Resolved stellar mass maps of galaxies – I. Method and implications for global mass estimates

Abstract

We introduce a novel technique to construct spatially resolved maps of stellar mass surface density in galaxies based on optical and near‐infrared (NIR) imaging. We use optical/NIR colour(s) to infer effective stellar mass‐to‐light ratios (M/L) at each pixel, which are then multiplied by the surface brightness to obtain the local surface stellar mass density. We build look‐up tables to express M/L as a function of colour(s) by marginalizing over a Monte Carlo library of 50 000 stellar population synthesis (SPS) models by Charlot & Bruzual, which include a revised prescription for the thermally pulsing asymptotic giant branch (TP‐AGB) stellar evolutionary phase. Moreover, we incorporate a wide range of possible dust extinction parameters. In order to extract reliable flux and colour information at any position in the galaxy, we perform a median adaptive smoothing of the images that preserves the highest possible spatial resolution. As the most practical and robust, and hence fiducial method, we express the M/L in the H band as a function of (g−i) and (i−H). Stellar mass maps computed in this way have a typical accuracy of 30 per cent or less at any given pixel, determined from the scatter in the models. We compare maps obtained with our fiducial method with those derived using other combinations of bandpasses: (i) mass maps based on the M/L in NIR bands require one optical and one optical‐NIR colour to avoid significant biases as a function of the local physical properties of a galaxy; (ii) maps based on M/L in i band as a function of (g−i) only are generally in excellent agreement with our best optical‐NIR set, except for extremely star‐forming and dust extincted regions. We further compute stellar mass maps using a model library identical to the previous one except for being based on older SPS models, which assume shorter lived TP‐AGB stars. The M/L in the NIR inferred using these old models may be up to 2.5 times larger than the new ones, but this varies strongly as a function of colours and is maximal for the bluest colours. Finally, we compare total stellar mass estimates obtained by integrating resolved mass maps with those obtained with unresolved photometry. In galaxies with evident dust lanes, unresolved estimates may miss up to 40 per cent of the total stellar mass because dusty regions are strongly under‐represented in the luminous fluxes.

Galaxy Cluster Mass Reconstruction Project – II. Quantifying scatter and bias using contrasting mock catalogues

“…First, the Skibba & Sheth (2009) model is extended by allowing for a dependence of the colour distribution on halo mass at fixed luminosity Hearin & Watson 2013;Rodríguez-Puebla et al 2013), and we include colour gradients within haloes (Hansen et al 2009;van den Bosch et al 2008), which results in red galaxies having higher number density concentrations than blue galaxies in haloes of a given mass (as measured by Collister & Lahav 2005). We include stellar masses based on the Zibetti et al (2009) Wojtak & Mamon (2013) and account for the fact that galaxies and subhaloes are less concentrated than dark matter (e.g., Hansen et al 2005;Yang et al 2005b, Wojtak & Mamon 2013 by adopting concentration index c gal = cDM/1.5. Thirdly, the updated model includes a treatment of dynamically unrelaxed systems, including some non-central brightest halo galaxies, central galaxy velocity bias, and massive substructures, all of which depend on host halo mass (see Skibba & Macciò 2011).…”

The Stellar Mass of M31 as inferred by the Andromeda Optical & Infrared Disk Survey

“…contributes to the maintenance of a Python-language wrapper for FSPS: http://dan.iel.fm/python-fsps lower dust opacities and lower mass-to-light ratios. By comparison, we have also plotted mass-to-light ratios predicted by three colour-M/L * relations (Zibetti et al 2009;Taylor et al 2011;Into & Portinari 2013). These fits systematically vary by 0.3 dex, far larger than the 0.1 dex of internal systematic uncertainty typically claimed by g − i -M/L * fits Courteau et al (2014).…”

“…This approach is more rigorous than the colour-M/L * prescriptions (e.g. Zibetti et al 2009;Taylor et al 2011;Into & Portinari 2013) often employed by pixel-by-pixel stellar mass estimation studies that use only a g − i colour and marginalize over all likely star formation histories. By studying M31 in detail, an overall goal of ANDROIDS is to explore systematic uncertainties in studies of more distant and poorly resolved systems.…”

Sizes, colour gradients and resolved stellar mass distributions for the massive cluster galaxies in XMMUJ2235-2557 atz= 1.39

“…While this is a powerful way to derive resolved properties, deep and high-resolution multi-band imaging are required to well constrain the SED in each resolved region, which is not available for most datasets. The latter method, demonstrated by Zibetti, Charlot & Rix (2009) and Szomoru et al (2013), relies on a M * /L -colour relation to determine the spatial variation of M * /L. Although this method cannot disentangle the degeneracy between age, dust and metallicity, it provides a relatively inexpensive way to study the mass distribution of galaxies.…”