Data Associated with Chemical Cartography with APOGEE: Two-process Parameters and Residual Abundances for 288,789 Stars from Data Release 17

Stellar abundance measurements are subject to systematic errors that induce extra scatter and artificial correlations in elemental abundance patterns.  We derive empirical calibration offsets to remove systematic trends with surface gravity log(g) in 17 elemental abundances of 288,789 evolved stars from the SDSS APOGEE survey.  We fit these corrected abundances as the sum of a prompt process tracing core-collapse supernovae and a delayed process tracing Type Ia supernovae, thus recasting each star's measurements into the amplitudes A_cc and A_Ia and the element-by-element residuals from this two-parameter fit. Here we present the log(g)-calibrated abundances, fit parameters, process amplitudes, and element-by-element abundance residuals of 288,789 stars (310,427 spectra) in APOGEE DR17 that accompany the paper.

calibration_values_final.dat contains all derived calibration offsets, including the grids of log(g) calibration offsets and zero-point offsets for two-process model analysis. The first five rows of this catalog are reproduced in Table 2 of the paper.

logg_calib_example.ipynb is a Jupyter notebook containing Python code to load calibration_values_final.dat, extract the log(g) calibration offsets for specific element, and apply calibration offsets to 10 sample stars.

2process_residual_abund_catalog_final.fits is the catalog of 310,427 APOGEE DR17 spectra (288,789 unique stars) containing calibrated abundances, two-process fit parameters, and abundance residuals. A full listing of columns in this catalog is given in Table 5 of the paper.

catalog_examples.ipynb is a Jupyter notebook containing Python code to load 2process_residual_abund_catalog_final.fits, cross match with other catalogs (using AstroNN and the APOGEE DR17 Globular Cluster Value-Added Catalog as examples), and make some example plots utilizing the cross-matched data.