MegaMorph: classifying galaxy morphology using multi-wavelength S\'ersic profile fits
M. Vika, B. Vulcani, S.P. Bamford, B. H\"au{\ss}ler, A.L. Rojas

TL;DR
This paper demonstrates that the wavelength dependence of galaxy structural parameters, especially the Sersic index, can effectively classify galaxy types and improve sample purity, even at moderate redshifts.
Contribution
It introduces a novel method using multi-wavelength Sersic profile fits to classify galaxy morphology more accurately than traditional color and size proxies.
Findings
Wavelength dependence of n helps distinguish galaxy types.
N ratio recovers misclassified galaxies better than color-n cuts.
Method remains effective up to redshift z ~ 0.1.
Abstract
Aims. This work investigates the potential of using the wavelength-dependence of galaxy structural parameters (S\'ersic index, n, and effective radius, Re) to separate galaxies into distinct types. Methods. A sample of nearby galaxies with reliable visual morphologies is considered, for which we measure structural parameters by fitting multi-wavelength single-S\'ersic models. Additionally, we use a set of artificially redshifted galaxies to test how these classifiers behave when the signal-to-noise decreases. Results. We show that the wavelength-dependence of n may be employed to separate visually-classified early- and late-type galaxies, in a manner similar to the use of colour and n. Furthermore, we find that the wavelength variation of n can recover galaxies that are misclassified by these other morphological proxies. Roughly half of the spiral galaxies that contaminate an early-type…
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