A (complex, semi-definite) inner product space is a complex vector space equipped with a sesquilinear form
which is conjugate symmetric, in the sense that
for all
, and non-negative in the sense that
for all
. By inspecting the non-negativity of
for complex numbers
, one obtains the Cauchy-Schwarz inequality
if one then defines , one then quickly concludes the triangle inequality
which then soon implies that is a semi-norm on
. If we make the additional assumption that the inner product
is positive definite, i.e. that
whenever
is non-zero, then this semi-norm becomes a norm. If
is complete with respect to the metric
induced by this norm, then
is called a Hilbert space.
The above material is extremely standard, and can be found in any graduate real analysis course; I myself covered it here. But what is perhaps less well known (except inside the fields of additive combinatorics and ergodic theory) is that the above theory of classical Hilbert spaces is just the first case of a hierarchy of higher order Hilbert spaces, in which the binary inner product is replaced with a
-ary inner product
that obeys an appropriate generalisation of the conjugate symmetry, sesquilinearity, and positive semi-definiteness axioms. Such inner products then obey a higher order Cauchy-Schwarz inequality, known as the Cauchy-Schwarz-Gowers inequality, and then also obey a triangle inequality and become semi-norms (or norms, if the inner product was non-degenerate). Examples of such norms and spaces include the Gowers uniformity norms
, the Gowers box norms
, and the Gowers-Host-Kra seminorms
; a more elementary example are the family of Lebesgue spaces
when the exponent is a power of two. They play a central role in modern additive combinatorics and to certain aspects of ergodic theory, particularly those relating to Szemerédi’s theorem (or its ergodic counterpart, the Furstenberg multiple recurrence theorem); they also arise in the regularity theory of hypergraphs (which is not unrelated to the other two topics).
A simple example to keep in mind here is the order two Hilbert space on a measure space
, where the inner product takes the form
In this brief note I would like to set out the abstract theory of such higher order Hilbert spaces. This is not new material, being already implicit in the breakthrough papers of Gowers and Host-Kra, but I just wanted to emphasise the fact that the material is abstract, and is not particularly tied to any explicit choice of norm so long as a certain axiom are satisfied. (Also, I wanted to write things down so that I would not have to reconstruct this formalism again in the future.) Unfortunately, the notation is quite heavy and the abstract axiom is a little strange; it may be that there is a better way to formulate things. In this particular case it does seem that a concrete approach is significantly clearer, but abstraction is at least possible.
Note: the discussion below is likely to be comprehensible only to readers who already have some exposure to the Gowers norms.
— 1. Definition of a higher order Hilbert space —
Let be complex vector spaces. Then one can form the (algebraic) tensor product
, which can be defined as the vector space spanned by formal tensor products
, subject to the constraint that the tensor product is bilinear (i.e. that
,
, and similarly with the roles of
and
reversed). More generally, one can define the tensor product
of any finite family of complex vector spaces
.
Given a complex vector space , one can define its complex conjugate
to be the set of formal conjugates
of vectors in
, with the vector space operations given by
The map is then an antilinear isomorphism from
to
. We adopt the convention that
, thus
is also an antilinear isomorphism from
to
. (One can work with real higher order Hilbert spaces instead of complex ones, in which case the conjugation symbols can be completely ignored.)
For inductive reasons, it is convenient to use finite sets of labels, rather than natural numbers
, to index the order of the systems we will be studying. In any case, the cardinality
of the set of labels will be the most important feature of this set.
Given a complex vector space and a finite set
of labels, we form the tensor cube
to be
where is the conjugation map
, and
when
; thus for instance
,
is spanned by tensor products
with
,
is spanned by tensor products
with
, and so forth. (It would be better to order the four factors
in a square pattern, rather than linearly as is done here, but we have used the inferior linear ordering here for typographical reasons.)
Given any finite set of labels and any
, one can form an identification
by identifying a tensor product in
with
where, for and
,
denotes the element of
that agrees with
on
and equals
on
. We refer to this identification as
, thus
is an isomorphism, and one can define the tensor product
of two elements
. Thus for instance, if
and
are elements of
, then
using the linear ordering conventions used earlier. If we instead view as elements of
rather than
, then
A (semi-)definite inner product on a complex vector space
can be viewed as a linear functional
on
obeying a conjugation symmetry and positive (semi-)definiteness property, defined on tensor products
as
. With this notation, the conjugation symmetry axiom becomes
and the positive semi-definiteness property becomes
with equality iff in the definite case.
Now we can define a higher order inner product space.
Definition 1 Let
be a finite set of labels. A (semi-definite) inner product space of order
is a complex vector space
, together with a linear functional
that obeys the following axiom:
- (Splitting axiom) For every
,
is a semi-definite classical inner product
on
, which we identify with
using
as mentioned above.
We say that the inner product space is positive definite if one has
whenever
is non-zero. (Note from the splitting axiom that one already has the non-strict inequality. But the positive definiteness property is weaker than the assertion that each of the classical inner products)
For instance, if is the empty set, then an inner product space of order
is just a complex vector space
equipped with a linear functional
from
to
(which one could interpret as an expectation or a trace, if one wished). If
is a singleton set, then an inner product space of order
is the same thing as a classical inner product space.
If , then an inner product space of order
is a complex vector space
equipped with a linear functional
, which in particular gives rise to a quartisesquilinear (!) form
which is a classical inner product in two different ways, thus for instance we have
for and some classical inner product
on
, and similarly
for some classical inner product on
.
— 2. Examples —
Let us now give the three major (and inter-related) examples of inner product spaces of higher order: the Gowers uniformity spaces, that arise in additive combinatorics; the Gowers box spaces, which arise in hypergraph regularity theory, and the Gowers-Host-Kra spaces, which arise in ergodic theory. We also remark on the much simpler example of the Lebesgue spaces of dyadic exponent.
The first example is the family of Gowers uniformity spaces , which we will define for simplicity on a finite additive group
(one can also define this norm more generally on finite subsets of abelian groups, and probably also nilpotent groups, but we will not do so here). Here
is a finite set of labels; in applications one usually sets
, in which case one abbreviates
as
. The space
is the space of all functions
, and so
can be canonically identified with the space of functions
. To make
into an inner product space of order
, we define
where is the subgroup of
consisting of the parallelopipeds
This is clearly a linear functional. To verify the splitting axiom, one observes the identity
for any and
. The right-hand side is then a semi-definite classical inner product on
; the semi-definiteness becomes more apparent if one makes the substitution
.
Specialising to tensor products, we obtain the Gowers inner product
Thus, for instance, when ,
The second example is the family of the (incomplete) Gowers box spaces , defined on a Cartesian product
of a family
of measure spaces indexed by a finite set
. To avoid some minor technicalities regarding absolute integrability, we assume that all the measure spaces have finite measure (the theory also works in the
-finite case, but we will not discuss this here). This space is the space of all bounded measurable functions
(here, for technical reasons, it is best not to quotient out by almost everywhere equivalence until later in the theory). The tensor power
can thus be identified with a subspace of
(roughly speaking, this is the subspace of “elementary functions”). We can then define an inner product of order
by the formula
for all , where
and
are integrated using product measure
.
The verification of the splitting property is analogous to that for the Gowers uniformity spaces. Indeed, there is the identity
for all and
, where
,
, and
for
. From this formula one can verify the inner product property without much trouble (the main difficulty here is simply in unpacking all the notation).
The third example is that of the (incomplete) Gowers-Host-Kra spaces . Here,
is a probability space with an invertible measure-preserving shift
, which of course induces a measure-preserving action
of the integers
on
. (One can replace the integers in the discussion that follows by more general nilpotent amenable groups, but we will stick to integer actions for simplicity.) It is often convenient to also assume that the measure
is ergodic, though this is not strictly required to define the semi-norms. The space here is
; the power
is then a subspace of
. One can define the Host-Kra measure
on
for any finite
by the following recursive procedure. Firstly, when
is empty, then
is just
. If instead
is non-empty, then pick an element
and view
as the Cartesian product of
with itself. The shift
acts on
, and thus acts diagonally on
by acting on each component separately. It is not hard to show inductively from the construction that we are about to give that
is invariant with respect to this diagonal shift, which we will call
. The product
-algebra
has an invariant factor
with respect to this shift. We then define
to be the relative product of
with itself relative to this invariant factor. One can show that this definition is independent of the choice of
, and that the form
is an inner product of order ; see the paper of Host and Kra for details.
A final (and significantly simpler) example of a inner product space of order is the Lebesgue space
on some measure space
, with inner product
where is the diagonal embedding from
to
. For tensor products, this inner product takes the form
thus for instance when ,
We leave it as an exercise to the reader to show is indeed an inner product space of order
. This example is (the completion of) the Gowers-Host-Kra space in the case when the shift
is trivial.
We also remark that given an inner product space of some order
, given some subset
of
, and given a fixed vector
in
, one can define a weighted inner product space
of order
by the formula
for all , where
is embedded in
by extension by zero and the tensor product on the right-hand side is defined in the obvious manner. One can check that this is indeed a weighted inner product space. This is a generalisation of the classical fact that every vector
in an inner product space
naturally defines a linear functional
on
. In the case of the Gowers uniformity spaces with
, this construction takes
to
; similarly for the Gowers box spaces.
— 3. Basic theory —
Let be an inner product space of order
for some finite non-empty
. The splitting axiom tells us that
for all ,
, and some inner product
on
. In particular one has
for all , as well as the classical Cauchy-Schwarz inequality
If we specialise this inequality to the tensor products
for various , one concludes that
where we write for some
and
. If we iterate this inequality once for each
, we obtain the Cauchy-Schwarz-Gowers inequality
where
The quantity is clearly non-negative and homogeneous. We also have the Gowers triangle inequality
which makes a semi-norm (and in fact a norm, if the inner product space was positive definite). To see this inequality, we first raise both sides to the power
:
The left-hand side can be expanded as
which after expanding out using linearity and the triangle inequality, can be bounded by
which by the Cauchy-Schwarz-Gowers inequality can be bounded in turn by
which can then be factored into as required.
Note that when is a singleton set, the above argument collapses to the usual derivation of the triangle inequality from the classical Cauchy-Schwarz inequality. It is also instructive to see how this collapses to one of the standard proofs of the triangle inequality for
using a large number of applications of the Cauchy-Schwarz inequality.
In analogy with classical Hilbert spaces, one can define a Hilbert space of order to be an inner product space
of order
which is both positive definite and complete, so that the norm
gives
the structure of a Banach space. A typical example is
for a finite abelian
, which is the space of all functions
with the norm
where is the Pontraygin dual of
(i.e. the space of homomorphisms
from
to
) and
is the Fourier transform. Thus we see that
is a Hilbert space of order
. More generally,
for any measure space
and any
can be viewed as a Hilbert space of order
.
The Gowers norms and Gowers-Host-Kra norms
coincide in the model case when
is a cyclic group with uniform measure and the standard shift
. Also, the Gowers norms
can be viewed as a special case of the box norms via the identity
where is the summation operation
.
Just as classical inner product spaces can be made positive definite by quotienting out the norm zero elements, and then made into a classical Hilbert space by metric completion, inner product spaces of any order can also be made positive definite and completed. One can apply this procedure for instance to obtain the completed Gowers box spaces and the completed Gowers-Host-Kra spaces
(which become
when the shift
is trivial). These spaces are related, but not equal, to their Lebesgue counterparts
; for instance for the Gowers-Host-Kra spaces in the ergodic setting, a repeated application of Young’s inequality reveals the inequalities
and so contains a (quotient) of
.
The null space of the Gowers-Host-Kra norm in
in the ergodic case is quite interesting; it turns out to be the space
of bounded measurable functions
whose conditional expectation
on the characteristic factor
of order
of
vanishes; in particular,
becomes a dense subspace of
, embedded injectively. It is a highly non-trivial and useful result, first obtained by Host and Kra), that
is the inverse limit of all nilsystem factors of step at most
; this is the ergodic counterpart of the inverse conjecture for the Gowers norms.
— 4. The category of higher order inner product spaces —
The higher order Hilbert spaces are related to each other via Hölder’s inequality; the pointwise product of two
functions is in
, the product of two
functions is in
, and so forth. Furthermore, the inner products on all of these spaces are can be connected to each other via the pointwise product.
We can generalise this concept, giving the class of inner product spaces (of arbitrary orders) the structure of a category.
Definition 2 Let
be finite sets, and let
,
be inner product spaces of order
respectively. An isometry
from
to
is a linear map
which preserves the inner product in the sense that
where
is the obvious concatenation map from
to
.
Given an isometry
from
to
, and an isometry
from
to
for some
, one can form the composition
by the formula
and extending by linearity; one can verify that this continues to be an isometry, and that the class of inner product spaces of arbitrary order together with isomorphisms form a category.
When is a singleton set, the above concept collapses to the classical notion of an isometry for inner product spaces. Of course, one could specialise to the subcategory of higher order Hilbert spaces if desired. The inner product on a higher order inner product space can now be interpreted as an isometry from that space to the space
(viewed as an inner product space of order
), and is the unique such isometry; in the language of category theory, this space
becomes the terminal object of the category.
A model example of an isometry is the sesquilinear product map , which is an isometry from
to
for any
. For the Gowers-Host-Kra norms, the map
is an isometry from
to
for any
and
.
To see analogous isometries for the Gowers uniformity norms, one has to generalise these norms to the “non-ergodic” setting when one does not average the shift parameter over the entire group
, but on a subgroup
. Specifically, for finite additive groups
and functions
with
, define the local Gowers inner product
By foliating into cosets of
, one can express this local Gowers inner product as an amalgam of the ordinary Gowers inner product and a Lebesgue inner product. For instance, one has the identity
We define the inner product space to be the space of functions from
to
with the above inner product. Given any
, we can then create an isometry
from
to
by defining
(This isometry does not ostensibly depend on , except through the labels of the inner product of the target space
of the isometry.)
One can obtain analogous isometries for the Gowers box norms after similarly generalising to “non-ergodic” settings; we leave this as an exercise to the interested reader.
Actually, the “derivative maps” from inner product spaces of order
to those of order
can be constructed abstractly. Indeed, one can view
as an inner product space of order
with the inner product defined on tensor products by
and then the map is an isometry. One can iterate this construction and obtain a cubic complex of inner product spaces
of order for each
, together with a commuting system of derivative isometries
from
to
for each
.
Conversely, one can use cubic complexes to build higher order inner product spaces:
Proposition 3 Let
be a finite set. For each
, suppose that we have a vector space
equipped with a
-sesquilinear form
and suppose that for each
one has a sesquilinear product
obeying the compatibility conditions
whenever
for all
. Suppose also that the form
is a classical inner product on
for every
. Then for each
,
is an inner product space of order
, and the maps
become isometries.
This proposition is established by an easy induction on the cardinality of . Note that we do not require the derivative maps
to commute with each other, although this is almost always the case in applications.
[Update, May 20: added section on cubic complexes.]
17 comments
Comments feed for this article
19 May, 2010 at 4:11 pm
Matt Leifer
Where is the best place to get some further background on the Gower’s norms? Is there a review article?
19 May, 2010 at 4:17 pm
Terence Tao
One can try Section 11.1 of my book with Van, or my lecture notes in my current course on higher Fourier analysis (starting with Notes 3). Ben Green also has some notes on quadratic Fourier analysis for a conference in Montreal which is also quite relevant.
20 May, 2010 at 4:00 am
tou
Dear Prof.Tao:
First thank you for your posts.
At first I must say Im not a mathematican at all.But I am curious about some thing to ask.I dont know where it is suitable to ask so please forgive me to put it on here.
It is well known that alge-geom was changed by brought in language of scheme.
It is said that it is not necessary for a beginner to study “old-fashion-stuff” to enter that fields.Because it became more abstract and more different from the origin.
So what I want to know is that is AddCom going through the same change as alge-geom were?
It seems that many researchers created or bring in many new concepts into the field such as Higher Order FA,nilsequence,regularity lemma, etc and I am not be able to see any connection with additive and combinatorics.So I wonder is that means AddCom have already became as abstract as Alge-geom.
Im very poor in knowledge of this fields so maybe this is a stupid question,but I would be very appreciate if anyone would like to clearify that for me.
20 May, 2010 at 10:43 am
Terence Tao
I think we are getting closer to having a natural and conceptual framework for the subject, but it will probably evolve a little more. Additive combinatorics has already evolved a fair way from its roots in additive number theory and combinatorial number theory (most notably, by moving the focus away from the integers, or on special subsets of integers such as the squares or the primes, though these are of course still an important special case). Given the remarkable interconnections between additive combinatorics and ergodic theory, Fourier analysis, graph theory, geometric group theory, and even model theory and cohomology, it seems clear to me that there should be a more unified perspective that should come more into focus in the near future.
The distinction between having an abstract framework and a concrete one (or between geometric and algebraic, etc.) seems to me to be a false dichotomy, though. I think a field is healthiest when there are multiple overlapping perspectives that are compatible with and complement each other. For instance, the classical approach to algebraic geometry based on varieties and solutions to polynomial equations via elimination, invariants, etc. is still hugely important, and has been improved by the scheme-theoretic perspective rather than supplanted by it. (I myself recently used this classical theory in a paper with Ben and Emmanuel on expansion in groups; to deal with issues such as complexity of varieties, it seems better to use the classical approach than the scheme-theoretic one, at least with the current state of the art.)
21 May, 2010 at 3:57 am
tou
Thank you very much for your answer Prof.Tao. I think I really need to read more math :)
20 May, 2010 at 10:37 am
johnny :)
that’s wicked :)
31 May, 2010 at 8:45 pm
richard borcherds
A higher order inner product on a space V reminds me of a state w on the tensor algebra TV of V, as in operator algebra theory, though this would give maps from all tensor powers of V to C, not just the ones corresponding to powers of 2. These things turn up in the construction of free quantum field theories, when V is the space of 1-particle states, and w encodes the Wightman distributions of the qft. I cant figure out if this has anything to do with additive combinatorics as I’m still confused your notation.
31 May, 2010 at 9:05 pm
Terence Tao
Yes, a higher order inner product is a special type of tensor state. I think the power of two restriction is needed in order to get Hilbert-like positivity properties; possibly there would be inner products for any even exponent with some positivity (e.g. the L^6 inner product, coming from the diagonal state over 6-tensors) but most of the Hilbert-like structure seems to be lost in those cases.
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16 May, 2011 at 7:28 am
S
Prof Tao, you write above that the Gowers spaces are initially incomplete. I am trying to see this explicitly for the normed space of complex measurable functions on the circle R/Z with finite Gowers U2 norm. Do you have an example showing this space is not complete? Thank you
16 May, 2011 at 7:47 am
Terence Tao
In this case, the complete
space is the space of distributions on the unit circle whose Fourier transform has finite
norm (and is thus isomorphic to
. The incomplete space of bounded functions on the unit circle is dense in the complete
but is not all of
.
20 May, 2011 at 6:15 am
S
Thank you for your reply. Sorry if this is naive but does this incompleteness persist if one restricts the range of the functions? For instance I would very much like to see an explicit example of a sequence of [-1,1]-valued functions on the circle which is Cauchy in the U2 norm and yet does not converge in U2 to a [-1,1]-valued function. Even more restricted: can a sequence of indicator functions on the circle be Cauchy in U2 yet not converge to an indicator function (or even a real valued function) in U2? Thank you for your time.
20 May, 2011 at 7:59 am
Terence Tao
For your first question, the answer is no; U^2 convergence implies weak convergence, which preserves bounds on the range (cf. the standard fact that the closed unit ball in a normed vector space is always weakly closed).
For your second question, the answer is yes. For instance, divide the circle into N congruent intervals and let f_N be a random function that, on each such interval, is either equal to the constant +1 or the constant 0 with equal probability of each, with the sign being independent on each interval. One can then show (by Borel-Cantelli and concentration of measure) that almost surely, f_N converges in U^2 to the constant function 1/2.
More generally, one can think of convergence in U^2 (or higher) norms as a strengthened version of weak convergence which “knows” about additive structure (but cannot “see” sufficiently pseudorandom behaviour).
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22 February, 2022 at 7:32 am
Anonymous
A few somewhat vague questions, but that hopefully will make sense. Is there a notion of adjoint of an operator in a higher order space like this? Or maybe an analogue of what a “TT*” argument is to prove that certain operators are bounded?
22 February, 2022 at 11:14 am
Terence Tao
Higher order spaces are normed vector spaces, so one can define adjoints in the usual fashion. In addition there is also the useful concept of a “dual function”: for instance, in a second order Hilbert space (with inner product that I will denote by
) that is also equipped with a usual inner product (which I’ll denote as
), any three functions
in this space can (in principle at least) generate a dual function
by the formula
These dual functions play an important role in the structural theory of spaces such as the Gowers norm spaces
or the Host-Kra seminorm spaces
. Perhaps an analogue to the TT^* method in this context is the method of “stashing” a dual function in one of the inputs of a multilinear form, as used for instance recently by Manners.