Modelling simple stellar populations in the near-ultraviolet to near-infrared with the X-shooter Spectral Library (XSL)



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Verro, K. and Trager, S. C. and Peletier, R. F. and Lançon, A. and Arentsen, A. and Chen, Y.-P. and Coelho, P. R. T. and Dries, M. and Falcón Barroso, J. and Gonneau, A. and Lyubenova, M. and Martins, L. and Prugniel, P. and Sánchez Blázquez, Patricia and Vazdekis, A. (2022) Modelling simple stellar populations in the near-ultraviolet to near-infrared with the X-shooter Spectral Library (XSL). Astronomy & Astrophysics, 661 . ISSN 0004-6361

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We present simple stellar population models based on the empirical X-shooter Spectral Library (XSL) from near-ultraviolet (NUV) to near-infrared (NIR) wavelengths. The unmatched characteristics of the relatively high resolution and extended wavelength coverage (350-2480 nm, R similar to 10 000) of the XSL population models bring us closer to bridging optical and NIR studies of intermediate-age and old stellar populations. It is now common to find good agreement between observed and predicted NUV and optical properties of stellar clusters due to our good understanding of the main-sequence and early giant phases of stars. However, NIR spectra of intermediate-age and old stellar populations are sensitive to cool K and M giants. The asymptotic giant branch, especially the thermally pulsing asymptotic giant branch, shapes the NIR spectra of 0.5-2 Gyr old stellar populations; the tip of the red giant branch defines the NIR spectra of older populations. We therefore construct sequences of the average spectra of static giants, variable O-rich giants, and C-rich giants to be included in the models separately. The models span the metallicity range -2.2 < [Fe/H] < +0.2 and ages above 50 Myr, a broader range in the NIR than in other models based on empirical spectral libraries. We focus on the behaviour of colours and absorption-line indices as a function of age and metallicity. Our models can reproduce the integrated optical colours of the Coma cluster galaxies at the same level as other semi-empirical models found in the literature. In the NIR, there are notable differences between the colours of the models and Coma cluster galaxies. Furthermore, the XSL models expand the range of predicted values of NIR indices compared to other models based on empirical libraries. Our models make it possible to perform in-depth studies of colours and spectral features consistently throughout the optical and the NIR range to clarify the role of evolved cool stars in stellar populations.

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© ESO 2022.
A.A. acknowledges funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No. 834148). R.F.P. acknowledges financial support from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 721463 to the SUNDIAL ITN network. A.V. and J.F.-B. acknowledge support through the RAVET project by the grant PID2019-107427GB-C32 from the Spanish Ministry of Science, Innovation and Universities (MCIU), and through the IAC project TRACES which is partially supported through the state budget and the regional budget of the Consejería de Economía, Industria, Comercio y Conocimiento of the Canary Islands Autonomous Community. P.C. acknowledges support from Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) under grant 310041/2018-0 and from Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) process number 2018/05392-8. P.S.B. acknowledges the financial support from the Spanish National Plan for Scientific and Technical Research and Innovation, through the grant PID2019107427GB-C31. L.M. thanks FAPESP (grant 2018/26381-4) and CNPQ (grant 306359/2018-9) for partial funding of this research.

Uncontrolled Keywords:Parsec evolutionary tracks; Early-type galaxies; Giant branch phase; Tp-agb stars; 2.5 mu-m; Empirical calibration; Caii triplet; Effective temperatures; Globular-clusters; Carbon stars
Subjects:Sciences > Physics > Astrophysics
ID Code:75086
Deposited On:17 Oct 2022 17:04
Last Modified:18 Oct 2022 09:59

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