Ten days ago, Fermat’s library posted a tweet saying that it is unknown whether the sum

converges or diverges, stirring up a lot of discussion. Sam Walters has been part of this discussion and pointed to a paper that says this is known as the Flint Hills series.

My first thought was to replace the sine term with a random variable and see what happens, because the values of *n* mod 2π act a lot like a random sequence. To be precise, the series is ergodic.

If *X* is a uniform random variable on the interval [0, 2π], then the random variable *Y =* 1/sin(*X*)² is fat tailed, so fat that it has no finite expected value. If *Y* had a finite expected value E[*Y*], then one might expect the Flint Hills sum to be roughly E[*Y*] ζ(3), i.e. the Flint Hills sum with the sine terms replaced by E[*Y*]. But since E[*Y*] diverges, this suggests that the Flint Hills series diverges.

Of course this doesn’t settle the question because the values of *n* mod 2π are not actually random. They simply act as if they were random *in some contexts*. For example, if you wanted to use them as if they were random values in order to do Monte Carlo integration, they would work just fine.

The question is whether the values act sufficiently like random values in the context of the Flint Hills problem. This is not clear, and is a problem in number theory rather than in probability. (Though number theory and probability are surprisingly interconnected.)

Sam Walters suggested considering a variation on the Flint Hills problem where we replace sin(*n*) with sin(2πθ*n*) for some constant θ, the original problem corresponding to θ = 1/2π. I suspect the series diverges for some (almost all?) values of θ. That is, unless you pick θ very carefully, number theory won’t rescue the series from divergence.