visualization, delta functions, interpretability

Late in the day, Rix, Ness, and I showed Ben Weiner (Arizona) the figures we have made for our paper on inferring red-giant masses and ages from APOGEE spectroscopy. He helped us think about changes we might make to the figures to bolster and make more clear the arguments.

I spent some of the day manipulating delta functions and mixtures of delta functions for my attempt to infer the star-formation history of the Milky Way. I learned (for the Nth time) that it is better to manipulate Gaussians than delta functions; delta functions are way too freaky! And, once again, thinking about things dimensionally (that is, in terms of units) is extremely valuable.

In the morning, Rix and I wrote to Andy Casey (Cambridge) regarding a proposal he made to use The Cannon and things we know about weak (that is, linearly responding) spectral lines to create a more interpretable or physically motivated version of our data-driven model, and maybe get detailed chemical abundances. Some of his ideas overlap what we are doing with Yuan-Sen Ting (Harvard). Unfortunately, there is no real way to benefit enormously from the flexibility of the data-driven model without also losing interpretability. The problem is that the training set can have arbitrary issues within it, and these become part of the model; if you can understand the training set so well that you can rule out these issues, then you don't need a data-driven model!

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