Equidistribution de sous-varietes speciales (Equisistribution of special subvarieties)

Mathematics – Algebraic Geometry

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Latex, French, 20. pages, no figure. to appear in Annals of Math

Scientific paper

A strongly special subvariety of a Shimura variety $S$ is (essentially) a subvariety associated to a semi-simple sub-Shimura datum. We prove that the set of probability measures canonically associated to to strongly special subvarieties is compact. More precisely: If $\mu_n$ is a sequence of such probability measures associated to strongly special subvarieties $Z_n$ of $S$ there exists a subsequence $\mu_{n_k}$ which converge to a measure $\mu_Z$ canonically associated to a strongly special subvariety $Z$ and for all $k>>0$ $Z_{n_k}$ is contained in $Z$. We give some application to the Andre-Oort conjecture: If $X$ is a subvariety of $S$ then there exists at most finitely many maximal (amongs subvarieties of $X$) strongly special subvarieties of $X$ as predicted by the Andre-Oort Conjecture. The proof uses Ratner's theory, some results of Mozes-Shah and Dani-Margulis.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Equidistribution de sous-varietes speciales (Equisistribution of special subvarieties) does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Equidistribution de sous-varietes speciales (Equisistribution of special subvarieties), we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Equidistribution de sous-varietes speciales (Equisistribution of special subvarieties) will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-601422

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.