In the modern theory of higher order Fourier analysis, a key role are played by the Gowers uniformity norms
for
. For finitely supported functions
, one can define the (non-normalised) Gowers norm
by the formula

where

denotes complex conjugation, and then on any discrete interval
![{[N] = \{1,\dots,N\}}](https://s0.wp.com/latex.php?latex=%7B%5BN%5D+%3D+%5C%7B1%2C%5Cdots%2CN%5C%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
and any function
![{f: [N] \rightarrow {\bf C}}](https://s0.wp.com/latex.php?latex=%7Bf%3A+%5BN%5D+%5Crightarrow+%7B%5Cbf+C%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
we can then define the (normalised) Gowers norm
![\displaystyle \|f\|_{U^k([N])} := \| f 1_{[N]} \|_{\tilde U^k({\bf Z})} / \|1_{[N]} \|_{\tilde U^k({\bf Z})}](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7Cf%5C%7C_%7BU%5Ek%28%5BN%5D%29%7D+%3A%3D+%5C%7C+f+1_%7B%5BN%5D%7D+%5C%7C_%7B%5Ctilde+U%5Ek%28%7B%5Cbf+Z%7D%29%7D+%2F+%5C%7C1_%7B%5BN%5D%7D+%5C%7C_%7B%5Ctilde+U%5Ek%28%7B%5Cbf+Z%7D%29%7D&bg=ffffff&fg=000000&s=0&c=20201002)
where
![{f 1_{[N]}: {\bf Z} \rightarrow {\bf C}}](https://s0.wp.com/latex.php?latex=%7Bf+1_%7B%5BN%5D%7D%3A+%7B%5Cbf+Z%7D+%5Crightarrow+%7B%5Cbf+C%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
is the extension of

by zero to all of

. Thus for instance
![\displaystyle \|f\|_{U^1([N])} = |\mathop{\bf E}_{n \in [N]} f(n)|](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7Cf%5C%7C_%7BU%5E1%28%5BN%5D%29%7D+%3D+%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29%7C&bg=ffffff&fg=000000&s=0&c=20201002)
(which technically makes
![{\| \|_{U^1([N])}}](https://s0.wp.com/latex.php?latex=%7B%5C%7C+%5C%7C_%7BU%5E1%28%5BN%5D%29%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
a seminorm rather than a norm), and one can calculate
![\displaystyle \|f\|_{U^2([N])} \asymp (N \int_0^1 |\mathop{\bf E}_{n \in [N]} f(n) e(-\alpha n)|^4\ d\alpha)^{1/4} \ \ \ \ \ (1)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7Cf%5C%7C_%7BU%5E2%28%5BN%5D%29%7D+%5Casymp+%28N+%5Cint_0%5E1+%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29+e%28-%5Calpha+n%29%7C%5E4%5C+d%5Calpha%29%5E%7B1%2F4%7D+%5C+%5C+%5C+%5C+%5C+%281%29&bg=ffffff&fg=000000&s=0&c=20201002)
where

, and we use the averaging notation

.
The significance of the Gowers norms is that they control other multilinear forms that show up in additive combinatorics. Given any polynomials
and functions
, we define the multilinear form
![\displaystyle \Lambda^{P_1,\dots,P_m}(f_1,\dots,f_m) := \sum_{n \in {\bf Z}^d} \prod_{j=1}^m f 1_{[N]}(P_j(n)) / \sum_{n \in {\bf Z}^d} \prod_{j=1}^m 1_{[N]}(P_j(n))](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5CLambda%5E%7BP_1%2C%5Cdots%2CP_m%7D%28f_1%2C%5Cdots%2Cf_m%29+%3A%3D+%5Csum_%7Bn+%5Cin+%7B%5Cbf+Z%7D%5Ed%7D+%5Cprod_%7Bj%3D1%7D%5Em+f+1_%7B%5BN%5D%7D%28P_j%28n%29%29+%2F+%5Csum_%7Bn+%5Cin+%7B%5Cbf+Z%7D%5Ed%7D+%5Cprod_%7Bj%3D1%7D%5Em+1_%7B%5BN%5D%7D%28P_j%28n%29%29&bg=ffffff&fg=000000&s=0&c=20201002)
(assuming that the denominator is finite and non-zero). Thus for instance
![\displaystyle \Lambda^{\mathrm{n}}(f) = \mathop{\bf E}_{n \in [N]} f(n)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5CLambda%5E%7B%5Cmathrm%7Bn%7D%7D%28f%29+%3D+%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29&bg=ffffff&fg=000000&s=0&c=20201002)
![\displaystyle \Lambda^{\mathrm{n}, \mathrm{n}+\mathrm{r}}(f,g) = (\mathop{\bf E}_{n \in [N]} f(n)) (\mathop{\bf E}_{n \in [N]} g(n))](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5CLambda%5E%7B%5Cmathrm%7Bn%7D%2C+%5Cmathrm%7Bn%7D%2B%5Cmathrm%7Br%7D%7D%28f%2Cg%29+%3D+%28%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29%29+%28%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+g%28n%29%29&bg=ffffff&fg=000000&s=0&c=20201002)
![\displaystyle \Lambda^{\mathrm{n}, \mathrm{n}+\mathrm{r}, \mathrm{n}+2\mathrm{r}}(f,g,h) \asymp \mathop{\bf E}_{n \in [N]} \mathop{\bf E}_{r \in [-N,N]} f(n) g(n+r) h(n+2r)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5CLambda%5E%7B%5Cmathrm%7Bn%7D%2C+%5Cmathrm%7Bn%7D%2B%5Cmathrm%7Br%7D%2C+%5Cmathrm%7Bn%7D%2B2%5Cmathrm%7Br%7D%7D%28f%2Cg%2Ch%29+%5Casymp+%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+%5Cmathop%7B%5Cbf+E%7D_%7Br+%5Cin+%5B-N%2CN%5D%7D+f%28n%29+g%28n%2Br%29+h%28n%2B2r%29&bg=ffffff&fg=000000&s=0&c=20201002)
![\displaystyle \Lambda^{\mathrm{n}, \mathrm{n}+\mathrm{r}, \mathrm{n}+\mathrm{r}^2}(f,g,h) \asymp \mathop{\bf E}_{n \in [N]} \mathop{\bf E}_{r \in [-N^{1/2},N^{1/2}]} f(n) g(n+r) h(n+r^2)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5CLambda%5E%7B%5Cmathrm%7Bn%7D%2C+%5Cmathrm%7Bn%7D%2B%5Cmathrm%7Br%7D%2C+%5Cmathrm%7Bn%7D%2B%5Cmathrm%7Br%7D%5E2%7D%28f%2Cg%2Ch%29+%5Casymp+%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+%5Cmathop%7B%5Cbf+E%7D_%7Br+%5Cin+%5B-N%5E%7B1%2F2%7D%2CN%5E%7B1%2F2%7D%5D%7D+f%28n%29+g%28n%2Br%29+h%28n%2Br%5E2%29&bg=ffffff&fg=000000&s=0&c=20201002)
where we view

as formal (indeterminate) variables, and
![{f,g,h: [N] \rightarrow {\bf C}}](https://s0.wp.com/latex.php?latex=%7Bf%2Cg%2Ch%3A+%5BN%5D+%5Crightarrow+%7B%5Cbf+C%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
are understood to be extended by zero to all of

. These forms are used to count patterns in various sets; for instance, the quantity

is closely related to the number of length three arithmetic progressions contained in

. Let us informally say that a form

is
controlled by the
![{U^k[N]}](https://s0.wp.com/latex.php?latex=%7BU%5Ek%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
norm if the form is small whenever
![{f_1,\dots,f_m: [N] \rightarrow {\bf C}}](https://s0.wp.com/latex.php?latex=%7Bf_1%2C%5Cdots%2Cf_m%3A+%5BN%5D+%5Crightarrow+%7B%5Cbf+C%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
are

-bounded functions with at least one of the

small in
![{U^k[N]}](https://s0.wp.com/latex.php?latex=%7BU%5Ek%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
norm. This definition was made more precise by Gowers and Wolf, who then defined the
true complexity of a form

to be the least

such that

is controlled by the
![{U^{s+1}[N]}](https://s0.wp.com/latex.php?latex=%7BU%5E%7Bs%2B1%7D%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
norm. For instance,
-
and
have true complexity
;
-
has true complexity
;
-
has true complexity
;
- The form
(which among other things could be used to count twin primes) has infinite true complexity (which is quite unfortunate for applications).
Roughly speaking, patterns of complexity

or less are amenable to being studied by classical Fourier analytic tools (the Hardy-Littlewood circle method); patterns of higher complexity can be handled (in principle, at least) by the methods of higher order Fourier analysis; and patterns of infinite complexity are out of range of both methods and are generally quite difficult to study. See
these recent slides of myself for some further discussion.
Gowers and Wolf formulated a conjecture on what this complexity should be, at least for linear polynomials
; Ben Green and I thought we had resolved this conjecture back in 2010, though it turned out there was a subtle gap in our arguments and we were only able to resolve the conjecture in a partial range of cases. However, the full conjecture was recently resolved by Daniel Altman.
The
(semi-)norm is so weak that it barely controls any averages at all. For instance the average
![\displaystyle \Lambda^{2\mathrm{n}}(f) = \mathop{\bf E}_{n \in [N], \hbox{ even}} f(n)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5CLambda%5E%7B2%5Cmathrm%7Bn%7D%7D%28f%29+%3D+%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%2C+%5Chbox%7B+even%7D%7D+f%28n%29&bg=ffffff&fg=000000&s=0&c=20201002)
is not controlled by the
![{U^1[N]}](https://s0.wp.com/latex.php?latex=%7BU%5E1%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
semi-norm: it is perfectly possible for a

-bounded function
![{f: [N] \rightarrow {\bf C}}](https://s0.wp.com/latex.php?latex=%7Bf%3A+%5BN%5D+%5Crightarrow+%7B%5Cbf+C%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
to even have vanishing
![{U^1([N])}](https://s0.wp.com/latex.php?latex=%7BU%5E1%28%5BN%5D%29%7D&bg=ffffff&fg=000000&s=0&c=20201002)
norm but have large value of

(consider for instance the parity function

).
Because of this, I propose inserting an additional norm in the Gowers uniformity norm hierarchy between the
and
norms, which I will call the
(or “profinite
“) norm:
![\displaystyle \| f\|_{U^{1^+}[N]} := \frac{1}{N} \sup_P |\sum_{n \in P} f(n)| = \sup_P | \mathop{\bf E}_{n \in [N]} f 1_P(n)|](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7C+f%5C%7C_%7BU%5E%7B1%5E%2B%7D%5BN%5D%7D+%3A%3D+%5Cfrac%7B1%7D%7BN%7D+%5Csup_P+%7C%5Csum_%7Bn+%5Cin+P%7D+f%28n%29%7C+%3D+%5Csup_P+%7C+%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f+1_P%28n%29%7C&bg=ffffff&fg=000000&s=0&c=20201002)
where

ranges over all arithmetic progressions in
![{[N]}](https://s0.wp.com/latex.php?latex=%7B%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
. This can easily be seen to be a norm on functions
![{f: [N] \rightarrow {\bf C}}](https://s0.wp.com/latex.php?latex=%7Bf%3A+%5BN%5D+%5Crightarrow+%7B%5Cbf+C%7D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
that controls the
![{U^1[N]}](https://s0.wp.com/latex.php?latex=%7BU%5E1%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
norm. It is also basically controlled by the
![{U^2[N]}](https://s0.wp.com/latex.php?latex=%7BU%5E2%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
norm for

-bounded functions

; indeed, if

is an arithmetic progression in
![{[N]}](https://s0.wp.com/latex.php?latex=%7B%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
of some spacing

, and if

be a standard bump function supported on
![{[-1,1]}](https://s0.wp.com/latex.php?latex=%7B%5B-1%2C1%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
with total mass and

is a parameter then
![\displaystyle \mathop{\bf E}_{n \in [N]} f 1_P(n) \ll |\mathop{\bf E}_{n \in [N]; h, k \in [-N,N]} \frac{1}{\delta} \psi(\frac{h}{\delta N}) 1_{q|h} 1_P(n+k) f(n+h+k)| + \delta](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f+1_P%28n%29+%5Cll+%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%3B+h%2C+k+%5Cin+%5B-N%2CN%5D%7D+%5Cfrac%7B1%7D%7B%5Cdelta%7D+%5Cpsi%28%5Cfrac%7Bh%7D%7B%5Cdelta+N%7D%29+1_%7Bq%7Ch%7D+1_P%28n%2Bk%29+f%28n%2Bh%2Bk%29%7C+%2B+%5Cdelta+&bg=ffffff&fg=000000&s=0&c=20201002)
which after some Fourier expansion of

gives
![\displaystyle \mathop{\bf E}_{n \in [N]} f 1_P(n) \ll \frac{1}{\delta} \sup_\alpha |\mathop{\bf E}_{n \in [N]; h, k \in [-N,N]} e(\alpha h) 1_P(n+k) f(n+h+k)| + \delta.](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f+1_P%28n%29+%5Cll+%5Cfrac%7B1%7D%7B%5Cdelta%7D+%5Csup_%5Calpha+%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%3B+h%2C+k+%5Cin+%5B-N%2CN%5D%7D+e%28%5Calpha+h%29+1_P%28n%2Bk%29+f%28n%2Bh%2Bk%29%7C+%2B+%5Cdelta.&bg=ffffff&fg=000000&s=0&c=20201002)
Writing

and using the Gowers–Cauchy–Schwarz inequality, we conclude
![\displaystyle \mathop{\bf E}_{n \in [N]} f 1_P(n) \ll \frac{1}{\delta} \|f\|_{U^2([N])} + \delta](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f+1_P%28n%29+%5Cll+%5Cfrac%7B1%7D%7B%5Cdelta%7D+%5C%7Cf%5C%7C_%7BU%5E2%28%5BN%5D%29%7D+%2B+%5Cdelta&bg=ffffff&fg=000000&s=0&c=20201002)
hence on optimising in

we have
![\displaystyle \| f\|_{U^{1^+}[N]} \ll \|f\|_{U^2[N]}^{1/2}.](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7C+f%5C%7C_%7BU%5E%7B1%5E%2B%7D%5BN%5D%7D+%5Cll+%5C%7Cf%5C%7C_%7BU%5E2%5BN%5D%7D%5E%7B1%2F2%7D.&bg=ffffff&fg=000000&s=0&c=20201002)
Forms which are controlled by the

norm (but not

) would then have their true complexity adjusted to

with this insertion.
The
norm recently appeared implicitly in work of Peluse and Prendiville, who showed that the form
had true complexity
in this notation (with polynomially strong bounds). [Actually, strictly speaking this control was only shown for the third function
; for the first two functions
one needs to localize the
norm to intervals of length
. But I will ignore this technical point to keep the exposition simple.] The weaker claim that
has true complexity
is substantially easier to prove (one can apply the circle method together with Gauss sum estimates).
The well known inverse theorem for the
norm tells us that if a
-bounded function
has
norm at least
for some
, then there is a Fourier phase
such that
![\displaystyle |\mathop{\bf E}_{n \in [N]} f(n) e(-\alpha n)| \gg \eta^2;](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29+e%28-%5Calpha+n%29%7C+%5Cgg+%5Ceta%5E2%3B&bg=ffffff&fg=000000&s=0&c=20201002)
this follows easily from
(1) and Plancherel’s theorem. Conversely, from the Gowers–Cauchy–Schwarz inequality one has
![\displaystyle |\mathop{\bf E}_{n \in [N]} f(n) e(-\alpha n)| \ll \|f\|_{U^2[N]}.](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29+e%28-%5Calpha+n%29%7C+%5Cll+%5C%7Cf%5C%7C_%7BU%5E2%5BN%5D%7D.&bg=ffffff&fg=000000&s=0&c=20201002)
For
one has a trivial inverse theorem; by definition, the
norm of
is at least
if and only if
![\displaystyle |\mathop{\bf E}_{n \in [N]} f(n)| \geq \eta.](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29%7C+%5Cgeq+%5Ceta.&bg=ffffff&fg=000000&s=0&c=20201002)
Thus the frequency

appearing in the

inverse theorem can be taken to be zero when working instead with the

norm.
For
one has the intermediate situation in which the frequency
is not taken to be zero, but is instead major arc. Indeed, suppose that
is
-bounded with
, thus
![\displaystyle |\mathop{\bf E}_{n \in [N]} 1_P(n) f(n)| \geq \eta](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+1_P%28n%29+f%28n%29%7C+%5Cgeq+%5Ceta&bg=ffffff&fg=000000&s=0&c=20201002)
for some progression

. This forces the spacing

of this progression to be

. We write the above inequality as
![\displaystyle |\mathop{\bf E}_{n \in [N]} 1_{n=b\ (q)} 1_I(n) f(n)| \geq \eta](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+1_%7Bn%3Db%5C+%28q%29%7D+1_I%28n%29+f%28n%29%7C+%5Cgeq+%5Ceta&bg=ffffff&fg=000000&s=0&c=20201002)
for some residue class

and some interval

. By Fourier expansion and the triangle inequality we then have
![\displaystyle |\mathop{\bf E}_{n \in [N]} e(-an/q) 1_I(n) f(n)| \geq \eta](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+e%28-an%2Fq%29+1_I%28n%29+f%28n%29%7C+%5Cgeq+%5Ceta&bg=ffffff&fg=000000&s=0&c=20201002)
for some integer

. Convolving

by

for

a small multiple of

and

a Schwartz function of unit mass with Fourier transform supported on
![{[-1,1]}](https://s0.wp.com/latex.php?latex=%7B%5B-1%2C1%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
, we have
![\displaystyle |\mathop{\bf E}_{n \in [N]} e(-an/q) (1_I * \psi_\delta)(n) f(n)| \gg \eta.](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+e%28-an%2Fq%29+%281_I+%2A+%5Cpsi_%5Cdelta%29%28n%29+f%28n%29%7C+%5Cgg+%5Ceta.&bg=ffffff&fg=000000&s=0&c=20201002)
The Fourier transform of

is bounded and supported on
![{[-1/\delta,1/\delta]}](https://s0.wp.com/latex.php?latex=%7B%5B-1%2F%5Cdelta%2C1%2F%5Cdelta%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
, thus by Fourier expansion and the triangle inequality we have
![\displaystyle |\mathop{\bf E}_{n \in [N]} e(-an/q) e(-\xi n) f(n)| \gg \eta](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+e%28-an%2Fq%29+e%28-%5Cxi+n%29+f%28n%29%7C+%5Cgg+%5Ceta&bg=ffffff&fg=000000&s=0&c=20201002)
for some
![{\xi \in [-1/\delta,1/\delta]}](https://s0.wp.com/latex.php?latex=%7B%5Cxi+%5Cin+%5B-1%2F%5Cdelta%2C1%2F%5Cdelta%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
, so in particular

. Thus we have
![\displaystyle |\mathop{\bf E}_{n \in [N]} f(n) e(-\alpha n)| \gg \eta \ \ \ \ \ (2)](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29+e%28-%5Calpha+n%29%7C+%5Cgg+%5Ceta+%5C+%5C+%5C+%5C+%5C+%282%29&bg=ffffff&fg=000000&s=0&c=20201002)
for some

of the major arc form

with

. Conversely, for

of this form, some routine summation by parts gives the bound
![\displaystyle |\mathop{\bf E}_{n \in [N]} f(n) e(-\alpha n)| \ll \frac{q}{\eta} \|f\|_{U^{1^+}[N]} \ll \frac{1}{\eta^2} \|f\|_{U^{1^+}[N]}](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+f%28n%29+e%28-%5Calpha+n%29%7C+%5Cll+%5Cfrac%7Bq%7D%7B%5Ceta%7D+%5C%7Cf%5C%7C_%7BU%5E%7B1%5E%2B%7D%5BN%5D%7D+%5Cll+%5Cfrac%7B1%7D%7B%5Ceta%5E2%7D+%5C%7Cf%5C%7C_%7BU%5E%7B1%5E%2B%7D%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
so if
(2) holds for a

-bounded

then one must have
![{\|f\|_{U^{1^+}[N]} \gg \eta^3}](https://s0.wp.com/latex.php?latex=%7B%5C%7Cf%5C%7C_%7BU%5E%7B1%5E%2B%7D%5BN%5D%7D+%5Cgg+%5Ceta%5E3%7D&bg=ffffff&fg=000000&s=0&c=20201002)
.
Here is a diagram showing some of the control relationships between various Gowers norms, multilinear forms, and duals of classes
of functions (where each class of functions
induces a dual norm
:

The Gowers norms have counterparts for measure-preserving systems
, known as Host-Kra seminorms. The
norm can be defined for
as
![\displaystyle \|f\|_{U^1(X)} := \lim_{N \rightarrow \infty} \int_X |\mathop{\bf E}_{n \in [N]} T^n f|\ d\mu](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7Cf%5C%7C_%7BU%5E1%28X%29%7D+%3A%3D+%5Clim_%7BN+%5Crightarrow+%5Cinfty%7D+%5Cint_X+%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+T%5En+f%7C%5C+d%5Cmu&bg=ffffff&fg=000000&s=0&c=20201002)
and the

norm can be defined as
![\displaystyle \|f\|_{U^2(X)}^4 := \lim_{N \rightarrow \infty} \mathop{\bf E}_{n \in [N]} \| T^n f \overline{f} \|_{U^1(X)}^2.](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7Cf%5C%7C_%7BU%5E2%28X%29%7D%5E4+%3A%3D+%5Clim_%7BN+%5Crightarrow+%5Cinfty%7D+%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+%5C%7C+T%5En+f+%5Coverline%7Bf%7D+%5C%7C_%7BU%5E1%28X%29%7D%5E2.&bg=ffffff&fg=000000&s=0&c=20201002)
The

seminorm is orthogonal to the
invariant factor 
(generated by the (almost everywhere) invariant measurable subsets of

) in the sense that a function

has vanishing

seminorm if and only if it is orthogonal to all

-measurable (bounded) functions. Similarly, the

norm is orthogonal to the
Kronecker factor 
, generated by the eigenfunctions of

(that is to say, those

obeying an identity

for some

-invariant

); for ergodic systems, it is the largest factor isomorphic to rotation on a compact abelian group. In analogy to the Gowers
![{U^{1^+}[N]}](https://s0.wp.com/latex.php?latex=%7BU%5E%7B1%5E%2B%7D%5BN%5D%7D&bg=ffffff&fg=000000&s=0&c=20201002)
norm, one can then define the Host-Kra

seminorm by
![\displaystyle \|f\|_{U^{1^+}(X)} := \sup_{q \geq 1} \frac{1}{q} \lim_{N \rightarrow \infty} \int_X |\mathop{\bf E}_{n \in [N]} T^{qn} f|\ d\mu;](https://s0.wp.com/latex.php?latex=%5Cdisplaystyle++%5C%7Cf%5C%7C_%7BU%5E%7B1%5E%2B%7D%28X%29%7D+%3A%3D+%5Csup_%7Bq+%5Cgeq+1%7D+%5Cfrac%7B1%7D%7Bq%7D+%5Clim_%7BN+%5Crightarrow+%5Cinfty%7D+%5Cint_X+%7C%5Cmathop%7B%5Cbf+E%7D_%7Bn+%5Cin+%5BN%5D%7D+T%5E%7Bqn%7D+f%7C%5C+d%5Cmu%3B&bg=ffffff&fg=000000&s=0&c=20201002)
it is orthogonal to the
profinite factor 
, generated by the periodic sets of

(or equivalently, by those eigenfunctions whose eigenvalue is a root of unity); for ergodic systems, it is the largest factor isomorphic to rotation on a profinite abelian group.