Shende and Tsimerman on equidistribution in Bun_2(P^1)

Very nice paper just posted by Vivek Shende and Jacob Tsimerman.  Take a sequence {C_i} of hyperelliptic curves of larger and larger genus.  Then for each i, you can look at the pushforward of a random line bundle drawn uniformly from Pic(C) / [pullbacks from P^1] to P^1, which is a rank-2 vector bundle.  This gives you a measure \mu_i on Bun_2(P^1), the space of rank-2 vector bundles, and Shende and Tsimerman prove, just as you might hope, that this sequence of measures converges to the natural measure.

I think (but I didn’t think this through carefully) that this corresponds to saying that if you look at a sequence of quadratic imaginary fields with increasing discriminant, and for each field you write down all the ideal classes, thought of as unimodular lattices in R^2 up to homothety, then the corresponding sequence of (finitely supported) measures on the space of lattices converges to the natural one.

Equidistribution comes down to counting, and the method here is to express the relevant counting problem as a problem of counting points on a variety (in this case a Brill-Noether locus inside Pic(C_i)), which by Grothendieck-Lefschetz you can do if you can control the cohomology (with its Frobenius action.)  The high-degree part of the cohomology they can describe explicitly, and fortunately they are able to exert enough control over the low-degree Betti numbers to show that the contribution of this stuff is negligible.

In my experience, it’s often the case that showing that the contribution of the low-degree stuff, which “should be small” but which you don’t actually have a handle on, is often the bottleneck!  And indeed, for the second problem they discuss (where you have a sequence of hyperelliptic curves and a single line bundle on each one) it is exactly this point that stops them, for the moment, from having the theorem they want.

Error terms are annoying.  (At least when you can’t prove they’re smaller than the main term.)

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