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Spectro-Photometric Model Fitting

The stellar population models of Maraston (2005) and Maraston et al. (2009) are used to perform a best-fit to the observed ugriz magnitudes of BOSS galaxies with the spectroscopic redshift determined by the BOSS pipeline, using an adaptation of the publicly available Hyper-Z code of Bolzonella, Miralles & Pelló (2000). The fit is carried out on extinction corrected model magnitudes that are scaled to the i-band c-model magnitude, i.e.:

mag_x = modelmag_x - extinction_x + (cmodelmag_i - modelmag_i),

where x denotes the photometric band (ugriz).

Two sets of template spectra are used (for details, see Maraston et al. 2013).

  1. a passively evolving galaxy with a two-component metallicity of same age and no ongoing star formation or reddening, as in Maraston et al. (2009),
  2. an ensemble of canonical star formation modes, including exponentially-declining, constant with truncation, and constant, star formation, for various timescales and various metallicities, as in Maraston et al. (2006). In order to minimize the event of low-age, high-dust fake solutions, reddening is not included (Pforr, Maraston & Tonini 2012).

The output of the fit for each galaxy includes: age, star formation mode, metallicity, the absolute rest-frame magnitude in the K-band as derived from the best-fitting model, plus the reduced χ2. Additionally, the best fit model spectrum as well as the probability distribution function (PDF) for the stellar mass are provided.

Stellar masses and star formation rates are computed from the best-fit SED as in Maraston et al. (2006). Furthermore the stellar mass at the median PDF and 68% confidence levels are provided.

Both calculation sets are available for Salpeter and Kroupa initial mass functions, and both account for the cases of with and without stellar mass losses from stellar evolution.

Rest-frame magnitudes in other bands and additional quantities described by Maraston et al. (2013) may be obtained by contacting C. Maraston.

Stellar Kinematics and Emission Line Fluxes

Portsmouth stellar kinematics and emission-line flux measurements Thomas et al. (2013) are based on adaptations of the publicly available codes Penalized PiXel Fitting (pPXF, Cappellari & Emsellem 2004) and Gas and Absorption Line Fitting code (GANDALF v1.5; Sarzi et al. 2006) to calculate stellar kinematics and to derive emission line properties. GANDALF fits stellar population and Gaussian emission line templates to the galaxy spectrum simultaneously to separate stellar continuum and absorption lines from the ionized gas emission. Stellar kinematics are evaluated by pPXF where the line-of-sight velocity distribution is fitted directly in pixel space. The fits account for the impact of diffuse dust in the galaxy on the spectral shape adopting a Calzetti (2001) obscuration curve. The code further determines the kinematics of the gas (velocity and velocity dispersion) and measures emission line fluxes and equivalent widths (EWs) on the resulting Gaussian emission line template.

The stellar population models from Maraston & Strömbäck (2011) based on the MILES stellar library (Sánchez-Blázquez et al. 2006), augmented with theoretical spectra at wavelengths λ < 3500 Å from Maraston et al. (2009), based on the theoretical library UVBLUE (Rodríguez-Merino et al. 2005) are adopted as galaxy templates (available at www.maraston.eu/M11). The stellar population templates were fixed to solar metallicity to limit computing time, with an age range from 6.5 Myr to 11 Gyr. The templates were slightly downgraded from MILES spectral resolution (Beifiori et al. 2011) to the resolution of BOSS.

Outputs from this fitting process include stellar velocity dispersions, emission-line fluxes (both observed and de-reddened) and equivalent widths, the gas kinematics, an E(B-V) value and derived BPT classifications. The reddening values can be obtained by plugging the E(B-V) value for each object into the dust attenuation equation of Calzetti et al. (2000). A reduced χ2 value is also provided for the fit, as well as Amplitude-over-Noise (AoN) values for each of the emission lines.

The fits account for the impact of diffuse dust in the galaxy on the spectral shape, adopting a Calzetti (2001) obscuration curve. The code further determines the kinematics of the gas (velocity and velocity dispersion), and measures emission line fluxes and equivalent widths (EWs) on the resulting Gaussian emission line template.

An emission line measurement is made when the amplitude-over-noise (AoN) ratio is larger than two, which implies that many emission lines are too weak to be detected in BOSS. Reasonable AoN ratios can be obtained in a subsample of BOSS galaxies, however, for some of the stronger lines such as the forbidden lines [OIII]5007 and [NII]6583, as well as the Balmer lines Hβ and Hα. EWs are calculated as the ratio between line and continuum fluxes.

The original GANDALF code considers two dust components: the diffuse dust in the galaxy affecting the spectral shape, and dust in emission line regions additionally affecting emission line fluxes and ratios. The latter is estimated through the Balmer decrement between Hβ and Hα, when available (Veilleux & Osterbrock 1987).

However, the relatively low signal-to-noise ratios in the BOSS spectra make measurement of the Balmer decrement highly uncertain. In cases in which the Hβ emission line is barely detected, the inclusion of this second dust component tends to yield unreasonably high values for dust extinction. Thus, Thomas et al. (2013) do not consider this second dust component in the fits; instead, they focus on the diffuse dust component that only affects the spectral shape adopting a Calzetti (2001) obscuration curve. The emission line fluxes provided have been corrected for dust extinction obtained in this way.

Note that the spectra have not been corrected for Milky Way foreground extinction before the emission lines analysis. This does not affect the emission line measurements, but does imply that the resulting E(B-V) values need to be corrected for Milky Way extinction a posteriori. To calibrate the procedure, Thomas et al. (2013) have derived stellar velocity dispersions and emission line properties for a subset of SDSS galaxies from SDSS Data Release 7 (Abazajian et al. 2009), and have found satisfying agreement.

The WMAP 7 flat ΛCDM cosmology with H0 = 70, Ωm = 0.274, and ΩΛ = 0.726. (White et al. 2011) is applied universally to each of the Portsmouth-Wisconsin-Granada computations by the BOSS Pipeline.

DATA

Data Release 10 was processed under GALAXY_VERSION v1_0.

Output is browsable via the Catalog Archive Server (CAS) database by selecting:

FITS output files are available from BOSS_GALAXY_REDUX/GALAXY_VERSION available at the SAS URL: http://data.sdss3.org/sas/dr10/boss/spectro/redux/galaxy/v1_0.

You may download data based on the Portsmouth Stellar Mass Passive datamodel from:

passive_krou:

passive_salp:

You may download data based on the Portsmouth Stellar Mass Star Forming datamodel from:

starforming_krou:

starforming_salp:

You may download the data based on the Portsmouth Emission-Line Kinematics datamodel

summary:

full:

REFERENCES

Abazajian, K.N., et al., 2009, ApJS, 182, 543, doi:10.1088/0067-0049/182/2/543.

Bolzonella, M., Miralles, J.M., Pelló, R., 2000, A&A, 363, 476, ads:2000A%26A...363..476B.

Calzetti, D., 2001, PASP, 113, 9, doi:10.1086/324269.

Maraston, C., 2005, MNRAS, 362(3), 799, doi:10.1111/j.1365-2966.2005.09270.x.

Maraston, C., Strömbäck, G., Thomas, D., Wake, D.A., Nichol, R.C., 2009, MNRAS Letters, 394(1), L107, doi:10.1111/j.1745-3933.2009.00621.x.

Maraston, C., Strömbäck, G., 2011, MNRAS Letters, 394(1), L107, doi:10.1111/j.1365-2966.2011.19738.x.

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Pforr, J., Maraston, C., Tonini, C., 2012, MNRAS, 422, 3285, ApJ, 626, 411, doi:10.1111/j.1365-2966.2012.20848.x.

Rodríguez-Merino, L.H., Chavez, M., Bertone, E., Buzzoni, A., 2005, ApJ, 626, 411, doi:10.1086/429858.

Sánchez-Blázquez, P., R.F. Peletier, J. Jiménez-Vincente, N. Cardiel, J. Cenarro, J. Falcón-Barroso, J. Gorgas, S. Selam, A. Vazdekis, 2006, MNRAS, 371(2), 703, doi:10.1111/j.1365-2966.2006.10699.x.

Sarzi, M., Falcón-Barroso, J., Davies, R.L., Bacon, R., Bureau, M., Cappellari, M., de Zeeuw, P.T., Emsellem, E., Kambiz, F., Krajnović, D., Kuntschner, H., McDermid, R.M., Peletier, R.F., 2006, MNRAS, 366(4), 1151, doi:10.1111/j.1365-2966.2005.09839.x.

Thomas, D., Steele, O., Maraston, C., Johansson, J., Beifiori, A., Pforr, J., Strömbäck, G., Tremonti, C.A., Wake, D., Bizyaev, D., Bolton, A., Brewington, H., Brownstein, J.R., Comparat, J., Kneib, J.-P., Malanushenko, E., Malanushenko, V., Oravetz, D., Pan, K., Parejko, J.K., Schneider, D.P., Shelden, A., Simmons, A., Snedden, S., Tanaka, M., Weaver, B.A., Yan, R., 2013, MNRAS, 431(2), 1383, doi:10.1093/mnras/stt261.

Veilleux, S., Osterbrock, D.E., 1987, ApJS, 63, 295, doi:10.1086/191166.

White, M., Blanton, M., Bolton, A., Schlegel, D., Tinker, J., Berlind, A., da Costa, L., Kazin, E., Lin, Y.T., Maia, M., McBride, C.K., Padmanabhan, N., Parejko, J., Percival, W., Prada, F., Ramos, B., Sheldon, E., de Simoni, F., Skibba, R., Thomas, D., Wake, D., Zehavi, I., Zheng, Z., Nichol, R., Schneider, D.P., Strauss, M.A., Weaver, B.A., Weinberg, D.H., 2011, ApJ, 728, 126, doi:10.1088/0004-637X/728/2/126.

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