constant bounded by a bound
depending only on
, thus
for all
.
In this paper we are able to refine this analysis a bit further; under the same hypotheses, we can show an estimate of the form
for all and some piecewise linear, continuous, non-decreasing function
with
, where the error
is bounded by a constant depending only on
, and where
has at most
pieces, each of which has a slope that is a natural number of size
. To put it another way, the function
for
behaves (up to multiplicative constants) like a piecewise polynomial function, where the degree of the function and number of pieces is bounded by a constant depending on
.
One could ask whether the function has any convexity or concavity properties. It turns out that it can exhibit either convex or concave behaviour (or a combination of both). For instance, if
is contained in a large finite group, then
will eventually plateau to a constant, exhibiting concave behaviour. On the other hand, in nilpotent groups one can see convex behaviour; for instance, in the Heisenberg group
, if one sets
to be a set of matrices of the form
for some large
(abusing the
notation somewhat), then
grows cubically for
but then grows quartically for
.
To prove this proposition, it turns out (after using a somewhat difficult inverse theorem proven previously by Breuillard, Green, and myself) that one has to analyse the volume growth of nilprogressions
. In the “infinitely proper” case where there are no unexpected relations between the generators of the nilprogression, one can lift everything to a simply connected Lie group (where one can take logarithms and exploit the Baker-Campbell-Hausdorff formula heavily), eventually describing
with fair accuracy by a certain convex polytope with vertices depending polynomially on
, which implies that
depends polynomially on
up to constants. If one is not in the “infinitely proper” case, then at some point
the nilprogression
develops a “collision”, but then one can use this collision to show (after some work) that the dimension of the “Lie model” of
has dropped by at least one from the dimension of
(the notion of a Lie model being developed in the previously mentioned paper of Breuillard, Greenm, and myself), so that this sort of collision can only occur a bounded number of times, with essentially polynomial volume growth behaviour between these collisions.
The arguments also give a precise description of the location of a set for which
grows polynomially in
. In the symmetric case, what ends up happening is that
becomes commensurate to a “coset nilprogression”
of bounded rank and nilpotency class, whilst
is “virtually” contained in a scaled down version
of that nilprogression. What “virtually” means is a little complicated; roughly speaking, it means that there is a set
of bounded cardinality such that
for all
. Conversely, if
is virtually contained in
, then
is commensurate to
(and more generally,
is commensurate to
for any natural number
), giving quite a (qualitatively) precise description of
in terms of coset nilprogressions.
The main tool used to prove these results is the structure theorem for approximate groups established by Breuillard, Green, and myself, which roughly speaking asserts that approximate groups are always commensurate with coset nilprogressions. A key additional trick is a pigeonholing argument of Sanders, which in this context is the assertion that if is comparable to
, then there is an
between
and
such that
is very close in size to
(up to a relative error of
). It is this fact, together with the comparability of
to a coset nilprogression
, that allows us (after some combinatorial argument) to virtually place
inside
.
Similar arguments apply when discussing iterated convolutions of (symmetric) probability measures on a (discrete) group
, rather than combinatorial powers
of a finite set. Here, the analogue of volume
is given by the negative power
of the
norm of
(thought of as a non-negative function on
of total mass 1). One can also work with other norms here than
, but this norm has some minor technical conveniences (and other measures of the “spread” of
end up being more or less equivalent for our purposes). There is an analogous structure theorem that asserts that if
spreads at most polynomially in
, then
is “commensurate” with the uniform probability distribution on a coset progression
, and
itself is largely concentrated near
. The factor of
here is the familiar scaling factor in random walks that arises for instance in the central limit theorem. The proof of (the precise version of) this statement proceeds similarly to the combinatorial case, using pigeonholing to locate a scale
where
has almost the same
norm as
.
A special case of this theory occurs when is the uniform probability measure on
elements
of
and their inverses. The probability measure
is then the distribution of a random product
, where each
is equal to one of
or its inverse
, selected at random with
drawn uniformly from
with replacement. This is very close to the Littlewood-Offord situation of random products
where each
is equal to
or
selected independently at random (thus
is now fixed to equal
rather than being randomly drawn from
. In the case when
is abelian, it turns out that a little bit of Fourier analysis shows that these two random walks have “comparable” distributions in a certain
sense. As a consequence, the results in this paper can be used to recover an essentially optimal abelian inverse Littlewood-Offord theorem of Nguyen and Vu. In the nonabelian case, the only Littlewood-Offord theorem I am aware of is a recent result of Tiep and Vu for matrix groups, but in this case I do not know how to relate the above two random walks to each other, and so we can only obtain an analogue of the Tiep-Vu results for the symmetrised random walk
instead of the ordered random walk
.
Just a short post here to note that the cover story of this month’s Notices of the AMS, by John Friedlander, is about the recent work on bounded gaps between primes by Zhang, Maynard, our own Polymath project, and others.
I may as well take this opportunity to upload some slides of my own talks on this subject: here are my slides on small and large gaps between the primes that I gave at the “Latinos in the Mathematical Sciences” back in April, and here are my slides on the Polymath project for the Schock Prize symposium last October. (I also gave an abridged version of the latter talk at an AAAS Symposium in February, as well as the Breakthrough Symposium from last November.)
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