Resolving galaxies in time and space

Abstract

Aims. Fossil record methods based on spectral synthesis techniques have matured during the past decade, and their application to integrated galaxy spectra has fostered substantial advances in the understanding of galaxies and their evolution. Yet, because of the lack of spatial resolution, these studies are limited to a global view, providing no information about the internal physics of galaxies. Methods. Motivated by the CALIFA survey, which is gathering integral field spectroscopy (IFS) over the full optical extent of 600 galaxies, we have developed an end-to-end pipeline that: (i) partitions the observed datacube into Voronoi zones in order to, when necessary and taking due account of correlated errors, increase the signal-to-noise ratio; (ii) extracts rest-framed spectra, including propagated errors and bad-pixel flags; (iii) feeds the spectra into the starlight spectral synthesis code; (iv) packs the results for all galaxy zones into a single FITS or HDF5 file; (v) performs a series of post-processing operations, including zone-topixel image reconstruction and unpacking the spectral and stellar population properties derived by starlight into multidimensional time, metallicity, and spatial coordinates. This paper provides an illustrated description of the whole pipeline and its many products. Using data for the nearby spiral NGC 2916 as a showcase, we go through each of the steps involved and present a series of ways of visualizing and analyzing this manifold. These include 2D maps of properties such as the velocity field, stellar extinction, mean ages and metallicities, mass surface densities, and star formation rates on different time scales and normalized in different ways, as well as 1D averages in the temporal and spatial dimensions, which lead to evolutionary curves and radial profiles of physical properties. Projections of the stellar light and mass growth onto radius-age diagrams are introduced as a means of visualizing galaxy evolution in time and space simultaneously, something which can also be achieved in 3D with snapshot cuts through the (x, y, t) cubes. Results. The results vividly illustrate the richness both of the combination of IFS data with spectral synthesis and of the insights on galaxy physics provided by the variety of diagnostics and semi-empirical constraints obtained. Additionally, they give a glimpse of what is to come from CALIFA and future IFS surveys.

The shape of oxygen abundance profiles explored with MUSE: evidence for widespread deviations from single gradients

“…FIT3D is now part of a more complete spectroscopic analysis pipeline named Pipe3D ), developed to characterise the properties of both the stellar populations and the ionised gas. In the modelling of the continuum emission, FIT3D uses an SSP template grid combining the GRANADA models from González Delgado et al (2005) for t < 63 Myr with those provided by the MILES project (Sánchez-Blázquez et al 2006;Vazdekis et al 2010;Falcón-Barroso et al 2011) for older ages (following Cid Fernandes et al 2013). This grid comprises a total of 156 individual populations covering 39 stellar ages between 0.001 and 14.1 Gyr and four metallicities between 0.004 and 0.03.…”

SDSS-IV MaNGA-resolved Star Formation and Molecular Gas Properties of Green Valley Galaxies: A First Look with ALMA and MaNGA

“…A stellar population fit of the coadded spectra within each spatial bin is then computed. The stellar population model for spaxels with continuum S/N > 3 is then estimated by rescaling the best fitted model within each spatial bin to the continuum flux intensity in the corresponding spaxel, following Cid Fernandes et al (2013) and Sánchez et al (2016a). The stellar mass surface density ( * S ) is then obtained using the stellar mass derived for each spaxel and then normalized to the physical area of one spaxel.…”

The CALIFA survey across the Hubble sequence

“…Our method to extract stellar population properties from datacubes has been explained and applied to CALIFA in Pérez et al (2013), Cid Fernandes et al (2013, and González Delgado et al (2014c,a). In short, we analyze the data with the  code (Cid Fernandes et al 2005), which fits an observed spectrum (O λ ) in terms of a model (M λ ) built by a nonparametric linear combination of N simple stellar populations (SSP) from a base spanning different ages (t) and metallicities (Z).…”

“…(9) of Cid Fernandes et al 2013), where x tZ is the fraction of flux at the normalization wavelength (5635 Å) attributed to the base element with age t and metallicity Z. The mass-weighted version of this index, log age M , is obtained by replacing x tZ by its corresponding mass fraction m tZ .…”