Open access
Date
2023-03-06Type
- Journal Article
ETH Bibliography
yes
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Abstract
In today's modern wide-field galaxy surveys, there is the necessity for parametric surface brightness decomposition codes characterised by accuracy, small degree of user intervention, and high degree of parallelisation. We try to address this necessity by introducing MORPHOFIT, a highly parallelisable python package for the estimate of galaxy structural parameters. The package makes use of wide-spread and reliable codes, namely, SEXTRACTOR and GALFIT. It has been optimised and tested in both low-density and crowded environments, where blending and diffuse light makes the structural parameters estimate particularly challenging. MORPHOFIT allows the user to fit multiple surface brightness components to each individual galaxy, among those currently implemented in the code. Using simulated images of single Sersic and bulge plus disk galaxy light profiles with different bulge-to-total luminosity (B/T) ratios, we show that MORPHOFIT is able to recover the input structural parameters of the simulated galaxies with good accuracy. We also compare its estimates against existing literature studies, finding consistency within the errors. We use the package in a companion paper to measure the structural parameters of cluster galaxies in order to study the wavelength dependence of the Kormendy relation of early-type galaxies. The package is available on github (1) and on the Pypi server (2) . Show more
Permanent link
https://doi.org/10.3929/ethz-b-000607027Publication status
publishedExternal links
Journal / series
Frontiers in Astronomy and Space SciencesVolume
Pages / Article No.
Publisher
Frontiers MediaSubject
galaxies: morphology; methods: data analysis; techniques: photometric; galaxies: photometry; galaxies: fundamental parameters; galaxies: clusters: individual: Abell S1063; galaxies: clusters: individual: MACS J0416.1-2403; galaxies: clusters: individual: MACS J1149.5+2223Funding
169130 - Cosmological Weak Lensing (SNF)
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ETH Bibliography
yes
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