mixtures of Gaussians for astronomy

Phil Marshall and I spent the day pair-coding a tiny Python package that fits a set of mixture-of-Gaussian models of increasing complexity to a PanSTARRS-produced catalog cutout image. It is insanely fast! (We did this outside of Lang's Tractor for reasons that are too annoying to explain here.) Our success means that in principle, any survey that is doing any kind of galaxy fitting can also, very easily, fit general non-parameteric models to everything: That is, we could have a variable-complexity description of every imaging patch. I love this just because I am a geek. Marshall loves this because maybe—just maybe—the mixture-of-Gaussians description of a patch of imaging will be close to a compact sufficient statistic for performing other kinds of fits or analyses. He has weak and strong gravitational lensing in mind, of course. More on this soon, I very much hope!

[In other news, Brian Cox thinks I am guilty of scientific misconduct. Fortunately, Sarah Kendrew (MPIA) doesn't.]

open science, importance sampling

It is Open Access Week and for that reason, SUNY Albany libraries held an afternoon-long event. I learned a lot at the brown-bag discussion about how open access policies could dramatically improve the abilities of librarians to serve their constituents, and dramatically improve the ability of universities to generate and transmit knowledge. The horror stories about copyright, DRM, and unfair IP practices were, well, horrific. In the afternoon I gave a seminar about the openness of our group at NYU, including this blog, our web-exposed SVN repo, and our free data and code policies (obeyed where we are permitted to obey them; see above). It was great, and a great reminder that librarians are currently—in many universities—the most radical intellectuals, with sharp critiques of the conflicts and interactions between institutions of higher learning and institutions of commerce.

On the train home, I tried out importance sampling for my posterior PDF over catalogs project. Not a good idea! The prior is so very, very large.

matplotlib

I love the wonderful people who built and maintain the Python matplotlib plotting package. They are heroes of science. I spent the weekend fixing up our GALEX time-stream plots, and they are now far more useful and informative, with transparency and overlays and non-linear axes, all showing multiple kinds of information.

practice of science

In the morning, Lang and I pair-coded. In the afternoon, Jiang and I discussed the finer points of English grammar! This sounds like a joke, but of course writing is the most important tool in the scientist's toolkit, bar none.

Blandford symposium

I started writing something today for the upcoming symposium in honor of Roger Blandford (my PhD advisor). What I am working on is a bit off the rails; I am supposed to be talking about cosmology, but I might use the opportunity to talk about scientific reasoning, since that has always been one of Blandford's hobby interests.

subjectivity

In my IMPRS lecture today, I admitted in public that when you make a hard decision (that is, when you choose a model, or choose to include or not include a source in your catalog) you are by necessity doing something subjective. After all, Bayes returns only relative probabilities; making a decision on that basis departs from the objective process of inference. You can do better by making your decisions with the help of explicit utilities, but even these don't save you from subjectivity.