Montgomery’s uncertainty principle

One of the most fundamental principles in Fourier analysis is the uncertainty principle. It does not have a single canonical formulation, but one typical informal description of the principle is that if a function is restricted to a narrow region of physical space, then its Fourier transform must be necessarily “smeared out” over a broad region of frequency space. Some versions of the uncertainty principle are discussed in this previous blog post.

In this post I would like to highlight a useful instance of the uncertainty principle, due to Hugh Montgomery, which is useful in analytic number theory contexts. Specifically, suppose we are given a complex-valued function on the integers. To avoid irrelevant issues at spatial infinity, we will assume that the support of this function is finite (in practice, we will only work with functions that are supported in an interval for some natural numbers ). Then we can define the Fourier transform by the formula

where . (In some literature, the sign in the exponential phase is reversed, but this will make no substantial difference to the arguments below.)

The classical uncertainty principle, in this context, asserts that if is localised in an interval of length , then must be “smeared out” at a scale of at least (and essentially constant at scales less than ). For instance, if is supported in , then we have the Plancherel identity

while from the Cauchy-Schwarz inequality we have

for each frequency , and in particular that

for any arc in the unit circle (with denoting the length of ). In particular, an interval of length significantly less than can only capture a fraction of the energy of the Fourier transform of , which is consistent with the above informal statement of the uncertainty principle.

Another manifestation of the classical uncertainty principle is the large sieve inequality. A particularly nice formulation of this inequality is due independently to Montgomery and Vaughan and Selberg: if is supported in , and are frequencies in that are -separated for some , thus for all (where denotes the distance of to the origin in ), then

The reader is encouraged to see how this inequality is consistent with the Plancherel identity (1) and the intuition that is essentially constant at scales less than . The factor can in fact be amplified a little bit to , which is essentially optimal, by using a neat dilation trick of Paul Cohen, in which one dilates to (and replaces each frequency by their roots), and then sending (cf. the tensor product trick); see this survey of Montgomery for details. But we will not need this refinement here.

In the above instances of the uncertainty principle, the concept of narrow support in physical space was formalised in the Archimedean sense, using the standard Archimedean metric on the integers (in particular, the parameter is essentially the Archimedean diameter of the support of ). However, in number theory, the Archimedean metric is not the only metric of importance on the integers; the -adic metrics play an equally important role; indeed, it is common to unify the Archimedean and -adic perspectives together into a unified adelic perspective. In the -adic world, the metric balls are no longer intervals, but are instead residue classes modulo some power of . Intersecting these balls from different -adic metrics together, we obtain residue classes with respect to various moduli (which may be either prime or composite). As such, another natural manifestation of the concept of “narrow support in physical space” is “vanishes on many residue classes modulo “. This notion of narrowness is particularly common in sieve theory, when one deals with functions supported on thin sets such as the primes, which naturally tend to avoid many residue classes (particularly if one throws away the first few primes).

In this context, the uncertainty principle is this: the more residue classes modulo that avoids, the more the Fourier transform must spread out along multiples of . To illustrate a very simple example of this principle, let us take , and suppose that is supported only on odd numbers (thus it completely avoids the residue class ). We write out the formulae for and :

If is supported on the odd numbers, then is always equal to on the support of , and so we have . Thus, whenever has a significant presence at a frequency , it also must have an equally significant presence at the frequency ; there is a spreading out across multiples of . Note that one has a similar effect if was supported instead on the even integers instead of the odd integers.

A little more generally, suppose now that avoids a single residue class modulo a prime ; for sake of argument let us say that it avoids the zero residue class , although the situation for the other residue classes is similar. For any frequency and any , one has

From basic Fourier analysis, we know that the phases sum to zero as ranges from to whenever is not a multiple of . We thus have

In particular, if is large, then one of the other has to be somewhat large as well; using the Cauchy-Schwarz inequality, we can quantify this assertion in an sense via the inequality

Let us continue this analysis a bit further. Now suppose that avoids residue classes modulo a prime , for some . (We exclude the case as it is clearly degenerates by forcing to be identically zero.) Let be the function that equals on these residue classes and zero away from these residue classes, then

Using the periodic Fourier transform, we can write

for some coefficients , thus

Some Fourier-analytic computations reveal that

and

and so after some routine algebra and the Cauchy-Schwarz inequality, we obtain a generalisation of (3):

Thus we see that the more residue classes mod we exclude, the more Fourier energy has to disperse along multiples of . It is also instructive to consider the extreme case , in which is supported on just a single residue class ; in this case, one clearly has , and so spreads its energy completely evenly along multiples of .

In 1968, Montgomery observed the following useful generalisation of the above calculation to arbitrary modulus:

Proposition 1 (Montgomery’s uncertainty principle) Let be a finitely supported function which, for each prime , avoids residue classes modulo for some . Then for each natural number , one has

where is the quantity

where is the Möbius function.

We give a proof of this proposition below the fold.

Following the “adelic” philosophy, it is natural to combine this uncertainty principle with the large sieve inequality to take simultaneous advantage of localisation both in the Archimedean sense and in the -adic senses. This leads to the following corollary:

Corollary 2 (Arithmetic large sieve inequality) Let be a function supported on an interval which, for each prime , avoids residue classes modulo for some . Let , and let be a finite set of natural numbers. Suppose that the frequencies with , , and are -separated. Then one has

where was defined in (4).

Indeed, from the large sieve inequality one has

while from Proposition 1 one has

whence the claim.

There is a great deal of flexibility in the above inequality, due to the ability to select the set , the frequencies , the omitted classes , and the separation parameter . Here is a typical application concerning the original motivation for the large sieve inequality, namely in bounding the size of sets which avoid many residue classes:

Corollary 3 (Large sieve) Let be a set of integers contained in which avoids residue classes modulo for each prime , and let . Then

where

Proof: We apply Corollary 2 with , , , , and . The key point is that the Farey sequence of fractions with and is -separated, since

whenever are distinct fractions in this sequence.

If, for instance, is the set of all primes in larger than , then one can set for all , which makes , where is the Euler totient function. It is a classical estimate that

Using this fact and optimising in , we obtain (a special case of) the Brun-Titchmarsh inequality

where is the prime counting function; a variant of the same argument gives the more general Brun-Titchmarsh inequality

for any primitive residue class , where is the number of primes less than or equal to that are congruent to . By performing a more careful optimisation using a slightly sharper version of the large sieve inequality (2) that exploits the irregular spacing of the Farey sequence, Montgomery and Vaughan were able to delete the error term in the Brun-Titchmarsh inequality, thus establishing the very nice inequality

for any natural numbers with . This is a particularly useful inequality in non-asymptotic analytic number theory (when one wishes to study number theory at explicit orders of magnitude, rather than the number theory of sufficiently large numbers), due to the absence of asymptotic notation.

I recently realised that Corollary 2 also establishes a stronger version of the “restriction theorem for the Selberg sieve” that Ben Green and I proved some years ago (indeed, one can view Corollary 2 as a “restriction theorem for the large sieve”). I’m placing the details below the fold.