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Register a new userSDSS-IV MaStar -- A Large and Comprehensive Empirical Stellar Spectral Library: First Release
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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 of 3,622-10,354A 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 SDSS-IV/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 [alpha/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 Sloan Digital Sky Survey Data Release 15. We expect the final release of the library to contain more than 10,000 stars.
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We introduce the ongoing MaStar project, which is going to construct a large, well-calibrated, high quality empirical stellar library with more than 8000 stars covering the wavelength range from 3622 to 10,354A at a resolution of R~2000, and with better than 3% relative flux calibration. The spectra are taken using hexagonal fiber bundles feeding the BOSS spectrographs on the 2.5m Sloan Foundation Telescope, by piggybacking on the SDSS-IV/APOGEE-2 observations. Compared to previous efforts of empirical libraries, the MaStar Library will have a more comprehensive stellar parameter coverage, especially in cool dwarfs, low metallicity stars, and stars with different [alpha/Fe]. This is achieved by a target selection method based on large spectroscopic catalogs from APOGEE, LAMOST, and SEGUE, combined with photometric selection. This empirical library will provide a new basis for calibrating theoretical spectral libraries and for stellar population synthesis. In addition, with identical spectral coverage and resolution to the ongoing integral field spectroscopy survey of nearby galaxies --- SDSS-IV/MaNGA (Mapping Nearby Galaxies at APO). This library is ideal for spectral modeling and stellar population analysis of MaNGA data.
We report the stellar atmospheric parameters for 7503 spectra contained in the first release of the MaNGA stellar library (MaStar) in SDSS DR15. The first release of MaStar contains 8646 spectra measured from 3321 unique stars, each covering the wavelength range 3622 AA to 10354 AA with a resolving power of $R sim$ 1800. In this work, we first determined the basic stellar parameters: effective temperature ($rm T_{eff}$), surface gravity ($log g$), and metallicity ($rm[Fe/H]$), which best fit the data using an empirical interpolator based on the Medium-resolution Isaac Newton Telescope library of empirical spectra (MILES), as implemented by the University of Lyon Spectroscopic analysis Software (Koleva et al. 2008, ULySS) package. While we analyzed all 8646 spectra from the first release of MaStar, since MaStar has a wider parameter-space coverage than MILES, not all of these fits are robust. In addition, not all parameter regions covered by MILES yield robust results, likely due to the non-uniform coverage of the parameter space by MILES. We tested the robustness of the method using the MILES spectra itself and identified a proxy based on the local density of the training set. With this proxy, we identified 7503 MaStar spectra with robust fitting results. They cover the range from 3179K to 20,517K in effective temperature ($rm T_{eff}$), from 0.40 to 5.0 in surface gravity ($log g$), and from $-$2.49 to $+$0.73 in metallicity ($rm[Fe/H]$).
We use the first release of the SDSS/MaStar stellar library comprising ~9000, high S/N spectra, to calculate integrated spectra of stellar population models. The models extend over the wavelength range 0.36-1.03 micron and share the same spectral resolution (R~1800) and flux calibration as the SDSS-IV/MaNGA galaxy data. The parameter space covered by the stellar spectra collected thus far allows the calculation of models with ages and chemical composition in the range t>200 Myr, -2 <=[Z/H]<= + 0.35, which will be extended as MaStar proceeds. Notably, the models include spectra for dwarf Main Sequence stars close to the core H-burning limit, as well as spectra for cold, metal-rich giants. Both stellar types are crucial for modelling lambda>0.7 micron absorption spectra. Moreover, a better parameter coverage at low metallicity allows the calculation of models as young as 500 Myr and the full account of the Blue Horizontal Branch phase of old populations. We present models adopting two independent sets of stellar parameters (T_eff, logg, [Z/H]). In a novel approach, their reliability is tested on the fly using the stellar population models themselves. We perform tests with Milky Way and Magellanic Clouds globular clusters, finding that the new models recover their ages and metallicities remarkably well, with systematics as low as a few per cent for homogeneous calibration sets. We also fit a MaNGA galaxy spectrum, finding residuals of the order of a few per cent comparable to the state-of-art models, but now over a wider wavelength range.
MEGARA is an optical integral field and multiobject fibre based spectrograph for the 10.4m Gran Telescopio CANARIAS that offers medium to high spectral resolutions (FWHM) of R $simeq$ 6000, 12000, 20000. Commissioned at the telescope in 2017, it started operation as a common-user instrument in 2018. We are creating an instrument-oriented empirical spectral library from MEGARA-GTC stars observations, MEGASTAR, crucial for the correct interpretation of MEGARA data. This piece of work describes the content of the first release of MEGASTAR, formed by the spectra of 414 stars observed with R $simeq$ 20000 in the spectral intervals from 6420 to 6790 $r{A}$ and from 8370 to 8885 $r{A}$, and obtained with a continuum average signal to noise ratio around 260. We describe the release sample, the observations, the data reduction procedure and the MEGASTAR database. Additionally, we include in Appendix A, an atlas with the complete set of 838 spectra of this first release of the MEGASTAR catalogue.
We introduce CoSHA: a Code for Stellar properties Heuristic Assignment. In order to estimate the stellar properties, CoSHA implements a Gradient Tree Boosting algorithm to label each star across the parameter space ($T_{text{eff}}$, $log{g}$, $left[text{Fe}/text{H}right]$, and $left[alpha/text{Fe}right]$). We use CoSHA to estimate these stellar atmospheric parameters of $22,$k unique stars in the MaNGA Stellar Library (MaStar). To quantify the reliability of our approach, we run both internal tests using the Gottingen Stellar Library (GSL, a theoretical library) and the first data release of MaStar, and external tests by comparing the resulting distributions in the parameter space with the APOGEE estimates of the same properties. In summary, our parameter estimates span in the ranges: $T_{text{eff}}=[2900,12000],$K, $log{g}=[-0.5,5.6]$, $left[text{Fe}/text{H}right]=[-3.74,0.81]$, $left[alpha/text{Fe}right]=[-0.22,1.17]$. We report internal (external) uncertainties of the properties of $sigma_{T_{text{eff}}}sim48,(325),$K, $sigma_{log{g}}sim0.2,(0.4)$, $sigma_{left[text{Fe}/text{H}right]}sim0.13,(0.27)$, $sigma_{left[alpha/text{Fe}right]}sim0.09,(0.14)$. These uncertainties are comparable to those of other methods with similar objectives. Despite the fact that CoSHA is not aware of the spatial distribution of these physical properties in the Milky Way, we are able to recover the main trends known in the literature with great statistical confidence. The catalogue of physical properties can be accessed in url{http://ifs.astroscu.unam.mx/MaStar}.
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