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Four annular structures in a protostellar disk less than 500,000 years old

Abstract

Annular structures (rings and gaps) in disks around pre-main-sequence stars have been detected in abundance towards class II protostellar objects that are approximately 1,000,000 years old1. These structures are often interpreted as evidence of planet formation1,2,3, with planetary-mass bodies carving rings and gaps in the disk4. This implies that planet formation may already be underway in even younger disks in the class I phase, when the protostar is still embedded in a larger-scale dense envelope of gas and dust5. Only within the past decade have detailed properties of disks in the earliest star-forming phases been observed6,7. Here we report 1.3-millimetre dust emission observations with a resolution of five astronomical units that show four annular substructures in the disk of the young (less than 500,000 years old)8 protostar IRS 63. IRS 63 is a single class I source located in the nearby Ophiuchus molecular cloud at a distance of 144 parsecs9, and is one of the brightest class I protostars at millimetre wavelengths. IRS 63 also has a relatively large disk compared to other young disks (greater than 50 astronomical units)10. Multiple annular substructures observed towards disks at young ages can act as an early foothold for dust-grain growth, which is a prerequisite of planet formation. Whether or not planets already exist in the disk of IRS 63, it is clear that the planet-formation process begins in the initial protostellar phases, earlier than predicted by current planet-formation theories11.

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Fig. 1: Enhanced-contrast image of the dust annular substructures around the class I protostar IRS 63.
Fig. 2: Radiative-transfer modelling reveals dust annular substructures not explained by a smooth disk.
Fig. 3: Ring positions and widths are measured from the radial profile of the residuals.
Fig. 4: Gap positions and widths are measured from the radial profile of the residuals.

Data availability

This paper makes use of ALMA data with the project code: ADS/JAO.ALMA#2015.1.01512.S. The archival data are available at http://almascience.eso.org/aq/ by querying the project code. The final calibrated version of the data analysed in this work is available from the Harvard Dataverse at https://doi.org/10.7910/DVN/LPVDSF. Other material in this work is available from the corresponding author on reasonable request58.

Code availability

The radiative-transfer modelling makes use of RADMC-3D, which is publicly available at http://www.ita.uni-heidelberg.de/~dullemond/software/radmc-3d/. The radiative-transfer modelling also uses the Pandora framework for the setup of and interfacing with RADMC-3D; Pandora is not open source and is available upon request. The MCMC modelling uses emcee, which is publicly available at https://emcee.readthedocs.io/en/stable/.

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Acknowledgements

ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada), MOST and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO and NAOJ. D.M.S.-C., A.S., J.E.P. and P.C. are grateful for support from the Max Planck Society. L.W.L. acknowledges support from NSF AST-1910364. Z.-Y.L. is supported in part by NASA 80NSSC18K1095 and NSF AST-1910106. This research made use of Astropy, a community-developed core Python package for astronomy.

Author information

Authors and Affiliations

Authors

Contributions

D.M.S.-C. led the observing proposal and project, led the analysis, reduced the ALMA data, and wrote the manuscript. A.S. performed the radiative-transfer modelling. J.E.P. performed the MCMC modelling. I.W.S., M.F.-L., L.W.L., Z.-Y.L., L.G.M., W.K. and R.J.H. contributed to the ALMA proposal. P.C. provided discussion and interpretation of the results. All authors discussed the results and implications, and commented on the manuscript.

Corresponding author

Correspondence to Dominique M. Segura-Cox.

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Competing interests

The authors declare no competing interests.

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Peer review information Nature thanks Jonathan Williams and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Asymmetry remains after re-centring the best radiative-transfer model.

a, The residual of the data minus the best radiative-transfer model, which had a centroid set to the Gaussian fit centre (same as Fig. 2c). b, The residuals of the best radiative-transfer model with a shifted centroid from minimizing the r.m.s. of the data minus model residuals. The asymmetry to the northwest portion of the disk is clear in both cases.

Extended Data Fig. 2 Posterior distributions of the analytic disk model parameters.

From left to right, the parameters are: normalization factor Σc, surface density gradient γ, characteristic radius Rc, the coordinates of the centroid of the fit x0 and y0, disk position angle PA and disk inclination angle IA.

Extended Data Fig. 3 A geometrically flat analytic model shows asymmetry in the residuals.

a, The original dust continuum data (same as Fig. 2a). b, The image of the flat analytic model, generated from the median parameter values resulting from the MCMC fit. c, The residuals of the observed data minus the analytic model. Again, here the annular substructures and the asymmetry with excess emission to the northwest are seen.

Extended Data Fig. 4 Position–intensity cuts of the dust continuum image centred at the position of the peak intensity.

The centroid is (α(2000), δ(2000)) = (16 h 31 m 35.6577 s, −24° 01′ 29.897″). ac, The cuts are taken at position angles of 150.0° or along the minor axis (a), of 60.0° or along the minor axis (b), and of 105.0° or along a cut from the southeast to northwest (c). d, The orientation of these cuts across the disk are shown in blue, orange and green, corresponding to ac, respectively. The radii in ac are deprojected assuming a disk inclination angle of 45.0° and are measured starting from the centroid outwards. The grey shaded areas represent the resolution of the observations, and the black horizontal lines show the 1σ noise level of 18.4 μJy per beam. We plot the radial intensities along either side of the centroid for each cut (solid and dashed lines). The 105.0° cut in c, along the southeast to northwest direction, shows the highest difference in intensities on either side of the centroid, and is consistent with the asymmetric and excess emission to the northwest previously seen in the residuals from the disk models.

Extended Data Fig. 5 Position–intensity cuts of the dust continuum image centred at the Gaussian fit position.

As in Extended Data Fig. 4, with a centroid of (α(2000), δ(2000)) = (16 h 31 m 35.6572 s, −24° 01′ 29.896″).

Extended Data Fig. 6 Position–intensity cuts of the dust continuum image centred at the centre determined from the MCMC fit to the analytic model.

As in Extended Data Fig. 4, with a centroid of (α(2000), δ(2000)) = 16 h 31 m 35.6575 s, −24° 01′ 29.901″.

Extended Data Fig. 7 Radial properties derived from observations.

ac, The radial profiles of the in-band spectral index (αa), the optical depth (τb) and the temperature (Tc) derived from the observational data. The grey shaded area represents the resolution of the observations, and the vertical grey dashed and dotted lines show the positions of the bright annular substructures R1 and R2 and dark annular substructures G1 and G2. For the spectral index the light-blue ribbon represents the local standard deviation of each bin, and the horizontal dashed grey line shows the α = 2 blackbody Rayleigh–Jeans limit. Optical depth is determined from a greybody fit to the intensity profile of the two in-band wavelengths. The temperature profile is determined from the greybody fit at radii where τ > 3 (solid blue line), and extrapolated to larger radii, r, as an inverse square-root law (dot–dash black line). For optical depth and temperature, the light-blue ribbons reflect the 10% amplitude uncertainty of the observations. The orange shaded region shows the location of the CO snowline based on dust temperature, reflecting the range of gas densities used to compute the condensation temperature.

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Segura-Cox, D.M., Schmiedeke, A., Pineda, J.E. et al. Four annular structures in a protostellar disk less than 500,000 years old. Nature 586, 228–231 (2020). https://doi.org/10.1038/s41586-020-2779-6

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