paper

RESOLVE Survey Photometry and Volume-limited Calibration of the Photometric Gas Fractions Technique

arXiv:1507.08669 · doi:10.1088/0004-637X/810/2/166

Abstract

We present custom-processed UV, optical, and near-IR photometry for the RESOLVE survey, a volume-limited census of stellar, gas, and dynamical mass within two subvolumes of the nearby universe (RESOLVE-A and -B), complete down to baryonic mass ~10^9.1-9.3 Msun. In contrast to standard pipeline photometry (e.g., SDSS), our photometry uses optimal background subtraction, avoids suppressing color gradients, and includes systematic errors. With these improvements, we measure brighter magnitudes, larger radii, bluer colors, and a real increase in scatter around the red sequence. Combining stellar masses from our photometry with the RESOLVE-A HI mass census, we create volume-limited calibrations of the photometric gas fractions (PGF) technique, which predicts gas-to-stellar mass ratios (G/S) from galaxy colors and optional additional parameters. We analyze G/S-color residuals vs. potential third parameters, finding that axial ratio is the best independent and physically meaningful third parameter. We define a "modified color" from planar fits to G/S as a function of both color and axial ratio. In the complete galaxy population, upper limits on G/S bias linear and planar fits. We therefore model the entire PGF probability density field, enabling iterative statistical modeling of upper limits and prediction of full G/S probability distributions for individual galaxies, with two-component structure for red colors. We use the RESOLVE-B 21cm census to test several PGF calibrations, finding that most systematically under- or overestimate gas masses, but the full probability density method performs well.

(29 pages, 15 figures, accepted for publication in ApJ; a data table is available at http://resolve.astro.unc.edu/data/resolve_phot_dr1.txt and a code for predicting individual galaxy G/S probability distributions (pred_loggs_dist.pro) is available at https://github.com/keckert7/codes

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