Galaxy Properties for DR8 spectra from MPA-JHU

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MPA-JHU

For DR8 galaxy spectra (virtually all of which were in DR7 too) we provide the “galSpec” galaxy properties from MPA-JHU. These properties are deprecated in dr12 in favor of the Wisconsin, Portsmouth, and Granada team analyses of the same data, but are provided in dr12 for comparison.

We refer to this set of line measurements as the MPA-JHU measurements, after the Max Planck Institute for Astrophysics and the Johns Hopkins University where the technique was developed. The Galspec product provided by the MPA-JHU group is based on the methods of Brinchmann et al. 2004, Kauffmann et al. 2003, and Tremonti et al. 2004. These have been run on previous SDSS data releases and the catalog has been made publicly available since DR4, and has been included in the SDSS data release since DR8.

We provide MPA measurements for all objects that idlspec2d calls a galaxy in rund2=26 (used for the DR7 plates). This code has not been run on the new SEGUE-2 plates in run2d=103 and 104 or on any BOSS spectra. We briefly describe the technique here; details can be found in the papers referenced above.

These files are line-by-line matched with the specObj file. However, no SDSS-III spectra have been analyzed by galSpec. The galSpec pipelines have not been run on all data; if the PLATE, FIBERID, MJD values are -1 then there is no result for that spectrum. Furthermore, if RELIABLE in the galSpecInfo file is set to zero, then the parameters are not considered reliable.

These files contain measurements of emission lines in galaxies, Lick and other indices, and derived quantities. The sections below describe the methods in more detail.

Galaxy emission lines

In measuring the nebular emission lines of galaxies, it is important to properly account for the galaxy continuum which is very rich in stellar absorption features. In DR8 we offer a set of emission line measurements for galaxy spectra which makes use of stellar population synthesis models to accurately fit and subtract the stellar continuum.

We first scale each galaxy spectrum to match its r-band fiber magnitude, and correct each spectrum for Galactic extinction following SFD and the O’Donnell (1994) attenuation curve. We adopt the basic assumption that any galaxy star formation history can be approximated as a sum of discrete bursts. Our library of template spectra is composed of single stellar population models generated using the population synthesis code of Bruzual & Charlot (2003). We have used a new version kindly made available by the authors which incorporates the MILES empirical spectral library (Sanchez-Blazquez et al. 2006; these spectra cover the range 3525-7500 Angstroms with 2.3 Angstrom FWHM). The spectral-type and metallicity coverage, flux-calibration accuracy, and number of stars in the library represent a substantial improvement over previous libraries. Our templates include models of ten different ages (0.005, 0.025, 0.1, 0.2, 0.6, 0.9, 1.4, 2.5, 5, 10 Gyr) and four metallicities (1/4, 1/2, 1, 2.4 solar). For each galaxy we transform the templates to the measured redshift and velocity dispersion and resample them to match the data. To construct the best-fitting model we perform a non-negative least squares fit to a linear combination of our ten single-age populations, with internal dust attenuation modeled as an additional free parameter following Charlot & Fall (2000). Given the S/N of the spectra, we model galaxies as single metallicity populations and select the metallicity that yields the minimum χ2.

After subtracting the best-fitting stellar population model of the continuum, we remove any remaining residuals (usually of order a few percent) with a sliding 150-pixel median, and fit all the nebular emission lines simultaneously as Gaussians. In doing so, we require that the Balmer lines (Hδ, Hγ, Hβ, and Hα) have the same line width and velocity offset, and likewise for the forbidden lines. We take into account the wavelength-dependent instrumental resolution of each fiber, which is measured by the idlspec2d pipeline from the arc lamp images.

Derived galaxy parameters

The files and tables above also include a number of galaxy parameters derived by the MPA-JHU group available.

  • BPT classification: We supply emission line classifications based on the BPT diagram. Galaxies are divided into “Star Forming”, “Composite”, “AGN”, “Low S/N Star Forming”, “Low S/N AGN”, and “Unclassifiable” categories.
  • Stellar Mass: Stellar masses are calculated using the Bayesian methodology and model grids described in Kauffmann et al. (2003). The spectra are measured through a 3 arcsec aperture, and therefore do not represent the entire galaxy. We therefore base our model on the ugriz galaxy photometry alone (rather than the spectral indices Dn(4000) and Hδ used by Kauffmann et al. 2003). We have corrected the photometry for the small contribution due to nebular emission using the spectra. We estimate the stellar mass within the SDSS spectroscopic fiber aperture using fiber magnitudes and the total stellar mass using model magnitudes. A Kroupa (2001) initial mass function is assumed. We output the stellar mass corresponding to the median and 2.5%, 16%, 84%, 97.5% of the probability distribution function.
  • Nebular Oxygen Abundance: Nebular oxygen abundances are estimated from the strong optical emission lines ([O II] 3727, Hβ, [O III] 5007, [N II] 6548, 6584 and [S II] 6717, 6731) using the Bayesian methodology outlined in Tremonti at al. (2004) and Brinchmann et al. (2004). Oxygen abundances are only computed for objects classified as “Star Forming”. We output the value of 12+\log(O/H) at the median and 2.5%, 16%, 84%, 97.5% of the probability distribution function.
  • Star Formation Rate: Star formation rates (SFRs) are computed within the galaxy fiber aperture using the nebular emission lines as described in Brinchmann et al. (2004). SFRs outside of the fiber are estimated using the galaxy photometry following Salim et al. (2007). For AGN and galaxies with weak emission lines, SFRs are estimated from the photometry. We report both the fiber SFR and the total SFR at the median and 2.5%, 16%, 84%, 97.5% of the probability distribution function.
  • Specific SFR: The Specific SFR (SFR divided by the stellar mass) has been calculated by combining the SFR and stellar mass likelihood distributions as outlined in Appendix A of Brinchmann et al. (2004). We report both the fiber and the total specific SFR at the median and 2.5%, 16%, 84%, 97.5% of the probability distribution function.