Stellar population models based on the SDSS-IV MaStar library of stellar spectra – I. Intermediate-age/old models Article Swipe
Claudia Maraston
,
Lewis Hill
,
D. Thomas
,
Renbin Yan
,
Yuca C Chen
,
Jianhui Lian
,
Taniya Parikh
,
Justus Neumann
,
S. Meneses-Goytia
,
Matthew A. Bershady
,
Niv Drory
,
Dmitry Bizyaev
,
Alice Concas
,
Joel R. Brownstein
,
Daniel Lazarz
,
Guy S. Stringfellow
,
Keivan G. Stassun
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/staa1489
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/staa1489
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 µm and share the same spectral resolution ($R\sim 1800$) 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 $\rm {\mathit{ t}\gt 200 \,Myr, -2 \lt = [Z/H] \lt = + 0.35}$, 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 λ > 0.7 µm 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 (Teff, log g, [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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/mnras/staa1489
- https://academic.oup.com/mnras/article-pdf/496/3/2962/33484758/staa1489.pdf
- OA Status
- bronze
- Cited By
- 75
- References
- 119
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2986096548
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2986096548Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/mnras/staa1489Digital Object Identifier
- Title
-
Stellar population models based on the SDSS-IV MaStar library of stellar spectra – I. Intermediate-age/old modelsWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-06-01Full publication date if available
- Authors
-
Claudia Maraston, Lewis Hill, D. Thomas, Renbin Yan, Yuca C Chen, Jianhui Lian, Taniya Parikh, Justus Neumann, S. Meneses-Goytia, Matthew A. Bershady, Niv Drory, Dmitry Bizyaev, Alice Concas, Joel R. Brownstein, Daniel Lazarz, Guy S. Stringfellow, Keivan G. StassunList of authors in order
- Landing page
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https://doi.org/10.1093/mnras/staa1489Publisher landing page
- PDF URL
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https://academic.oup.com/mnras/article-pdf/496/3/2962/33484758/staa1489.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/mnras/article-pdf/496/3/2962/33484758/staa1489.pdfDirect OA link when available
- Concepts
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Physics, Stellar population, Astrophysics, Spectral line, Stellar evolution, Population, Astronomy, Stars, Star formation, Medicine, Environmental healthTop concepts (fields/topics) attached by OpenAlex
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75Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 13, 2024: 14, 2023: 16, 2022: 17, 2021: 10Per-year citation counts (last 5 years)
- References (count)
-
119Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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