another data-driven model of stars

My people are tired of hearing endlessly about data-driven models of stars. But today Boris Leistedt (NYU) created a new one, and I am extremely excited about it.

The idea—which is more-or-less my unattempted Gaia Sprint idea—is to build a very flexible model in color–magnitude space, and then generate noisy parallaxes. That is, a hierarchical model for the parallaxes, with a color–magnitude diagram that is learned simultaneously. Today, Leistedt had the breakthrough that this could be done in bins in color and magnitude, with a Dirichlet model. That is out-of-the-box inference; he got it working and it looks nice! This is all on the path to removing physical models from (what you might call) the Gaia distance ladder (which starts at parallaxes, and ends with some kind of distance estimate for everything that can be detected).

(The first sentence of the second paragraph of this post uses all three kinds of dashes: em, en, and hyphen. Bring it on, typography nerds!)

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