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Full spectrum fitting with photometry in <scp>ppxf</scp>: stellar population versus dynamical masses, non-parametric star formation history and metallicity for 3200 LEGA-C galaxies at redshift <i>z</i> ≈ 0.8

2023/08/31 by Michele Cappellari · 29 citations
Physics and Astronomy · #Galaxies: Formation, Evolution, Phenomena #Astronomy and Astrophysical Research #Stellar, planetary, and galactic studies

paper · pdf · doi:10.1093/mnras/stad2597

Abstract

ABSTRACT I introduce some improvements to the ppxf method, which measures the stellar and gas kinematics, star formation history (SFH) and chemical composition of galaxies. I describe the new optimization algorithm that ppxf uses and the changes I made to fit both spectra and photometry simultaneously. I apply the updated ppxf method to a sample of 3200 galaxies at redshift 0.6 &amp;lt; z &amp;lt; 1 (median z = 0.76, stellar mass M_∗ \gtrsim 3× 1010 M⊙), using spectroscopy from the LEGA-C survey (DR3) and 28-bands photometry from two different sources. I compare the masses from new JAM dynamical models with the ppxf stellar population M* and show the latter are more reliable than previous estimates. I use three different stellar population synthesis (SPS) models in ppxf and both photometric sources. I confirm the main trend of the galaxies’ global ages and metallicity [M/H] with stellar velocity dispersion σ* (or central density), but I also find that [M/H] depends on age at fixed σ*. The SFHs reveal a sharp transition from star formation to quenching for galaxies with \lg (σ _∗ /km s-1)\gtrsim 2.3 (σ _∗ \gtrsim 200km s-1), or average mass density within 1 kpc \lg (Σ 1\rm JAM/\mathrmM\odot kpc-2)\gtrsim 9.9 (Σ 1\rm JAM\gtrsim 7.9× 109 \mathrmM\odot kpc-2), or with [M/H]\gtrsim -0.1, or with Sersic index \lg n\rm Ser\gtrsim 0.5 (n\rm Ser\gtrsim 3.2). However, the transition is smoother as a function of M*. These results are consistent for two SPS models and both photometric sources, but they differ significantly from the third SPS model, which demonstrates the importance of comparing model assumptions.

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