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Sub one per cent mass fractions of young stars in red massive galaxies

Nature Astronomy volume 4, pages 252–259 (2020)Cite this article

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Abstract

Early-type galaxies are considered to be the end products of massive galaxy formation1. Optical spectroscopic studies reveal that massive early-type galaxies formed the bulk of their stars over short timescales (\(\lesssim\)1 Gyr) and at high redshift (z \(\gtrsim\) 2), followed by passive evolution to the present2. However, their optical spectra are unable to constrain small episodes of recent star formation, since they are dominated by old stars. Fortunately, this problem can be tackled in the ultraviolet range. While recent studies that make use of ultraviolet absorption lines have suggested the presence of young stars in a few early-type galaxies3, the age and mass fractions of young stars and their dependence on galaxy mass are unknown. Here we report a detailed study of these young stellar populations, from high-quality stacked spectra of 28,663 galaxies from the BOSS survey4, analysing optical and ultraviolet absorption lines simultaneously. We find that residual star formation is ubiquitous in massive early-type galaxies, measuring average mass fractions of 0.5% in young stars in the last 2 Gyr of their evolution. This fraction shows a decreasing trend with galaxy stellar mass, consistent with a downsizing scenario5. We also find that synthetic galaxies from state-of-the-art cosmological numerical simulations6 substantially overproduce both intermediate and young stellar populations. Therefore, our results pose stringent constraints on numerical simulations of galaxy formation6,7.

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Data availability

The observational data used in this study are derived from the SDSS-III DR12 Survey Science Archive Server (https://dr12.sdss.org/advancedSearch). The stacked spectrum data analysed during the current study that support the plots within this paper are available as Source Data. The EAGLE simulation data are publicly available (http://eagle.strw.leidenuniv.nl/) and the simulated spectra of the EAGLE galaxies analysed in this manuscript are available from the authors on reasonable request. The E-MILES SSP models are publicly available at the MILES website (http://miles.iac.es).

Code availability

To measure line-strength indices of the spectra we use our own code based on the publicly available indexf code from https://indexf.readthedocs.io/en/latest/index.html. The emcee package used to fit the observed line-strength indices is available at https://emcee.readthedocs.io/en/stable/. Codes generated in this study are not publicly available since they can be reproduced following the Methods description but are available from the corresponding author on reasonable request.

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Acknowledgements

Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation and the US Department of Energy Office of Science. The SDSS-III website is http://www.sdss3.org/. SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofísica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington and Yale University. We thank G. Bruzual and S. Charlot for kindly providing us with their new version of stellar population models extended to the ultraviolet spectral range to test how results change when using other SSP models. Parts of this research have been funded by the Spanish Ministry of Science, Innovation and Universities (MCIU) through research project SEV-2015-0548-16-4 and predoctoral contract BES-2016-078409. N.S.R., M.A.B., A.V. and I.F. acknowledge support from grant AYA2016-77237-C3-1-P from the MCIU. F.L.B. acknowledges financial support from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement 721463 to the SUNDIAL ITN network. M.A.B. and A.N. acknowledge the Severo Ochoa excellence scheme SEV-2015-0548. C.D.V. acknowledges financial support from MCIU through grants AYA2014-58308 and RYC-2015-1807.

Author information

Authors and Affiliations

  1. Instituto de Astrofísica de Canarias, La Laguna, Tenerife, Spain

    Núria Salvador-Rusiñol, Alexandre Vazdekis, Michael A. Beasley, Ignacio Ferreras, Andrea Negri & Claudio Dalla Vecchia

  2. Departmento de Astrofísica, Universidad de La Laguna, La Laguna, Tenerife, Spain

    Núria Salvador-Rusiñol, Alexandre Vazdekis, Michael A. Beasley, Ignacio Ferreras, Andrea Negri & Claudio Dalla Vecchia

  3. INAF Osservatorio Astronomico di Capodimonte, Naples, Italy

    Francesco La Barbera

  4. MSSL, University College London, Dorking, Surrey, UK

    Ignacio Ferreras

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  1. Núria Salvador-Rusiñol
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Contributions

N.S.R. led the analysis and wrote the text. A.V., M.A.B. and F.L.B. developed the idea and supervised the work. I.F. prepared the BOSS data for analysis. F.L.B and N.S.R. wrote code. N.S.R., A.V., M.A.B., F.L.B. and I.F. interpreted and analysed the results. A.N. and C.D.V. prepared the simulation data. All authors discussed the results and edited the manuscript.

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Correspondence to Núria Salvador-Rusiñol.

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The authors declare no competing interests.

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Peer review information Nature Astronomy thanks Camilla Pacifici and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Data selection criteria.

Selection of our BOSS galaxy sample as a function of velocity dispersion and redshift. The plot illustrates the number density in logarithmic scale of available BOSS spectra with SNR > 7 in the SDSS-r band and (g-i) > 2.35. We select BOSS galaxies with redshift \(0.35{\le }{{\rm{z}}}\le0.6\), and velocity dispersion between 220 and 340 km s\({}^{-1}\). Lowest density regions show individual galaxies with dark blue.

Extended Data Fig. 2 BOSS stacked spectra.

Panel a) shows our stacked spectra from the BOSS survey, colour-coded with respect to the stellar velocity dispersion range labelled on the top left of each spectrum. The spectra have been shifted vertically for ease of visualization. Panel b) represents the signal-to-noise ratio, following the same colour scheme.

Extended Data Fig. 3 Probability distribution functions from MCMC.

Probability distribution functions of an intermediate velocity dispersion stack (250–260 km/s) corresponding to the model parameters obtained with the 2SSPs approach. From top to bottom: age and metallicity for the old component, and age and mass fraction of the young component. The panels show the marginalized PDF over each single parameter over the other parameters. Contours show the two-dimensional \(1\sigma\), \(2\sigma\) and \(3\sigma\) confidence levels between all the parameters. The last panel of each row shows the median (blue solid line) and the 16 and 84 percentiles (dashed lines) for each PDF. Note the burst age–burst strength degeneracy found between the age and the fraction of the young component, for which a smaller burst can be produced more recently.

Extended Data Fig. 4 NUV and optical line-strength indices.

The panels show the behaviour of the NUV and optical SSP model indices as a function of age, for two different metallicities ([M/H]=0.0, solid lines; [M/H]=+0.22, dashed lines). The black dots correspond to the observed measurements of BOSS stacked spectra and their error bars show the 1𝜎 uncertainty on the measurements. Red stars indicate the best fitting 2SSPs model predictions. Blue triangles show the index values predicted by the best fitting 1SSP+cSFR model. Note that the discrepancy between SSP model predictions and data increases towards bluer indices. The indices shown exclude those in Figure 1.

Extended Data Fig. 5 2SSPs best index fit spectrum.

Panel a) shows the stacked spectrum with the highest velocity dispersion range (thick black line). Overplotted is the 2SSPs model (thin black) that best fits the 14 indices shown in Figure 1 and in Extended Data 4. The main purpose of this figure is to illustrate the relative effect of the young component as a function of wavelength but note it does not represent a full-spectrum fit. The 2SSPs model can be split into the young (65 Myr) component (blue dashed) which contributes a 0.09% mass fraction, and the old (9.38 Gyr) dominant population (red dotted). Panel b) shows the ratio between the 2SSPs best fit model with the stacked spectrum (black) and with a pure old SSP model of 9.38 Gyr (orange). The inset subplot shows the flux ratio of the dashed box in more detail.

Supplementary information

Supplementary Information

Supplementary Tables 1 and 2.

Source data

Source Data for Extended Data Fig. 2

BOSS stacked spectra data sorted by the velocity dispersion of each bin, smoothed at 340 km s−1.

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Salvador-Rusiñol, N., Vazdekis, A., La Barbera, F. et al. Sub one per cent mass fractions of young stars in red massive galaxies. Nat Astron 4, 252–259 (2020). https://doi.org/10.1038/s41550-019-0955-0

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