LCOGT

I spent the day at LCOGT today, hosted by Diana Dragomir. While she was giving me a tour of the facilities, I met the founder and president, Wayne Rosing, who was in the shops working on the 1-m telescopes. The director, Todd Boroson, explained to me the idea behind LCOGT: It operates not as a set of independent observatories, but as a single telescope that happens to be a network of apertures (and capabilities). That's interesting; and it permits the telescope to make continuous measurements in a way that few other telescopes can. Most of the science is in the time domain. After this I had many great conversations. Some highlights follow.

One of the big issues for LCOGT is scheduling. I had a great conversation about this with Eric Saunders, who said various things that were music to my ears: One is that they have tried to specify the scheduling problem as an integer programming problem. This separates the objectives from the method or algorithm used to optimize it. The other musical thing he said is that they optimize using industrial-grade operations research packages. They are so much better than anything you could write by hand.

With Dragomir I discussed exoplanet atmospheres, and her evidence for Rayleigh scattering in a planet they are writing up now. She is struggling with inconsistencies in the data, which come from different telescopes working at different wavelengths: Are they real or, if not, how to model or remove them?

Late in the day, Andy Howell, Iair Arcavi, and Curtis McCully showed me the Supernova Exchange, which is a project they are working on to coordinate supernova follow-up. They are following up so many supernova of so many types, with so many collaborating projects, that they can't keep track without some sophisticated software. This has to be flexible enough to encode the planned and completed observations and their status, and also comments and discussion, and also tags that represent the reasons behind the follow-up. This latter point is something I have always been interested in: For many statistical questions, you need to know why something was observed.