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In situ spheroid formation in distant submillimetre-bright galaxies

Nature volume 636, pages 69–74 (2024)Cite this article

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Abstract

Most stars in today’s Universe reside within spheroids, which are bulges of spiral galaxies and elliptical galaxies1,2. Their formation is still an unsolved problem3,4,5. Infrared/submillimetre-bright galaxies at high redshifts6 have long been suspected to be related to spheroid formation7,8,9,10,11,12. Proving this connection has been hampered so far by heavy dust obscuration when focusing on their stellar emission13,14,15 or by methodologies and limited signal-to-noise ratios when looking at submillimetre wavelengths16,17. Here we show that spheroids are directly generated by star formation within the cores of highly luminous starburst galaxies in the distant Universe. This follows from the ALMA submillimetre surface brightness profiles, which deviate substantially from those of exponential disks, and from the skewed-high axis-ratio distribution. Most of these galaxies are fully triaxial rather than flat disks: the ratio of the shortest to the longest of their three axes is half, on average, and increases with spatial compactness. These observations, supported by simulations, reveal a cosmologically relevant pathway for in situ spheroid formation through starbursts that is probably preferentially triggered by interactions (and mergers) acting on galaxies fed by non-coplanar gas accretion streams.

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Fig. 1: Physical properties of submm-bright galaxies, measured from fitting Spergel light profiles to the visibilities.
Fig. 2: Observed and 3D intrinsic axis ratios for ALMA submm-bright galaxies.
Fig. 3: Classification of intrinsic galaxy shapes.
Fig. 4: Examples of JWST cut-out images for our sample of galaxies.

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Data availability

The A3COSMOS submm imaging data are publicly available at https://sites.google.com/view/a3cosmos. The COSMOS2020 catalogues are available from Institut d’Astrophysique de Paris (https://cosmos2020.calet.org) and the COSMOS super-deblended photometry catalogue is published at https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/864/56.

Code availability

The ALMA submm data were reduced using CASA (https://casa.nrao.edu) and the MAPPING procedure of GILDAS (https://iram.fr/IRAMFR/GILDAS/).

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Acknowledgements

Q.-H.T. acknowledges the support by the China Scholarship Council (CSC) and the National Natural Science Foundation of China (NSFC), grant no. 12033004. S.A. gratefully acknowledges the Collaborative Research Center 1601 (SFB 1601 sub-project C2) financed by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 500700252. D.L. acknowledges the support from the Strategic Priority Research Program of Chinese Academy of Sciences, grant no. XDB0800401.

Author information

Authors and Affiliations

  1. Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, People’s Republic of China

    Qing-Hua Tan, Shao-Bo Zhang & Daizhong Liu

  2. Université Paris-Saclay, Université Paris Cité, CEA, CNRS, AIM, Gif-sur-Yvette, France

    Qing-Hua Tan, Emanuele Daddi, Benjamin Magnelli, Camila A. Correa, Frédéric Bournaud, David Elbaz & Carlos Gómez-Guijarro

  3. Argelander-Institut für Astronomie, Universität Bonn, Bonn, Germany

    Sylvia Adscheid

  4. Kavli Institute for the Physics and Mathematics of the Universe, The University of Tokyo, Kashiwa, Japan

    Boris S. Kalita, Zhaoxuan Liu & John D. Silverman

  5. Center for Data-Driven Discovery, Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Japan

    Boris S. Kalita, Zhaoxuan Liu & John D. Silverman

  6. Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing, People’s Republic of China

    Boris S. Kalita

  7. Department of Astronomy, School of Science, The University of Tokyo, Bunkyo, Japan

    Zhaoxuan Liu & John D. Silverman

  8. Institut de Radioastronomie Millimétrique, Saint-Martin-d’Hères, France

    Jérôme Pety

  9. LERMA, Observatoire de Paris, PSL Research University, CNRS, Sorbonne Universités, Paris, France

    Jérôme Pety

  10. School of Physics and Astronomy, University of Southampton, Southampton, UK

    Annagrazia Puglisi

  11. Center for Extragalactic Astronomy, Department of Physics, Durham University, Durham, UK

    Annagrazia Puglisi

  12. Max-Planck-Institut für Astronomie, Heidelberg, Germany

    Eva Schinnerer

  13. Center for Astrophysical Sciences, Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD, USA

    John D. Silverman

  14. European Southern Observatory, Garching bei Munchen, Germany

    Francesco Valentino

  15. Cosmic Dawn Center (DAWN), Copenhagen, Denmark

    Francesco Valentino

Authors
  1. Qing-Hua Tan
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  2. Emanuele Daddi
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  3. Benjamin Magnelli
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  4. Camila A. Correa
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  7. Shao-Bo Zhang
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  11. Daizhong Liu
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  17. Francesco Valentino
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Contributions

Q.-H.T. and E.D. developed the initial idea and led the analysis and the writing of this manuscript. B.M., S.A. and D.L. led the processing of the ALMA data. F.B. and C.A.C. led the hydrodynamical simulations and the analysis of EAGLE simulations of galaxy mergers, respectively. S.-B.Z. contributed to the computation of triaxial modelling. All authors contributed to the development of the analysis and/or the interpretation of the results.

Corresponding authors

Correspondence to Qing-Hua Tan or Emanuele Daddi.

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The authors declare no competing interests.

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Nature thanks Claudia Maraston and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Sample of ALMA submm-bright galaxies in the SFR–M⋆–z plane.

The solid and dashed black lines represent the positions of the main sequence at a common redshift (from left to right: z = 1.5, 2.5 and 4.0) and the associated 1σ dispersion given by ref. 85. The dotted red line shows the main sequence threshold above which galaxies are classified as starbursts (SFR/SFRMS > 4, ΔMS = 0.6 dex). We note that the values of SFR shown in each panel were scaled to a common redshift zbin by multiplying the actual SFR by a factor of \({{\rm{SFR}}}_{{\rm{MS}}}^{{z}_{{\rm{bin}}}}/{{\rm{SFR}}}_{{\rm{MS}}}^{z}\), to maintain the relative position of each galaxy with respect to the main sequence at its redshift. The vertical and horizontal bars indicate the median uncertainties of M⋆ and SFR, respectively.

Extended Data Fig. 2 Examples of the best-fit results of the Spergel profile fitting for our sample of galaxies on the uv-plane.

From left to right, we show the dirty image (natural weighting), source model convolved with the dirty beam, residuals after subtracting the source model and the normalized visibility amplitudes as a function of uv-distance. Contours start at ±3σ and increase by a factor of 1.5. The black crosses mark the centres of submm emission from sources derived from Spergel model fitting and the source name and the S/Nbeam of the data are indicated in the left panels. The ALMA beam is shown in the bottom-left corner of the left panels. Solid red curves in the right panels represent the best fit of Spergel modelling to the uv-data. For comparison, an exponential (Sérsic n = 1) model is overlaid by a dashed black curve. Error bars show the statistical noise on the average amplitude in each bin. The reduced chi-squared values calculated for the best fit of Spergel modelling (\({\chi }_{\nu ,{\rm{Spergel}}}^{2}\)) and n = 1 profile fit (\({\chi }_{\nu ,n=1}^{2}\)), along with a degree of confidence (P(n = 1)) by which the n = 1 solution can be rejected, are reported in each panel.

Extended Data Fig. 3 Histograms showing the distribution of Spergel index ν measured for subsamples of galaxies.

a, ΣSFR-compact galaxies. b, ΣSFR-extended galaxies. The blue and olive curves represent the intrinsic and best-fit distributions of ν, respectively. The vertical dashed lines indicate the ν = 0 threshold above which the galaxies are classified as pure disks. The error bar in each bin corresponds to the 1σ Poisson error.

Extended Data Fig. 4 Relative precision in the measurement of Spergel index ν and apparent axis ratio q.

a, The uncertainty σν is a measure of the accuracy of the recovered ν in Monte Carlo simulation, evaluated as the MAD of the data around the true value (σ = 1.48 × MAD). The dashed line represents the best-fit linear relationship between σν and ν and the shaded region indicates the 1σ confidence interval. b, Similar to panel a but showing the uncertainty in q measurement.

Extended Data Fig. 5 Corner plots showing the projections of the posterior probability distributions of the fitted parameters using a MCMC analysis.

Left, probability distribution of the parameters in a two-Gaussian model of the Spergel index ν distribution. Right, geometric parameter estimation for the triaxial model. a,b, The full sample. c,d, A subsample of ΣSFR-compact galaxies. e,f, A subsample of ΣSFR-extended galaxies. The best-fit values are marked as red crosses and dotted red lines and listed at the top of the histograms, with uncertainties computed as 1σ standard deviation (dotted grey lines), using the posterior probability as weights.

Extended Data Fig. 6 Distribution of measured parameters for the full ALMA sample galaxies.

a, Axis ratio q versus rest-frame wavelength λrest. b, Spergel index ν versus S/Nbeam. c, q versus S/Nbeam. The red squares in panel a indicate the median values of q in different wavelength bins, whereas those in panels b and c represent the median and mean values of ν and q in different S/Nbeam bins, respectively. The vertical and horizontal bars indicate the error on the average and bin width, respectively. The blue crosses in panel c represent the intrinsic distribution of q, derived from the best fit for the whole sample, perturbed by noise. The noise is assumed to be Gaussian, with the standard deviation estimated as the error on q measured at the corresponding S/Nbeam bins, with average values of 0.19, 0.16 and 0.08, respectively. The good agreement between the model and data suggests that the slight decrease in q at lower S/N levels can be attributed to the higher levels of noise observed.

Extended Data Fig. 7 Results from triaxial modelling for the subsamples of galaxies split by flux density and beam size.

The median flux density at band 7 and the median beam size for the full sample are \({7.8}_{-4.7}^{+3.6}\,{\rm{mJy}}\) and \(0.5{1}_{-0.31}^{+0.39}\,{\rm{arcsec}}\) (uncertainties are interquartile range), respectively. a,b, A subsample of galaxies with flux brighter than the median value. The ⟨B/A⟩ and ⟨C/A⟩ are 0.88 ± 0.06 and 0.50 ± 0.04, respectively. c,d, A subsample of galaxies with flux fainter than the median value. The ⟨B/A⟩ and ⟨C/A⟩ are 0.89 ± 0.07 and 0.51 ± 0.05, respectively. e,f, A subsample of galaxies with beam size larger than the median value. The ⟨B/A⟩ and ⟨C/A⟩ are 0.87 ± 0.07 and 0.49 ± 0.04, respectively. g,h, A subsample of galaxies with beam size smaller than the median value. The ⟨B/A⟩ and ⟨C/A⟩ are 0.90 ± 0.06 and 0.52 ± 0.04, respectively.

Extended Data Fig. 8 Reanalysis of sample galaxies of submm galaxies measured with Re/ΔRe > 3 in ref. 16.

a,b, Distribution of Spergel ν and axis ratio q measured using Spergel modelling for the galaxies in ref. 16, compared with the subsample of ΣSFR-extended galaxies in our sample. c,d, Comparison of Sérsic index n and q measurements between Spergel fitting and those derived from ref. 16. Data points are colour-coded by S/Nbeam. The vertical and horizontal bars indicate the median uncertainties derived from Spergel fitting and those reported in ref. 16, respectively. The dashed lines indicate the 1:1 line. e,f, Similar to Fig. 2 but showing the triaxial modelling results for the sample galaxies in ref. 16 with parameters fitted using Spergel profile. The measured ⟨B/A⟩ and ⟨C/A⟩ are 0.85 ± 0.08 and 0.47 ± 0.05, respectively.

Extended Data Fig. 9 Compact spheroid-like gas distribution from hydro-simulations of major mergers.

Reanalysis of recent very-high-resolution simulations of mergers of turbulent clumpy disks42. a, Maps (2 × 2 kpc) of the central gas in three different mergers, showing the flattest projection for these systems observed at 12 Myr from coalescence, that is, these systems are 3D spheroidal structures, not face-on disks. b,c, Evolution of SFR surface density and disk thickness C/A over time after merger coalescence for three merger orbits, respectively. Panel b distinguishes the nuclear regions of the mergers in which submm emission is bright from the wider outskirts. Time analysis shows that the spheroidal shape of the gas can be maintained over approximately 30–50 Myr. This is compatible with the inferred timescales for the submm-bright bursts based on observations. After the intensely star-forming spheroid-like star formation, lacking further turbulent energy injection back into the system, the residual gas flattens into a disk (panel c). However, the earlier phase led to the formation of a stellar spheroid.

Extended Data Fig. 10 Merger history of submm galaxies using EAGLE cosmological simulation.

a, Stellar mass and redshift distribution of the submm galaxy sample (orange symbols). b, SFR of the submm sample (shown by orange symbols) relative to the star-forming main sequence of the simulations (solid blue line; all trends rescaled in star formation to z = 1 for clarity). Dark grey shaded regions mark the 16th–84th percentiles of the relation, whereas light grey shaded regions indicate the 5th–95th percentiles. Individual SFRs of the submm sample have been renormalized (see text). c, Fraction of submm galaxies that underwent major (blue symbols) or minor (grey symbols) mergers. The panel shows that major mergers do not seem to dominate the assembly of submm-bright galaxies. d, Gas accretion rates of galaxies before they became submm bright. The accretion includes diffuse gas and minor and (rare) major mergers. Blue symbols indicate the median rates of a control sample, consisting of galaxies with stellar masses within ±0.2 dex of the median stellar mass of the submm galaxies. This panel indicates that the submm event was probably triggered by a high rate of gas inflow. e, Disk-to-total (D/T) mass ratio of all galaxies at z = 0. Orange symbols highlight the D/T ratio of the z = 0 descendants of the submm galaxies. f, Similar to panel e, stellar [α/Fe] (represented by [O/Fe]) of all galaxies at z = 0, as well as of the submm descendants. Panels e and f indicate that submm galaxies evolve into elliptical galaxies with typical [α/Fe] element ratios.

Extended Data Table 1 Physical properties and best-fitting triaxial model parameters
Full size table
Extended Data Table 2 Full galaxy sample
Full size table

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Tan, QH., Daddi, E., Magnelli, B. et al. In situ spheroid formation in distant submillimetre-bright galaxies. Nature 636, 69–74 (2024). https://doi.org/10.1038/s41586-024-08201-6

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