Astronomy and Astrophysics – Astrophysics – Cosmology and Extragalactic Astrophysics
Scientific paper
2009-04-27
Mon.Not.Roy.Astron.Soc.400:1181-1198,2009
Astronomy and Astrophysics
Astrophysics
Cosmology and Extragalactic Astrophysics
Accepted for publication on MNRAS on Aug 10th 2009. 21 pages, 14 figures (see http://www.mpia.de/homes/zibetti/mass_maps_I.pdf
Scientific paper
10.1111/j.1365-2966.2009.15528.x
(Abridged) We introduce a novel technique to construct spatially resolved maps of stellar mass surface density in galaxies based on optical and near IR 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 stellar surface 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 (2007), which include a revised prescription for the TP-AGB stellar evolutionary phase, with a wide range of dust exinctions. 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 and the old BC03 TP-AGB prescription. 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.
Charlot Stephane
Rix Hans-Walter
Zibetti Stefano
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