Recovering galaxy star formation and metallicity histories from spectra using VESPA

By R. Tojeiro, Alan Heavens, Raul Jimenez, B. Panter. 2007

190 citations recorded by the source corpus.

We introduce versatile spectral analysis (VESPA): a new method which aims to recover robust star formation and metallicity histories from galactic spectra. VESPA uses the full spectral range to construct a galaxy history from synthetic models. We investigate the use of an adaptative parametrization grid to recover reliable star formation histories on a galaxy-by-galaxy basis. Our goal is robustness as opposed to high-resolution histories, and the method is designed to return high time resolution only where the data demand it. In this paper we detail the method and we present our findings when we apply VESPA to synthetic and real Sloan Digital Sky Survey (SDSS) spectroscopic data. We show that the number of parameters that can be recovered from a spectrum depends strongly on the signal-to-noise ratio, wavelength coverage and presence or absence of a young population. For a typical SDSS sample of galaxies, we can normally recover between two and five stellar populations. We find very good agreement between VESPA and our previous analysis of the SDSS sample with MOPED.

Subfields: Astronomy and Astrophysics, Computer Vision and Pattern Recognition, Ecology

View Paper: https://www.semanticscholar.org/paper/68b9e62ec4172c5198ba23f6ea43cbad1f43c7bf

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In Astronomy and Astrophysics

  1. C. Conroy
  2. P. Hopkins
  3. P. V. van Dokkum
  4. M. Cappellari
  5. L. Hernquist
  6. Simon D. M. White
  7. Volker Springel
  8. R. Dav'e

In Computer Vision and Pattern Recognition

  1. M. Cappellari
  2. J. Falc'on-Barroso
  3. C. Maraston
  4. C. Conroy
  5. P. Sánchez-Blázquez
  6. M. Koleva
  7. J. Leja
  8. Benjamin D. Johnson

In Ecology

  1. C. Conroy
  2. M. Blanton
  3. J. Leja
  4. Benjamin D. Johnson
  5. Eric Emsellem
  6. Joshua S. Speagle
  7. Robert Nichol
  8. Daniel J. Eisenstein

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