# The polymath blog

## August 9, 2009

### (Research thread II) Deterministic way to find primes

Filed under: finding primes,research — Terence Tao @ 3:57 am
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This thread marks the formal launch of “Finding primes” as the massively collaborative research project Polymath4, and now supersedes the proposal thread for this project as the official “research” thread for this project, which has now become rather lengthy. (Simultaneously with this research thread, we also have the discussion thread to oversee the research thread and to provide a forum for casual participants, and also the wiki page to store all the settled knowledge and accumulated insights gained from the project to date.) See also this list of general polymath rules.

The basic problem we are studying here can be stated in a number of equivalent forms:

Problem 1. (Finding primes) Find a deterministic algorithm which, when given an integer k, is guaranteed to locate a prime of at least k digits in length in as quick a time as possible (ideally, in time polynomial in k, i.e. after $O(k^{O(1)})$ steps).

Problem 2. (Finding primes, alternate version) Find a deterministic algorithm which, after running for k steps, is guaranteed to locate as large a prime as possible (ideally, with a polynomial number of digits, i.e. at least $k^c$ digits for some $c>0$.)

To make the problem easier, we will assume the existence of a primality oracle, which can test whether any given number is prime in O(1) time, as well as a factoring oracle, which will provide all the factors of a given number in O(1) time. (Note that the latter supersedes the former.) The primality oracle can be provided essentially for free, due to polynomial-time deterministic primality algorithms such as the AKS primality test; the factoring oracle is somewhat more expensive (there are deterministic factoring algorithms, such as the quadratic sieve, which are suspected to be subexponential in running time, but no polynomial-time algorithm is known), but seems to simplify the problem substantially.

The problem comes in at least three forms: a strong form, a weak form, and a very weak form.

1. Strong form: Deterministically find a prime of at least k digits in poly(k) time.
2. Weak form: Deterministically find a prime of at least k digits in $\exp(o(k))$ time, or equivalently find a prime larger than $k^C$ in time O(k) for any fixed constant C.
3. Very weak form: Deterministically find a prime of at least k digits in significantly less than $(10^k)^{1/2}$ time, or equivalently find a prime significantly larger than $k^2$ in time O(k).

The pr0blem in all of these forms remain open, even assuming a factoring oracle and strong number-theoretic hypotheses such as GRH. One of the main difficulties is that we are seeking a deterministic guarantee that the algorithm works in all cases, which is very different from a heuristic argument that the algorithm “should” work in “most” cases. (Note that there are already several efficient probabilistic or heuristic prime generation algorithms in the literature, e.g. this one, which already suffice for all practical purposes; the question here is purely theoretical.) In other words, rather than working in some sort of “average-case” environment where probabilistic heuristics are expected to be valid, one should instead imagine a “Murphy’s law” or “worst-case” scenario in which the primes are situated in a “maximally unfriendly” manner. The trick is to ensure that the algorithm remains efficient and successful even in the worst-case scenario.

Below the fold, we will give some partial results, and some promising avenues of attack to explore. Anyone is welcome to comment on these strategies, and to propose new ones. (If you want to participate in a more “casual” manner, you can ask questions on the discussion thread for this project.)

Also, if anything from the previous thread that you feel is relevant has been missed in the text below, please feel free to recall it in the comments to this thread.

## July 27, 2009

### Proposal: deterministic way to find primes

Filed under: finding primes,polymath proposals,research — Terence Tao @ 2:24 am

Here is a proposal for a polymath project:

Problem. Find a deterministic algorithm which, when given an integer k, is guaranteed to find a prime of at least k digits in length of time polynomial in k.  You may assume as many standard conjectures in number theory (e.g. the generalised Riemann hypothesis) as necessary, but avoid powerful conjectures in complexity theory (e.g. P=BPP) if possible.

The point here is that we have no explicit formulae which (even at a conjectural level) can quickly generate large prime numbers.  On the other hand, given any specific large number n, we can test it for primality in a deterministic manner in a time polynomial in the number of digits (by the AKS primality test).  This leads to a probabilistic algorithm to quickly find k-digit primes: simply select k-digit numbers at random, and test each one in turn for primality.  From the prime number theorem, one is highly likely to eventually hit on a prime after about O(k) guesses, leading to a polynomial time algorithm.  However, there appears to be no obvious way to derandomise this algorithm.

Now, given a sufficiently strong pseudo-random number generator – one which was computationally indistinguishable from a genuinely random number generator – one could derandomise this algorithm (or indeed, any algorithm) by substituting the random number generator with the pseudo-random one.  So, given sufficiently strong conjectures in complexity theory (I don’t think P=BPP is quite sufficient, but there are stronger hypotheses than this which would work), one could solve the problem.

Cramer conjectured that the largest gap between primes in [N,2N] is of size $O( \log^2 N )$.  Assuming this conjecture, then the claim is easy: start at, say, $10^k$, and increment by 1 until one finds a prime, which will happen after $O(k^2)$ steps.  But the only real justification for Cramer’s conjecture is that the primes behave “randomly”.  Could there be another route to solving this problem which uses a more central conjecture in number theory, such as GRH? (Note that GRH only seems to give an upper bound of $O(\sqrt{N})$ or so on the largest prime gap.)

My guess is that it will be very unlikely that a polymath will be able to solve this problem unconditionally, but it might be reasonable to hope that it could map out a plausible strategy which would need to rely on a number of not too unreasonable or artificial number-theoretic claims (and perhaps some mild complexity-theory claims as well).

Note: this is only a proposal for a polymath, and is not yet a fully fledged polymath project.  Thus, comments should be focused on such issues as the feasibility of the problem and its suitability for the next polymath experiment, rather than actually trying to solve the problem right now. [Update, Jul 28: It looks like this caution has become obsolete; the project is now moving forward, though it is not yet designated an official polymath project.  However, because we have not yet fully assembled all the components and participants of the project, it is premature to start flooding this thread with a huge number of ideas and comments yet.  If you have an immediate and solidly grounded thought which would be of clear interest to other participants, you are welcome to share it here; but please refrain from working too hard on the problem or filling this thread with overly speculative or diverting posts for now, until we have gotten the rest of the project in place.]

See also the discussion thread for this proposal, which will also contain some expository summaries of the comments below, as well as the wiki page for this proposal, which will summarise partial results, relevant terminology and literature, and other resources of interest.

## July 26, 2009

Filed under: mock-up,research — Terence Tao @ 7:27 pm

This is a mock-up of what a research thread for a polymath project would look like.  The thread would begin with a statement of the research problem, e.g.

Problem (Boundedness of the trilinear Hilbert transform). Show that the trilinear Hilbert transform $T(f,g,h) := p.v. \int_{-\infty}^\infty f(x+t) g(x+2t) h(x+3t) \frac{dt}{t}$ is bounded from $L^{p_1}({\Bbb R}) \times \ldots \times L^{p_3}({\Bbb R}) \to L^p({\Bbb R)}$ for some $p_1,p_2,p_3,p$ (e.g. $p_1=p_2=p_3=4$ and $p_4 = 4/3$).

Some discussion of the precise objective (are we aiming for an actual proof, or would we be happy with understanding why the problem is difficult?) would go here.  [Note: while the above problem is an important open problem in harmonic analysis, I am not actually proposing to solve it by polymath here; it is only being used as an example for the purposes of this mock-up.]

A brief discussion of prior results would also be appropriate here, though an extended bibliography might be better placed on the wiki.

A reminder of the polymath rules might also be placed here, together with a link to the discussion thread for issues relating to exposition, strategy, and other meta-comments.  The initiator of the project should also put some effort into laying down preliminary thoughts of the project as clearly as possible.

All threads in a polymath project would have a dedicated category; in this case, the category is mock-up.

Finally, one should put a list of moderators of the project, who would be able to respond to technical issues, such as fixing up a mangled comment.  For this mock-up project, the moderators are:

• Terence Tao (tao@math.ucla.edu)
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