Principal Component Analysis of Sloan Digital Sky Survey Stellar Spectra (original) (raw)

Principal Component Analysis of SDSS Stellar Spectra

Arxiv preprint arXiv:1001.4340, 2010

arXiv:1001.4340v2 [astro-ph.SR] 26 Jan 2010 Principal Component Analysis of SDSS Stellar Spectra Rosalie C. McGurk, Amy E. Kimball, Zeljko Ivezic Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 ABSTRACT ... 2.3. The g − r Color Binning ...

SDSS spectroscopic survey of stars

Arxiv preprint astro-ph/ …, 2007

In addition to optical photometry of unprecedented quality, the Sloan Digital Sky Survey (SDSS) is also producing a massive spectroscopic database. We discuss determination of stellar parameters, such as effective temperature, gravity and metallicity from SDSS spectra, describe correlations between kinematics and metallicity, and study their variation as a function of the position in the Galaxy. We show that stellar parameter estimates by Beers et al. show a good correlation with the position of a star in the g − r vs. u − g colorcolor diagram, thereby demonstrating their robustness as well as a potential for photometric parameter estimation methods. Using Beers et al. parameters, we find that the metallicity distribution of the Milky Way stars at a few kpc from the galactic plane is bimodal with a local minimum at [Z/Z ⊙ ] ∼ −1.3. The median metallicity for the low-metallicity [Z/Z ⊙ ] < −1.3 subsample is nearly independent of Galactic cylindrical coordinates R and z, while it decreases with z for the high-metallicity [Z/Z ⊙ ] > −1.3 sample. We also find that the low-metallicity sample has ∼2.5 times larger velocity dispersion and that it does not rotate (at the ∼10 km/s level), while the rotational velocity of the high-metallicity sample decreases smoothly with the height above the galactic plane.

Empirical Modeling of the Stellar Spectrum of Galaxies

Astronomical Journal, 2005

An empirical method of modeling the stellar spectrum of galaxies is proposed, based on two successive applications of Principal Component Analysis (PCA). PCA is first applied to the newly available stellar library STELIB, supplemented by the J, H and K$_{s}$ magnitudes taken mainly from the 2 Micron All Sky Survey (2MASS). Next the resultant eigen-spectra are used to fit the observed spectra of a sample of 1016 galaxies selected from the Sloan Digital Sky Survey Data Release One (SDSS DR1). PCA is again applied, to the fitted spectra to construct the eigen-spectra of galaxies with zero velocity dispersion. The first 9 galactic eigen-spectra so obtained are then used to model the stellar spectrum of the galaxies in SDSS DR1, and synchronously to estimate the stellar velocity dispersion, the spectral type, the near-infrared SED, and the average reddening. Extensive tests show that the spectra of different type galaxies can be modeled quite accurately using these eigen-spectra. The method can yield stellar velocity dispersion with accuracies better than 10%, for the spectra of typical S/N ratios in SDSS DR1.

SEGUE: A SPECTROSCOPIC SURVEY OF 240,000 STARS WITH g = 14-20

Astronomical Journal, 2009

The Sloan Extension for Galactic Understanding and Exploration (SEGUE) survey obtained ≈ 240,000 moderate resolution (R ∼ 1800) spectra from 3900Å to 9000Å of fainter Milky Way stars (14.0 < g < 20.3) of a wide variety of spectral types, both main-sequence and evolved objects, with the goal of studying the kinematics and populations of our Galaxy and its halo. The spectra are clustered in 212 regions spaced over three-quarters of the sky. Radial velocity accuracies for stars are σ(RV) ∼ 4 km s −1 at g < 18, degrading to σ(RV) ∼ 15 km s −1 at g ∼ 20. For stars with signal-to-noise ratio > 10 per resolution element, stellar atmospheric parameters are estimated, including metallicity, surface gravity, and effective temperature. SEGUE obtained 3500deg 2 of additional ugriz imaging (primarily at low Galactic latitudes) providing precise multicolor photometry (σ(g, r, i) ∼ 2%), (σ(u, z) ∼ 3%) and astrometry (≈ 0.1 ′′ ) for spectroscopic target selection. The stellar spectra, imaging data, and derived parameter catalogs for this survey are publicly available as part of Sloan Digital Sky Survey Data Release 7.

Quantitative Stellar Spectral Classification. IV: Application to the Open Cluster IC 2391

2009

Se ha extendido, a las estrellas del tipo espectral B, el método desarrollado por Stock y Stock (1999) para estrellas del tipo espectral A-K, con el cual es posible derivar magnitudes absolutas y colores intrínsecos a partir de los anchos equivalentes de las líneas de absorción de los espectros estelares. Espectros de estrellas tipo-B para las cuales el catálogo de Hipparcos proporciona paralajes con un error menor al 20%, fueron observados con el reflector de 1-m del CIDA equipado con espectrógrafo Richardson y un detector CCD Thompson 576x384. Utilizando una rejilla de 600 lineas/mm se obtuvo una dispersión en el primer orden de 1.753 A/pixel. Para cubrir el rango espectral comprendido entre 3850Å y 5750Å fue necesario utilizar la rejilla en dos posiciones distintas, teniendo un solapamiento en la región entre 4800Å y 4900Å. Fueron observadas un total de 116 estrellas, pero no todas en las dos posiciones de la rejilla. Se identificaron un total de 12 lineas de absorción en los espectros y se midieron sus anchos equivalentes. Estos fueron relacionados con las magnitudes absolutas derivadas del Catálogo Hipparcos y con los colores intrínsecos (deducidos de los tipos espectrales MK), por medio de polinomios de primer y segundo orden y combinaciones de dos o tres lineas como variables independientes. Las mejores soluciones fueron obtenidas con polinomios de tres lineas, reproduciendo las magnitudes absolutas con un residuo promedio de 0.40 magnitudes, y los colores intrínsecos con un residuo promedio de 0.016 magnitudes.

Using spectroscopic data to disentangle stellar population properties

Astronomy & Astrophysics, 2003

It is well known that, when analyzed at the light of current synthesis model predictions, variations in the physical properties of single stellar populations (e.g. age, metallicity, initial mass function, element abundance ratios) may have a similar effect in their integrated spectral energy distributions. The confusion is even worsened when more realistic scenarios, i.e. composite star formation histories, are considered. This is, in fact, one of the major problems when facing the study of stellar populations in star clusters and galaxies. Typically, the observational efforts have been aimed to find the most appropriate spectroscopic indicators in order to avoid, as far as possible, degeneracies in the parameter space. However, from a practical point of view, the most suited observables are not, necessarily, those that provide more orthogonality in that parameter space, but those that give the best balance between parameter degeneracy and sensitivity to signal-to-noise ratio per Å, SN(Å). In order to achieve the minimum combined total error in the derived physical parameters, this work discusses how the functional dependence of typical line-strength indices and colors on SN(Å) allows to define a suitability parameter which helps to obtain better realistic combinations of spectroscopic data. As an example, we discuss in more detail the problem of breaking the well known age-metallicity degeneracy in relatively old stellar populations, comparing the suitability of different spectroscopic diagrams for a simple stellar population of solar metallicity and 12 Gyr old.

SDSS-IV MaStar: A Large and Comprehensive Empirical Stellar Spectral Library—First Release

The Astrophysical Journal, 2019

We present the first release of the MaNGA Stellar Library (MaStar), which is a large, well-calibrated, high-quality empirical library covering the wavelength range 3622-10354 Å at a resolving power of R∼1800. The spectra were obtained using the same instrument as used by the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) project, by piggybacking on the Sloan Digital Sky Survey (SDSS-IV)/Apache Point Observatory Galaxy Evolution Experiment 2-N (APOGEE-2N) observations. Compared to previous empirical libraries, the MaStar library will have a higher number of stars and a more comprehensive stellar-parameter coverage, especially of cool dwarfs, low-metallicity stars, and stars with different [α/Fe], achieved by a sophisticated target-selection strategy that takes advantage of stellar-parameter catalogs from the literature. This empirical library will provide a new basis for stellar-population synthesis and is particularly well suited for stellar-population analysis of MaNGA galaxies. The first version of the library contains 8646 high-quality per-visit spectra for 3321 unique stars. Compared to photometry, the relative flux calibration of the library is accurate to 3.9% in g−r, 2.7% in r−i, and 2.2% in i−z. The data are released as part of SDSS Data Release 15. We expect the final release of the library to contain more than 10,000 stars.

QUALITATIVE INTERPRETATION OF GALAXY SPECTRA

The Astrophysical Journal, 2012

We describe a simple step-by-step guide to qualitative interpretation of galaxy spectra. Rather than an alternative to existing automated tools, it is put forward as an instrument for quick-look analysis and for gaining physical insight when interpreting the outputs provided by automated tools. Though the recipe is for general application, it was developed for understanding the nature of the Automatic Spectroscopic K-means-based (ASK) template spectra. They resulted from the classification of all the galaxy spectra in the Sloan Digital Sky Survey data release 7, thus being a comprehensive representation of the galaxy spectra in the local universe. Using the recipe, we give a description of the properties of the gas and the stars that characterize the ASK classes, from those corresponding to passively evolving galaxies, to H ii galaxies undergoing a galaxy-wide starburst. The qualitative analysis is found to be in excellent agreement with quantitative analyses of the same spectra. We compare the mean ages of the stellar populations with those inferred using the code starlight. We also examine the estimated gas-phase metallicity with the metallicities obtained using electron-temperature-based methods. A number of byproducts follow from the analysis. There is a tight correlation between the age of the stellar population and the metallicity of the gas, which is stronger than the correlations between galaxy mass and stellar age, and galaxy mass and gas metallicity. The galaxy spectra are known to follow a one-dimensional sequence, and we identify the luminosity-weighted mean stellar age as the affine parameter that describes the sequence. All ASK classes happen to have a significant fraction of old stars, although spectrum-wise they are outshined by the youngest populations. Old stars are metal-rich or metal-poor depending on whether they reside in passive galaxies or in star-forming galaxies.

Stellar parametrization fromGaiaRVS spectra

Astronomy & Astrophysics, 2015

Context. Among the myriad of data collected by the ESA Gaia satellite, about 150 million spectra will be delivered by the Radial Velocity Spectrometer (RVS) for stars as faint as G RVS ∼ 16. A specific stellar parametrization will be performed on most of these RVS spectra, i.e. those with enough high signal-to-noise ratio (S/N), which should correspond to single stars that have a magnitude in the RVS band brighter than ∼14.5. Some individual chemical abundances will also be estimated for the brightest targets. Aims. We describe the different parametrization codes that have been specifically developed or adapted for RVS spectra within the GSP-Spec working group of the analysis consortium. The tested codes are based on optimisation (FERRE and GAUGUIN), projection (MATISSE), or pattern-recognition methods (Artificial Neural Networks). We present and discuss each of their expected performances in the recovered stellar atmospheric parameters (effective temperature, surface gravity, overall metallicity) for B-to K-type stars. The performances for determining of [α/Fe] ratios are also presented for cool stars. Methods. Each code has been homogeneously tested with a large grid of RVS simulated synthetic spectra of BAFGK-spectral types (dwarfs and giants), with metallicities varying from 10 −2.5 to 10 +0.5 the solar metallicity, and taking variations of ±0.4 dex in the composition of the α-elements into consideration. The tests were performed for S/N ranging from ten to 350. Results. For all the stellar types we considered, stars brighter than G RVS ∼ 12.5 are very efficiently parametrized by the GSP-Spec pipeline, including reliable estimations of [α/Fe]. Typical internal errors for FGK metal-rich and metal-intermediate stars are around 40 K in T eff , 0.10 dex in log(g), 0.04 dex in [M/H], and 0.03 dex in [α/Fe] at G RVS = 10.3. They degrade to 155 K in T eff , 0.15 dex in log(g), 0.10 dex in [M/H], and 0.1 dex in [α/Fe] at G RVS ∼ 12. Similar accuracies in T eff and [M/H] are found for A-type stars, while the log(g) derivation is more accurate (errors of 0.07 and 0.12 dex at G RVS = 12.6 and 13.4, respectively). For the faintest stars, with G RVS > ∼ 13−14, a T eff input from the spectrophotometric-derived parameters will allow the final GSP-Spec parametrization to be improved. Conclusions. The reported results, while neglecting possible mismatches between synthetic and real spectra, show that the contribution of the RVS-based stellar parameters will be unique in the brighter part of the Gaia survey, which allows for crucial age estimations and accurate chemical abundances. This will constitute a unique and precious sample, providing many pieces of the Milky Way history puzzle with unprecedented precision and statistical relevance.