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Two of the most famous open problems in additive prime number theory are the twin prime conjecture and the binary Goldbach conjecture. They have quite similar forms:
- Twin prime conjecture The equation has infinitely many solutions with prime.
- Binary Goldbach conjecture The equation has at least one solution with prime for any given even .
In view of this similarity, it is not surprising that the partial progress on these two conjectures have tracked each other fairly closely; the twin prime conjecture is generally considered slightly easier than the binary Goldbach conjecture, but broadly speaking any progress made on one of the conjectures has also led to a comparable amount of progress on the other. (For instance, Chen’s theorem has a version for the twin prime conjecture, and a version for the binary Goldbach conjecture.) Also, the notorious parity obstruction is present in both problems, preventing a solution to either conjecture by almost all known methods (see this previous blog post for more discussion).
In this post, I would like to note a divergence from this general principle, with regards to bounded error versions of these two conjectures:
- Twin prime with bounded error The inequalities has infinitely many solutions with prime for some absolute constant .
- Binary Goldbach with bounded error The inequalities has at least one solution with prime for any sufficiently large and some absolute constant .
The first of these statements is now a well-known theorem of Zhang, and the Polymath8b project hosted on this blog has managed to lower to unconditionally, and to assuming the generalised Elliott-Halberstam conjecture. However, the second statement remains open; the best result that the Polymath8b project could manage in this direction is that (assuming GEH) at least one of the binary Goldbach conjecture with bounded error, or the twin prime conjecture with no error, had to be true.
All the known proofs of Zhang’s theorem proceed through sieve-theoretic means. Basically, they take as input equidistribution results that control the size of discrepancies such as
for various congruence classes and various arithmetic functions , e.g. (or more generaly for various ). After taking some carefully chosen linear combinations of these discrepancies, and using the trivial positivity lower bound
one eventually obtains (for suitable ) a non-trivial lower bound of the form
where is some weight function, and is the set of such that there are at least two primes in the interval . This implies at least one solution to the inequalities with , and Zhang’s theorem follows.
In a similar vein, one could hope to use bounds on discrepancies such as (1) (for comparable to ), together with the trivial lower bound (2), to obtain (for sufficiently large , and suitable ) a non-trivial lower bound of the form
for some weight function , where is the set of such that there is at least one prime in each of the intervals and . This would imply the binary Goldbach conjecture with bounded error.
However, the parity obstruction blocks such a strategy from working (for much the same reason that it blocks any bound of the form in Zhang’s theorem, as discussed in the Polymath8b paper.) The reason is as follows. The sieve-theoretic arguments are linear with respect to the summation, and as such, any such sieve-theoretic argument would automatically also work in a weighted setting in which the summation is weighted by some non-negative weight . More precisely, if one could control the weighted discrepancies
to essentially the same accuracy as the unweighted discrepancies (1), then thanks to the trivial weighted version
of (2), any sieve-theoretic argument that was capable of proving (3) would also be capable of proving the weighted estimate
However, (4) may be defeated by a suitable choice of weight , namely
where is the Liouville function, which counts the parity of the number of prime factors of a given number . Since , one can expand out as the sum of and a finite number of other terms, each of which consists of the product of two or more translates (or reflections) of . But from the Möbius randomness principle (or its analogue for the Liouville function), such products of are widely expected to be essentially orthogonal to any arithmetic function that is arising from a single multiplicative function such as , even on very short arithmetic progressions. As such, replacing by in (1) should have a negligible effect on the discrepancy. On the other hand, in order for to be non-zero, has to have the same sign as and hence the opposite sign to cannot simultaneously be prime for any , and so vanishes identically, contradicting (4). This indirectly rules out any modification of the Goldston-Pintz-Yildirim/Zhang method for establishing the binary Goldbach conjecture with bounded error.
The above argument is not watertight, and one could envisage some ways around this problem. One of them is that the Möbius randomness principle could simply be false, in which case the parity obstruction vanishes. A good example of this is the result of Heath-Brown that shows that if there are infinitely many Siegel zeroes (which is a strong violation of the Möbius randomness principle), then the twin prime conjecture holds. Another way around the obstruction is to start controlling the discrepancy (1) for functions that are combinations of more than one multiplicative function, e.g. . However, controlling such functions looks to be at least as difficult as the twin prime conjecture (which is morally equivalent to obtaining non-trivial lower-bounds for ). A third option is not to use a sieve-theoretic argument, but to try a different method (e.g. the circle method). However, most other known methods also exhibit linearity in the “” variable and I would suspect they would be vulnerable to a similar obstruction. (In any case, the circle method specifically has some other difficulties in tackling binary problems, as discussed in this previous post.)
This post is a continuation of the previous post on sieve theory, which is an ongoing part of the Polymath8 project. As the previous post was getting somewhat full, we are rolling the thread over to the current post. We also take the opportunity to correct some errors in the treatment of the truncated GPY sieve from this previous post.
As usual, we let be a large asymptotic parameter, and a sufficiently slowly growing function of . Let and be such that holds (see this previous post for a definition of this assertion). We let be a fixed admissible -tuple, let , let be the square-free numbers with prime divisors in , and consider the truncated GPY sieve
where
where , is the polynomial
and is a fixed smooth function supported on . As discussed in the previous post, we are interested in obtaining an upper bound of the form
as well as a lower bound of the form
for all (where when is prime and otherwise), since this will give the conjecture (i.e. infinitely many prime gaps of size at most ) whenever
It turns out we in fact have precise asymptotics
although the exact formulae for are a little complicated. (The fact that could be computed exactly was already anticipated in Zhang’s paper; see the remark on page 24.) We proceed as in the previous post. Indeed, from the arguments in that post, (2) is equivalent to
and (3) is similarly equivalent to
Here is the number of prime factors of .
We will work for now with (4), as the treatment of (5) is almost identical.
We would now like to replace the truncated interval with the untruncated interval , where . Unfortunately this replacement was not quite done correctly in the previous post, and this will now be corrected here. We first observe that if is any finitely supported function, then by Möbius inversion we have
Note that if and only if we have a factorisation , with and coprime to , and that this factorisation is unique. From this, we see that we may rearrange the previous expression as
Applying this to (4), and relabeling as , we conclude that the left-hand side of (4) is equal to
This is almost the same formula that we had in the previous post, except that the Möbius function of the greatest common divisor of was missing, and also the coprimality condition was not handled properly in the previous post.
We may now eliminate the condition as follows. Suppose that there is a prime that divides both and . The expression
can then be bounded by
which may be factorised as
which by Mertens’ theorem (or the simple pole of at ) is
Summing over all gives a negligible contribution to (6) for the purposes of (4). Thus we may effectively replace (6) by
The inner summation can be treated using Proposition 10 of the previous post. We can then reduce (4) to
Note that vanishes if or . In practice, we will work with functions in which has a definite sign (in our normalisations, will be non-positive), making non-negative.
We rewrite the left-hand side of (7) as
We may factor for some with ; in particular, . The previous expression now becomes
Using Mertens’ theorem, we thus conclude an exact formula for , and similarly for :
Proposition 1 (Exact formula) We have
where
Similarly we have
where and are defined similarly to and by replacing all occurrences of with .
These formulae are unwieldy. However if we make some monotonicity hypotheses, namely that is positive, is negative, and is positive on , then we can get some good estimates on the (which are now non-negative functions) and hence on . Namely, if is negative but increasing then we have
for and , which implies that
for any . A similar argument in fact gives
for any . Iterating this we conclude that
and similarly
From Cauchy-Schwarz we thus have
Observe from the binomial formula that of the pairs with , of them have even, and of them have odd. We thus have
We have thus established the upper bound
By symmetry we may factorise
The expression is explicitly computable for any given . Following the recent preprint of Pintz, one can get a slightly looser, but cleaner, bound by using the upper bound
and so
Note that
and hence
where
In practice we expect the term to dominate, thus we have the heuristic approximation
Now we turn to the estimation of . We have an analogue of (8), namely
But we have an improvment in the lower bound in the case, because in this case we have
From the positive decreasing nature of we see that and so is non-negative and can thus be ignored for the purposes of lower bounds. (There are similar improvements available for higher but this seems to only give negligible improvements and will not be pursued here.) Thus we obtain
Estimating similarly to we conclude that
where
By (9), (10), we see that the condition (1) is implied by
By Theorem 14 and Lemma 15 of this previous post, we may take the ratio to be arbitrarily close to . We conclude the following theorem.
Theorem 2 Let and be such that holds. Let be an integer, define
and
and suppose that
Then holds.
As noted earlier, we heuristically have
and is negligible. This constraint is a bit better than the previous condition, in which was not present and was replaced by a quantity roughly of the form .
This post is a continuation of the previous post on sieve theory, which is an ongoing part of the Polymath8 project to improve the various parameters in Zhang’s proof that bounded gaps between primes occur infinitely often. Given that the comments on that page are getting quite lengthy, this is also a good opportunity to “roll over” that thread.
We will continue the notation from the previous post, including the concept of an admissible tuple, the use of an asymptotic parameter going to infinity, and a quantity depending on that goes to infinity sufficiently slowly with , and (the -trick).
The objective of this portion of the Polymath8 project is to make as efficient as possible the connection between two types of results, which we call and . Let us first state , which has an integer parameter :
Conjecture 1 () Let be a fixed admissible -tuple. Then there are infinitely many translates of which contain at least two primes.
Zhang was the first to prove a result of this type with . Since then the value of has been lowered substantially; at this time of writing, the current record is .
There are two basic ways known currently to attain this conjecture. The first is to use the Elliott-Halberstam conjecture for some :
Conjecture 2 () One has
for all fixed . Here we use the abbreviation for .
Here of course is the von Mangoldt function and the Euler totient function. It is conjectured that holds for all , but this is currently only known for , an important result known as the Bombieri-Vinogradov theorem.
In a breakthrough paper, Goldston, Yildirim, and Pintz established an implication of the form
for any , where depends on . This deduction was very recently optimised by Farkas, Pintz, and Revesz and also independently in the comments to the previous blog post, leading to the following implication:
Theorem 3 (EH implies DHL) Let be a real number, and let be an integer obeying the inequality
where is the first positive zero of the Bessel function . Then implies .
Note that the right-hand side of (2) is larger than , but tends asymptotically to as . We give an alternate proof of Theorem 3 below the fold.
Implications of the form Theorem 3 were modified by Motohashi and Pintz, which in our notation replaces by an easier conjecture for some and , at the cost of degrading the sufficient condition (2) slightly. In our notation, this conjecture takes the following form for each choice of parameters :
Conjecture 4 () Let be a fixed -tuple (not necessarily admissible) for some fixed , and let be a primitive residue class. Then
for any fixed , where , are the square-free integers whose prime factors lie in , and is the quantity
and is the set of congruence classes
and is the polynomial
This is a weakened version of the Elliott-Halberstam conjecture:
Proposition 5 (EH implies MPZ) Let and . Then implies for any . (In abbreviated form: implies .)
In particular, since is conjecturally true for all , we conjecture to be true for all and .
Proof: Define
then the hypothesis (applied to and and then subtracting) tells us that
for any fixed . From the Chinese remainder theorem and the Siegel-Walfisz theorem we have
for any coprime to (and in particular for ). Since , where is the number of prime divisors of , we can thus bound the left-hand side of (3) by
The contribution of the second term is by standard estimates (see Proposition 8 below). Using the very crude bound
and standard estimates we also have
and the claim now follows from the Cauchy-Schwarz inequality.
In practice, the conjecture is easier to prove than due to the restriction of the residue classes to , and also the restriction of the modulus to -smooth numbers. Zhang proved for any . More recently, our Polymath8 group has analysed Zhang’s argument (using in part a corrected version of the analysis of a recent preprint of Pintz) to obtain whenever are such that
The work of Motohashi and Pintz, and later Zhang, implicitly describe arguments that allow one to deduce from provided that is sufficiently large depending on . The best implication of this sort that we have been able to verify thus far is the following result, established in the previous post:
Theorem 6 (MPZ implies DHL) Let , , and let be an integer obeying the constraint
Then implies .
This complicated version of is roughly of size . It is unlikely to be optimal; the work of Motohashi-Pintz and Pintz suggests that it can essentially be improved to , but currently we are unable to verify this claim. One of the aims of this post is to encourage further discussion as to how to improve the term in results such as Theorem 6.
We remark that as (5) is an open condition, it is unaffected by infinitesimal modifications to , and so we do not ascribe much importance to such modifications (e.g. replacing by for some arbitrarily small ).
The known deductions of from claims such as or rely on the following elementary observation of Goldston, Pintz, and Yildirim (essentially a weighted pigeonhole principle), which we have placed in “-tricked form”:
Lemma 7 (Criterion for DHL) Let . Suppose that for each fixed admissible -tuple and each congruence class such that is coprime to for all , one can find a non-negative weight function , fixed quantities , a quantity , and a fixed positive power of such that one has the upper bound
for all , and the key inequality
holds. Then holds. Here is defined to equal when is prime and otherwise.
By (6), (7), this quantity is at least
By (8), this expression is positive for all sufficiently large . On the other hand, (9) can only be positive if at least one summand is positive, which only can happen when contains at least two primes for some with . Letting we obtain as claimed.
In practice, the quantity (referred to as the sieve level) is a power of such as or , and reflects the strength of the distribution hypothesis or that is available; the quantity will also be a key parameter in the definition of the sieve weight . The factor reflects the order of magnitude of the expected density of in the residue class ; it could be absorbed into the sieve weight by dividing that weight by , but it is convenient to not enforce such a normalisation so as not to clutter up the formulae. In practice, will some combination of and .
Once one has decided to rely on Lemma 7, the next main task is to select a good weight for which the ratio is as small as possible (and for which the sieve level is as large as possible. To ensure non-negativity, we use the Selberg sieve
for some weights vanishing for that are to be chosen, where is an interval and is the polynomial . If the distribution hypothesis is , one takes and ; if the distribution hypothesis is instead , one takes and .
One has a useful amount of flexibility in selecting the weights for the Selberg sieve. The original work of Goldston, Pintz, and Yildirim, as well as the subsequent paper of Zhang, the choice
is used for some additional parameter to be optimised over. More generally, one can take
for some suitable (in particular, sufficiently smooth) cutoff function . We will refer to this choice of sieve weights as the “analytic Selberg sieve”; this is the choice used in the analysis in the previous post.
However, there is a slight variant choice of sieve weights that one can use, which I will call the “elementary Selberg sieve”, and it takes the form
for a sufficiently smooth function , where
for is a -variant of the Euler totient function, and
for is a -variant of the function . (The derivative on the cutoff is convenient for computations, as will be made clearer later in this post.) This choice of weights may seem somewhat arbitrary, but it arises naturally when considering how to optimise the quadratic form
(which arises naturally in the estimation of in (6)) subject to a fixed value of (which morally is associated to the estimation of in (7)); this is discussed in any sieve theory text as part of the general theory of the Selberg sieve, e.g. Friedlander-Iwaniec.
The use of the elementary Selberg sieve for the bounded prime gaps problem was studied by Motohashi and Pintz. Their arguments give an alternate derivation of from for sufficiently large, although unfortunately we were not able to confirm some of their calculations regarding the precise dependence of on , and in particular we have not yet been able to improve upon the specific criterion in Theorem 6 using the elementary sieve. However it is quite plausible that such improvements could become available with additional arguments.
Below the fold we describe how the elementary Selberg sieve can be used to reprove Theorem 3, and discuss how they could potentially be used to improve upon Theorem 6. (But the elementary Selberg sieve and the analytic Selberg sieve are in any event closely related; see the appendix of this paper of mine with Ben Green for some further discussion.) For the purposes of polymath8, either developing the elementary Selberg sieve or continuing the analysis of the analytic Selberg sieve from the previous post would be a relevant topic of conversation in the comments to this post.
Suppose one is given a -tuple of distinct integers for some , arranged in increasing order. When is it possible to find infinitely many translates of which consists entirely of primes? The case is just Euclid’s theorem on the infinitude of primes, but the case is already open in general, with the case being the notorious twin prime conjecture.
On the other hand, there are some tuples for which one can easily answer the above question in the negative. For instance, the only translate of that consists entirely of primes is , basically because each translate of must contain an even number, and the only even prime is . More generally, if there is a prime such that meets each of the residue classes , then every translate of contains at least one multiple of ; since is the only multiple of that is prime, this shows that there are only finitely many translates of that consist entirely of primes.
To avoid this obstruction, let us call a -tuple admissible if it avoids at least one residue class for each prime . It is easy to check for admissibility in practice, since a -tuple is automatically admissible in every prime larger than , so one only needs to check a finite number of primes in order to decide on the admissibility of a given tuple. For instance, or are admissible, but is not (because it covers all the residue classes modulo ). We then have the famous Hardy-Littlewood prime tuples conjecture:
Conjecture 1 (Prime tuples conjecture, qualitative form) If is an admissible -tuple, then there exists infinitely many translates of that consist entirely of primes.
This conjecture is extremely difficult (containing the twin prime conjecture, for instance, as a special case), and in fact there is no explicitly known example of an admissible -tuple with for which we can verify this conjecture (although, thanks to the recent work of Zhang, we know that satisfies the conclusion of the prime tuples conjecture for some , even if we can’t yet say what the precise value of is).
Actually, Hardy and Littlewood conjectured a more precise version of Conjecture 1. Given an admissible -tuple , and for each prime , let denote the number of residue classes modulo that meets; thus we have for all by admissibility, and also for all . We then define the singular series associated to by the formula
where is the set of primes; by the previous discussion we see that the infinite product in converges to a finite non-zero number.
We will also need some asymptotic notation (in the spirit of “cheap nonstandard analysis“). We will need a parameter that one should think of going to infinity. Some mathematical objects (such as and ) will be independent of and referred to as fixed; but unless otherwise specified we allow all mathematical objects under consideration to depend on . If and are two such quantities, we say that if one has for some fixed , and if one has for some function of (and of any fixed parameters present) that goes to zero as (for each choice of fixed parameters).
Conjecture 2 (Prime tuples conjecture, quantitative form) Let be a fixed natural number, and let be a fixed admissible -tuple. Then the number of natural numbers such that consists entirely of primes is .
Thus, for instance, if Conjecture 2 holds, then the number of twin primes less than should equal , where is the twin prime constant
As this conjecture is stronger than Conjecture 1, it is of course open. However there are a number of partial results on this conjecture. For instance, this conjecture is known to be true if one introduces some additional averaging in ; see for instance this previous post. From the methods of sieve theory, one can obtain an upper bound of for the number of with all prime, where depends only on . Sieve theory can also give analogues of Conjecture 2 if the primes are replaced by a suitable notion of almost prime (or more precisely, by a weight function concentrated on almost primes).
Another type of partial result towards Conjectures 1, 2 come from the results of Goldston-Pintz-Yildirim, Motohashi-Pintz, and of Zhang. Following the notation of this recent paper of Pintz, for each , let denote the following assertion (DHL stands for “Dickson-Hardy-Littlewood”):
Conjecture 3 () Let be a fixed admissible -tuple. Then there are infinitely many translates of which contain at least two primes.
This conjecture gets harder as gets smaller. Note for instance that would imply all the cases of Conjecture 1, including the twin prime conjecture. More generally, if one knew for some , then one would immediately conclude that there are an infinite number of pairs of consecutive primes of separation at most , where is the minimal diameter amongst all admissible -tuples . Values of for small can be found at this link (with denoted in that page). For large , the best upper bounds on have been found by using admissible -tuples of the form
where denotes the prime and is a parameter to be optimised over (in practice it is an order of magnitude or two smaller than ); see this blog post for details. The upshot is that one can bound for large by a quantity slightly smaller than (and the large sieve inequality shows that this is sharp up to a factor of two, see e.g. this previous post for more discussion).
In a key breakthrough, Goldston, Pintz, and Yildirim were able to establish the following conditional result a few years ago:
Theorem 4 (Goldston-Pintz-Yildirim) Suppose that the Elliott-Halberstam conjecture is true for some . Then is true for some finite . In particular, this establishes an infinite number of pairs of consecutive primes of separation .
The dependence of constants between and given by the Goldston-Pintz-Yildirim argument is basically of the form . (UPDATE: as recently observed by Farkas, Pintz, and Revesz, this relationship can be improved to .)
Unfortunately, the Elliott-Halberstam conjecture (which we will state properly below) is only known for , an important result known as the Bombieri-Vinogradov theorem. If one uses the Bombieri-Vinogradov theorem instead of the Elliott-Halberstam conjecture, Goldston, Pintz, and Yildirim were still able to show the highly non-trivial result that there were infinitely many pairs of consecutive primes with (actually they showed more than this; see e.g. this survey of Soundararajan for details).
Actually, the full strength of the Elliott-Halberstam conjecture is not needed for these results. There is a technical specialisation of the Elliott-Halberstam conjecture which does not presently have a commonly accepted name; I will call it the Motohashi-Pintz-Zhang conjecture in this post, where is a parameter. We will define this conjecture more precisely later, but let us remark for now that is a consequence of .
We then have the following two theorems. Firstly, we have the following strengthening of Theorem 4:
Theorem 5 (Motohashi-Pintz-Zhang) Suppose that is true for some . Then is true for some .
A version of this result (with a slightly different formulation of ) appears in this paper of Motohashi and Pintz, and in the paper of Zhang, Theorem 5 is proven for the concrete values and . We will supply a self-contained proof of Theorem 5 below the fold, the constants upon those in Zhang’s paper (in particular, for , we can take as low as , with further improvements on the way). As with Theorem 4, we have an inverse quadratic relationship .
In his paper, Zhang obtained for the first time an unconditional advance on :
This is a deep result, building upon the work of Fouvry-Iwaniec, Friedlander-Iwaniec and Bombieri-Friedlander-Iwaniec which established results of a similar nature to but simpler in some key respects. We will not discuss this result further here, except to say that they rely on the (higher-dimensional case of the) Weil conjectures, which were famously proven by Deligne using methods from l-adic cohomology. Also, it was believed among at least some experts that the methods of Bombieri, Fouvry, Friedlander, and Iwaniec were not quite strong enough to obtain results of the form , making Theorem 6 a particularly impressive achievement.
Combining Theorem 6 with Theorem 5 we obtain for some finite ; Zhang obtains this for but as detailed below, this can be lowered to . This in turn gives infinitely many pairs of consecutive primes of separation at most . Zhang gives a simple argument that bounds by , giving his famous result that there are infinitely many pairs of primes of separation at most ; by being a bit more careful (as discussed in this post) one can lower the upper bound on to , and if one instead uses the newer value for one can instead use the bound . (Many thanks to Scott Morrison for these numerics.) UPDATE: These values are now obsolete; see this web page for the latest bounds.
In this post we would like to give a self-contained proof of both Theorem 4 and Theorem 5, which are both sieve-theoretic results that are mainly elementary in nature. (But, as stated earlier, we will not discuss the deepest new result in Zhang’s paper, namely Theorem 6.) Our presentation will deviate a little bit from the traditional sieve-theoretic approach in a few places. Firstly, there is a portion of the argument that is traditionally handled using contour integration and properties of the Riemann zeta function; we will present a “cheaper” approach (which Ben Green and I used in our papers, e.g. in this one) using Fourier analysis, with the only property used about the zeta function being the elementary fact that blows up like as one approaches from the right. To deal with the contribution of small primes (which is the source of the singular series ), it will be convenient to use the “-trick” (introduced in this paper of mine with Ben), passing to a single residue class mod (where is the product of all the small primes) to end up in a situation in which all small primes have been “turned off” which leads to better pseudorandomness properties (for instance, once one eliminates all multiples of small primes, almost all pairs of remaining numbers will be coprime).
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 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.
This is my final Milliman lecture, in which I talk about the sum-product phenomenon in arithmetic combinatorics, and some selected recent applications of this phenomenon to uniform distribution of exponentials, expander graphs, randomness extractors, and detecting (sieving) almost primes in group orbits, particularly as developed by Bourgain and his co-authors.
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[This post is authored by Emmanuel Kowalski.]
This post may be seen as complementary to the post “The parity problem in sieve theory“. In addition to a survey of another important sieve technique, it might be interesting as a discussion of some of the foundational issues which were discussed in the comments to that post.
Many readers will certainly have heard already of one form or another of the “large sieve inequality”. The name itself is misleading however, and what is meant by this may be something having very little, if anything, to do with sieves. What I will discuss are genuine sieve situations.
The framework I will describe is explained in the preprint arXiv:math.NT/0610021, and in a forthcoming Cambridge Tract. I started looking at this first to have a common setting for the usual large sieve and a “sieve for Frobenius” I had devised earlier to study some arithmetic properties of families of zeta functions over finite fields. Another version of such a sieve was described by Zywina (“The large sieve and Galois representations”, preprint), and his approach was quite helpful in suggesting more general settings than I had considered at first. The latest generalizations more or less took life naturally when looking at new applications, such as discrete groups.
Unfortunately (maybe), there will be quite a bit of notation involved; hopefully, the illustrations related to the classical case of sieving integers to obtain the primes (or other subsets of integers with special multiplicative features) will clarify the general case, and the “new” examples will motivate readers to find yet more interesting applications of sieves.
The parity problem is a notorious problem in sieve theory: this theory was invented in order to count prime patterns of various types (e.g. twin primes), but despite superb success in obtaining upper bounds on the number of such patterns, it has proven to be somewhat disappointing in obtaining lower bounds. [Sieves can also be used to study many other things than primes, of course, but we shall focus only on primes in this post.] Even the task of reproving Euclid’s theorem – that there are infinitely many primes – seems to be extremely difficult to do by sieve theoretic means, unless one of course injects into the theory an estimate at least as strong as Euclid’s theorem (e.g. the prime number theorem). The main obstruction is the parity problem: even assuming such strong hypotheses as the Elliott-Halberstam conjecture (a sort of “super-generalised Riemann Hypothesis” for sieves), sieve theory is largely (but not completely) unable to distinguish numbers with an odd number of prime factors from numbers with an even number of prime factors. This “parity barrier” has been broken for some select patterns of primes by injecting some powerful non-sieve theory methods into the subject, but remains a formidable obstacle in general.
I’ll discuss the parity problem in more detail later in this post, but I want to first discuss how sieves work [drawing in part on some excellent unpublished lecture notes of Iwaniec]; the basic ideas are elementary and conceptually simple, but there are many details and technicalities involved in actually executing these ideas, and which I will try to suppress for sake of exposition.
This week I am in Boston, giving this year’s Simons lectures at MIT together with David Donoho. (These lectures, incidentally, are endowed by Jim Simons, who was mentioned in some earlier discussion here.) While preparing these lectures, it occurred to me that I may as well post my lecture notes on this blog, since this medium is essentially just an asynchronous version of a traditional lecture series, and the hypertext capability is in some ways more convenient and informal than, say, slides.
I am giving three lectures, each expounding on some aspects of the theme “the dichotomy between structure and randomness”, which I also spoke about (and wrote about) for the ICM last August. This theme seems to pervade many of the areas of mathematics that I work in, and my lectures aim to explore how this theme manifests itself in several of these. In this, the first lecture, I describe the dichotomy as it appears in Fourier analysis and in number theory. (In the second, I discuss the dichotomy in ergodic theory and graph theory, while in the third, I discuss PDE.)
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