[Paper Review] Resolving galaxies in time and space: I: Applying STARLIGHT to CALIFA data cubes

R. Cid Fernandes, E. Pérez+9 more|arXiv (Cornell University)|Apr 21, 2013

Galaxies: Formation, Evolution, PhenomenaPhysics and Astronomy38 references104 citations

TL;DR

This paper presents an end-to-end pipeline for applying the STARLIGHT spectral synthesis code to spatially resolved Integral Field Spectroscopy (IFS) data from the CALIFA survey, enabling full 3D mapping of stellar population properties (age, metallicity, mass, star formation history) across galaxies. Using NGC 2916 as a case study, it demonstrates how Voronoi binning, rest-frame spectral extraction, and multi-dimensional FITS/HDF5 organization yield detailed radial and temporal profiles, revealing inside-out growth and spatially varying star formation histories.

ABSTRACT

Fossil record methods based on spectral synthesis techniques have matured over the past decade, and their application to integrated galaxy spectra fostered substantial advances on 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. Motivated by the CALIFA survey, which is gathering Integral Field Spectroscopy over the full optical extent of 600 galaxies, we have developed an end-to-end pipeline which: (i) partitions the observed data cube into Voronoi zones in order to, when necessary and taking due account of correlated errors, increase the S/N, (ii) extracts 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 file, (v) performs a series of post-processing operations, including zone-to-pixel image reconstruction and unpacking the spectral and stellar population properties into multi-dimensional time, metallicity, and spatial coordinates. This paper provides an illustrated description of this whole pipeline and its products. Using data for the nearby spiral NGC 2916 as a show case, we go through each of the steps involved, presenting ways of visualizing and analyzing this manifold. These include 2D maps of properties such as the v-field, stellar extinction, mean ages and metallicities, mass surface densities, star formation rates on different time scales and normalized in different ways, 1D averages in the temporal and spatial dimensions, projections of the stellar light and mass growth (x,y,t) cubes onto radius-age diagrams, etc. The results illustrate the richness of the combination of IFS data with spectral synthesis, providing a glimpse of what is to come from CALIFA and future surveys. (Abridged)

Motivation & Objective

• To develop a systematic, automated pipeline for applying spectral synthesis (STARLIGHT) to spatially resolved IFS data cubes from the CALIFA survey.
• To enable the recovery of multi-dimensional stellar population properties—age, metallicity, mass, and star formation rate—across spatial and temporal dimensions.
• To address technical challenges in IFS data reduction, including signal-to-noise enhancement via Voronoi binning and correction for correlated errors in spatially binned spectra.
• To produce a standardized, accessible data format (FITS/HDF5) integrating spectral and stellar population products for future analysis.
• To demonstrate the method’s utility through a detailed case study on the spiral galaxy NGC 2916, revealing spatially resolved evolutionary trends.

Proposed method

• Pre-processing involves constructing spatial masks, correcting flag and error spectra, rest-framing and resampling the data cubes, and applying Voronoi tesselation to spatially bin spaxels to achieve a minimum signal-to-noise ratio of 20.
• The pipeline uses the qbick Python package to automate pre-processing, including error propagation and handling of bad pixels, with an empirical correction for correlated errors in spatially binned spectra.
• STARLIGHT is applied to each spatial bin using a base of stellar population synthesis models (MILES and Granada) spanning 1 Myr to 14 Gyr in age and 0.2–1.5 solar metallicities.
• Results are packed into a hierarchical FITS or HDF5 file using the pyCASSO software, enabling efficient storage and retrieval of multi-dimensional stellar population parameters.
• Post-processing includes zone-to-pixel image reconstruction, 2D mapping of physical quantities (e.g., extinction, mass surface density, mean age, metallicity), and 1D radial and temporal profiles.
• Advanced visualization tools such as radius-age diagrams and 3D snapshot cuts through the (x,y,t) cube are introduced to visualize galaxy evolution in time and space simultaneously.

Experimental results

Research questions

• RQ1 How can spectral synthesis methods be systematically applied to spatially resolved IFS data cubes to recover the full 3D history of stellar populations?
• RQ2 What are the spatial and temporal gradients in stellar age, metallicity, and star formation rate across a typical spiral galaxy like NGC 2916?
• RQ3 How does the inside-out growth scenario of galaxies manifest in spatially resolved star formation histories derived from IFS data?
• RQ4 What are the effects of correlated errors in spatial binning, and how can they be corrected to preserve statistical reliability?
• RQ5 How can multi-dimensional stellar population products be efficiently organized, visualized, and analyzed in a standardized format?

Key findings

• The pipeline successfully recovers spatially resolved stellar population properties across the full optical extent of NGC 2916, with high fidelity in regions of high signal-to-noise (R < 1 HLR) and robust binning in lower signal regions.
• The analysis reveals negative age and metallicity gradients, with older and more metal-rich stars concentrated in the inner regions, consistent with inside-out growth.
• Mass surface density and star formation rate profiles show higher growth efficiency in the inner regions, peaking at intermediate stellar masses (~7×10¹¹ M☉), supporting a mass-dependent growth efficiency.
• The use of time-averaged star formation rates and b-parameter diagnostics in IFS reveals spatially varying star formation histories, with distinct patterns in different radial zones.
• Radius-age diagrams and 3D snapshot cuts effectively visualize the co-evolution of spatial and temporal stellar population properties, enabling direct comparison of 'present here' and 'present elsewhere' stellar populations.
• The pyCASSO framework enables efficient organization and analysis of multi-dimensional stellar population data, paving the way for systematic studies of the CALIFA sample and future IFS surveys.