cheap and dirty chemical abundances

It was a packed research day, with great conversations about data analysis and inference with Rix, Dalcanton, Fouesneau, Price-Whelan, Schölkopf, and others. I have so many things to do this summer!

The highlight conversation of the day was with Rix and Melissa Ness (MPIA) about the possibility that we might be able to build data-driven metallicity indicators or indices for APOGEE spectra by performing regressions of the data against known metallicities and other meta-data (confounders, if you will). We came up with a baseline plan and talked through the iterated linear algebra the project requires. The baseline project has strong overlap with things we worked on with Conroy & Choi this Spring. The idea is to have the (noisily) labeled data decide what operators on the data are the best predictors or estimators of chemical abundances by building an empirical predictive model of the labels.

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