SDSS-IV MaNGA: stellar population gradients as a function of galaxy environment

Abstract

We study the internal radial gradients of stellar population properties within 1.5 R e and analyse the impact of galaxy environment. We use a representative sample of 721 galaxies with masses ranging between 10 9 M to 10 11.5 M from the SDSS-IV survey MaNGA. We split this sample by morphology into early-type and late-type galaxies. Using the full spectral fitting code FIREFLY, we derive the light and mass-weighted stellar population properties age and metallicity, and calculate the gradients of these properties. We use three independent methods to quantify galaxy environment, namely the N th nearest neighbour, the tidal strength parameter Q and distinguish between central and satellite galaxies. In our analysis, we find that early-type galaxies generally exhibit shallow light-weighted age gradients in agreement with the literature and mass-weighted median age gradients tend to be slightly positive. Latetype galaxies, instead, have negative light-weighted age gradients. We detect negative metallicity gradients in both early and late-type galaxies that correlate with galaxy mass, with the gradients being steeper and the correlation with mass being stronger in late-types. We find, however, that stellar population gradients, for both morphological classifications, have no significant correlation with galaxy environment for all three characterisations of environment. Our results suggest that galaxy mass is the main driver of stellar population gradients in both early and late-type galaxies, and any environmental dependence, if present at all, must be very subtle.

Mild evolution of the stellar metallicity gradients of disc galaxies

“…Recent results on the stellar metallicity gradients from the MaNGA survey have been reported. Goddard et al (2017) find most stellar metallicity gradients to be negative in agreement with previous works and to show an anticorrelation with the stellar mass. Using the MaNGA survey, Zheng et al (2017) reported a correlation of the stellar metallicity gradients with stellar mass, albeit depending on galaxy morphology, in agreement with results from the CALIFA survey (Sánchez-Blázquez et al 2014;González Delgado et al 2015).…”

The 13th Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey Mapping Nearby Galaxies at Apache Point Observatory

“…Using different spectral fitting techniques and complementary environmental metrics, both Goddard et al (2017b) and Zheng et al (2017) conclude that any environmental signal in the average shape of gradients is weak at best, with no obvious trends emerging in the initial MaNGA data. Goddard et al (2017a) studied the internal gradients of the stellar population age and metallicity within 1.5 R e obtained from full spectral fitting and confirm several key results of previous surveys. Age gradients tend to be shallow for both early-type and late-type galaxies.…”

SDSS-IV MaNGA: Probing the Kinematic Morphology–Density Relation of Early-type Galaxies with MaNGA

“…Galaxy mass functions are a function of environment (e.g., Binggeli et al 1988). Once stellar mass is controlled, however, there are only subtle remaining differences as a function of environment for many internal galaxy properties, including morphology and color (e.g., Blanton & Moustakas 2009;Alpaslan et al 2015), star formation rates (Wijesinghe et al 2012), stellar populations (Thomas et al 2010), and gradients therein (e.g., Greene et al 2015;Goddard et al 2017). As the MaNGA survey progresses, the larger sample size will enable yet more sensitive searches for subtle trends between environment, stellar kinematics, gas content, and stellar populations.…”

“…The local overdensity measurement employed here ( n S ) is simply the number of galaxies (in our case, n = 5) with M 20.3 r > -mag, divided by the volume required to enclose that number of neighbors above the magnitude limit. We adopt the 5 S measurements from Goddard et al (2017; as defined by Etherington & Thomas 2015). n S is a complex measure of environment.…”