In:
Astronomy & Astrophysics, EDP Sciences, Vol. 664 ( 2022-8), p. A92-
Kurzfassung:
Aims. We present the capabilities of G alapagos -2 and G alfitm in the context of fitting two-component profiles – bulge–disk decompositions – to galaxies, with the ultimate goal of providing complete multi-band, multi-component fitting of large samples of galaxies in future surveys. We also release both the code and the fit results to 234 239 objects from the DR3 of the GAMA survey, a sample significantly deeper than in previous works. Methods. We use stringent tests on both simulated and real data, as well as comparison to public catalogues to evaluate the advantages of using multi-band over single-band data. Results. We show that multi-band fitting using G alfitm provides significant advantages when trying to decompose galaxies into their individual constituents, as more data are being used, by effectively being able to use the colour information buried in the individual exposures to its advantage. Using simulated data, we find that multi-band fitting significantly reduces deviations from the real parameter values, allows component sizes and Sérsic indices to be recovered more accurately, and – by design – constrains the band-to-band variations of these parameters to more physical values. On both simulated and real data, we confirm that the spectral energy distributions (SEDs) of the two main components can be recovered to fainter magnitudes compared to using single-band fitting, which tends to recover ‘disks’ and ‘bulges’ with – on average – identical SEDs when the galaxies become too faint, instead of the different SEDs they truly have. By comparing our results to those provided by other fitting codes, we confirm that they agree in general, but measurement errors can be significantly reduced by using the multi-band tools developed by the MEGAMORPH project. Conclusions. We conclude that the multi-band fitting employed by G alapagos -2 and G alfitm significantly improves the accuracy of structural galaxy parameters and enables much larger samples to be be used in a scientific analysis.
Materialart:
Online-Ressource
ISSN:
0004-6361
,
1432-0746
DOI:
10.1051/0004-6361/202142935
Sprache:
Englisch
Verlag:
EDP Sciences
Publikationsdatum:
2022
ZDB Id:
1458466-9
SSG:
16,12
