2021-10-25, 12:30–12:45, Grand Ballroom
RCSEDv2 (https://rcsed2.voxastro.org/), the second Reference Catalog of Spectral Energy Distributions of galaxies includes the largest homogeneously processed photometric dataset for 4 million galaxies assembled from several wide-field surveys. Rather than providing a collection of original measurements like NED or SIMBAD, we provide converted measurements in a form which allows one to compare data from different surveys directly. Here we describe the methodology of the photometric data homogenization. The original measurements come from different surveys: GALEX and the OM catalog of XMM-Newton (near-UV); SDSS, DESI Legacy Surveys, Dark Energy Survey, PanSTARRS, VST ATLAS, SkyMapper, KIDS (optical); UKIDSS, VHS, UHS, VIKING (near-IR); CatWISE and unWISE (near/mid-IR). They all have measurements in different photometric systems; (quasi-)integrated fluxes of extended sources are measured using various methods, e.g. Petrosian vs Kron vs asymptotic fluxes; aperture fluxes are measured in a set of specific apertures for each survey. Finally, galaxies span a range of redshifts from 0 to 1 and one has to apply k-corrections to be able to compare SEDs of sources at different redshifts. We first correct all photometric measurements for the foreground Galactic extinction, then convert them into the photometric system we adopted as a standard (GALEX + SDSS + UKIDSS + WISE). We worked out our own photometric system conversions by using a subset galaxies with photometric data available in several surveys. We computed aperture corrections into several pre-defined apertures by using published galaxy sizes / light profiles and image quality for each of the surveys. We also computed k-corrections using our own analytic approximations (the older version of this tool is available as standard functions within TOPCAT). Such a homogeneous photometric catalog allows us to build fully calibrated SEDs for the galaxies in our sample (defined by the availability of their spectra) and enables direct scientific analysis of this unique extragalactic dataset.
Big data: How to deal with the 5 Vs (volume, velocity, variety, veracity, value)