Stellar populations of massive early-type galaxies observed by MUSE

TL;DR

This study uses high-resolution MUSE data to analyze the stellar populations and initial mass function gradients in eight massive early-type galaxies, revealing non-universal IMFs and complex radial variations.

Contribution

It provides detailed measurements of stellar population parameters and IMF gradients in ETGs, highlighting non-universality and radial variations of the IMF.

Findings

IMF gradients are present in some galaxies, with bottom-heavy centers.

Metallicity and [Na/Fe] show negative gradients, while age and [Mg/Fe] are flat.

Discrepancies between stellar population M/L and dynamical M/L increase with NaI strength.

Abstract

Stellar population studies of massive early-type galaxies (ETGs) suggest that the stellar initial mass function may not be universal. In particular, the centres of ETGs seem to contain an excess of low-mass dwarf stars compared to our own Galaxy. Through high resolution MUSE IFU data, we carry out a detailed study of the stellar populations of eight massive ETGs. We use full spectrum fitting to determine ages, element abundances, and IMF slopes for spatially binned spectra. We measure flat gradients in age and [Mg/Fe] ratio, as well as negative gradients in metallicity and [Na/Fe]. We detect IMF gradients in some galaxies, with the centres hosting bottom-heavy IMFs and mass excess factors between 1.5-2.5 compared to a Kroupa IMF. The IMF slope below 0.5~M$_\odot$ varies for our galaxy sample between 1-2.8, with negative radial gradients, while the IMF slope between 0.5-1~M$_\odot$ has a steep value of $\sim$3 with mildly positive gradients for most galaxies. For M87, we find excellent agreement with the dynamical M/L as a function of radius. For the other galaxies, we find systematically higher M/L from stellar populations compared to orbit-based dynamical analysis of the same data. This discrepancy increases with NaI strength, suggesting a combination of calibration issues of this line and correlated uncertainties.