Comparing six evolutionary population synthesis models through spectral synthesis on galaxies

TL;DR

This study compares six popular evolutionary population synthesis models by fitting galaxy spectra from SDSS, revealing significant differences in derived stellar populations and emphasizing the importance of model consistency for reliable results.

Contribution

It provides a comprehensive comparison of six EPS models on galaxy spectral fitting, highlighting the variability in results and the need for consistent model use.

Findings

Different EPS models yield significantly different light fractions.

Stellar population synthesis depends on age and metallicity, not much on stellar evolution tracks.

Young populations are more prominent in star-forming and composite galaxies.

Abstract

We compare six popularly used evolutionary population synthesis (EPS) models (BC03, CB07, Ma05, GALEV, GRASIL, Vazdekis/Miles) through fitting the full optical spectra of six representative types of galaxies (star-forming and composite galaxies, Seyfert 2s, LINERs, E+A and early-type galaxies), which are taken from the Sloan Digital Sky Survey (SDSS). Throughout our paper, we use the simple stellar populations (SSPs) from each EPS model and the software STARLIGHT to do our fits. Our main results are: Using different EPS models the resulted numerical values of contributed light fractions change obviously, even though the dominant populations are consistent. The stellar population synthesis does depend on the selection of age and metallicity, while it does not depend on the stellar evolution track much. The importance of young populations decreases from star-forming, composite, Seyfert 2, LINER to early-type galaxies, and E+A galaxies lie between composite galaxies and Seyfert 2s in most cases. We conclude that different EPS models do derive different stellar populations, so that it is not reasonable to directly compare stellar populations estimated from different EPS models. To get reliable results, we should use the same EPS model for the compared samples.