Lambda Adaptive Multi-Band Deblending Algorithm in R
Data Release coming soon
The LDR is a public release of consistent 21-band photometry, for 221,369 sources in the GAMA Equatorial fields, measured using the LAMBDAR program. LDR photometry is currently being processed through GAMA's internal QC, and will become available in the coming weeks.
Accepted for Publication in MNRAS. Pre-print available on ArXiv.
Documentation in progress
View the current version here.
LAMBDAR (Lambda Adaptive Multi-Band Deblending Algorithm in R) is a procedure for measuring the fluxes of galaxies in an arbitrary FITS image, covering an arbitrary photometric wave-band, when provided all parameters needed to construct galactic apertures at the required locations. The motivation for the creation of this program is the determination of multi-band matched aperture galactic photometry. Through sophisticated matched aperture photometry, it is possible to develop robust Spectral Energy Distributions (SEDs) and accurately establish the physical properties of galactic objects. This code is based primarily on a program written by Dr Nathan Bourne, which was designed for determining galactic fluxes in low resolution Herschel images. The code has been developed primarily by the Author, and in close collaboration with Dr Aaron Robotham. The Author welcomes any comments/criticisms/suggestions and encourages users to pass on any of the above through the repository page on GitHub or directly via .
The panchromatic SEDs of GAMA object G574689. The grey SED is as determined when using photometry from the PDR catalogue, while the coloured lines show the SED fit to photometry returned by lambdar. Note that after our procedure, the aperture used for all bands is consistent (shown in the inset image) and the photometry is therefore also consistent. Here the LDR photometry is in black, model photometry is in green, unobscured SED is in blue, and the obscured SED is in red. The inset is an RGB cutout using the viking H - sdss i - sdss g bands. Taken from Wright et. al. (2016).