Schubert varieties in Gaussian conditional independence

We study conditional independence of sets of coordinates in a multivariate Gaussian distribution, with an interest in the different conditional independence models that are possible. In one natural case, corresponding to certain memoryless processes that generalise Markov chains, a complete answer can be obtained using the tools of Schubert varieties and determinantal ideals. This is joint work with Jenna Rajchgot and Seth Sullivant.