Galaxy And Mass Assembly: accurate panchromatic photometry from optical priors using lambdar

Abstract

We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (lambdar), a novel code for calculating matched aperture photometry across images that are neither pixel-nor PSF-matched, using prior aperture definitions derived from high resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalisation, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric dataset from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR;Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from lambdar with that presented in Driver et al. (2016), finding broad agreement between the datasets. Nonetheless, we demonstrate that the photometry from lambdar is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the lambdar dataset. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using lambdar photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour-colour parameter-space able to be explored.

Measurements of Extragalactic Background Light From the Far Uv to the Far Ir From Deep Ground- And Space-Based Galaxy Counts

“…The SEXTRACTOR-defined apertures are convolved with the appropriate point-spread function for each facility and used to derive consistent flux measurements in all other bands. Care is taken to manage overlapping objects and flux-share appropriately (see Wright et al 2016 for full details). As part of the quality control process, all bright and all oversized apertures (for their magnitude) were visually inspected and corrected if necessary.…”

“…The very simple strategy we adopt here is to identify the point at which the counts in the GAMA Wright catalog diverge from the deeper data sets and truncate our counts 0.5 mag brightward of this limit. See Wright et al (2016) for full details of the GAMA analysis, including aperture verification.…”

Galaxy and Mass Assembly (GAMA): Exploring the WISE Web in G12

“…These cases will have systematically underestimated profile-fit (WPRO) fluxes. For extragalactic work, in which the target galaxies are local-for example using a sample such as SDSS/GAMA-it is therefore better to use the ALLWISE Standard Aperture photometry or use your own circular aperture measurements that are appropriate to the size scales under consideration; more details can be found in M. Cluver et al (2017, in preparation) and Wright et al (2016).…”

“…This problem is not wide spread, however, as only 1.2% WISE sources have more than one GAMA cross match within a 5″ radius, which is referred to as a "catastrophic blend" in Paper I and does not adversely affect the GAMA-WISE statistics or analysis. A more detailed discussion of the GAMA-WISE blending is found in Paper I, but see also Wright et al (2016) for a multiwavelength deblending analysis of all GAMA photometry.…”

Galaxy And Mass Assembly (GAMA): blue spheroids within 87 Mpc

“…We use the matched-aperture photometry measured across 21 wavebands for GAMA galaxies using the Lambda Adaptive MultiBand Deblending Algorithm in R (LAMBDAR; Wright et al 2016). Specifically, we use LambdarSDSSgv01, LambdarSDSSrv01 and LambdarInputCatUVOptNIRv01 catalogues from the LAMBDAR data management unit (DMU).…”