Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

A tidal disruption event coincident with a high-energy neutrino

Nature Astronomy volume 5, pages 510–518 (2021)Cite this article

Subjects

Abstract

Cosmic neutrinos provide a unique window into the otherwise hidden mechanism of particle acceleration in astrophysical objects. The IceCube Collaboration recently reported the likely association of one high-energy neutrino with a flare from the relativistic jet of an active galaxy pointed towards the Earth. However a combined analysis of many similar active galaxies revealed no excess from the broader population, leaving the vast majority of the cosmic neutrino flux unexplained. Here we present the likely association of a radio-emitting tidal disruption event, AT2019dsg, with a second high-energy neutrino. AT2019dsg was identified as part of our systematic search for optical counterparts to high-energy neutrinos with the Zwicky Transient Facility. The probability of finding any coincident radio-emitting tidal disruption event by chance is 0.5%, while the probability of finding one as bright in bolometric energy flux as AT2019dsg is 0.2%. Our electromagnetic observations can be explained through a multizone model, with radio analysis revealing a central engine, embedded in a UV photosphere, that powers an extended synchrotron-emitting outflow. This provides an ideal site for petaelectronvolt neutrino production. Assuming that the association is genuine, our observations suggest that tidal disruption events with mildly relativistic outflows contribute to the cosmic neutrino flux.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Multiwavelength lightcurve of AT2019dsg.
Fig. 2: Synchrotron analysis of AT2019dsg.
Fig. 3: Diagram of the three emission zones in AT2019dsg.

Similar content being viewed by others

Data availability

The data that support the plots within this paper and other findings of this study are available from https://github.com/robertdstein/at2019dsg, and at https://doi.org/10.5281/zenodo.4308124.

Code availability

Python scripts used to perform significant calculations, and to reproduce all figures, are available from https://github.com/robertdstein/at2019dsg, and at https://doi.org/10.5281/zenodo.4308124.

References

  1. Aartsen, M. G. et al. The IceCube Neutrino Observatory: instrumentation and online systems. J. Instrum. 12, P03012 (2017).

    Article  Google Scholar 

  2. Stein, R. IceCube-191001A—IceCube observation of a high-energy neutrino candidate event. GCN Circ. 25913 (2019).

  3. Bellm, E. C. et al. The Zwicky Transient Facility: system overview, performance, and first results. Publ. Astron. Soc. Pac. 131, 018002 (2019).

    Article  ADS  Google Scholar 

  4. Kowalski, M. & Mohr, A. Detecting neutrino transients with optical follow-up observations. Astropart. Phys. 27, 533–538 (2007).

    Article  ADS  Google Scholar 

  5. Farrar, G. R. & Gruzinov, A. Giant AGN flares and cosmic ray bursts. Astrophys. J. 693, 329–332 (2009).

    Article  ADS  Google Scholar 

  6. Dai, L. & Fang, K. Can tidal disruption events produce the IceCube neutrinos? Mon. Not. R. Astron. Soc. 469, 1354–1359 (2017).

    Article  ADS  Google Scholar 

  7. Hayasaki, K. & Yamazaki, R. Neutrino emissions from tidal disruption remnants. Astrophys. J. 886, 114 (2019).

    Article  ADS  Google Scholar 

  8. Farrar, G. R. & Piran, T. Tidal disruption jets as the source of Ultra-High Energy Cosmic Rays. Preprint at https://arxiv.org/abs/1411.0704 (2014).

  9. Senno, N., Murase, K. & Mészáros, P. High-energy neutrino flares from X-ray bright and dark tidal disruption events. Astrophys. J. 838, 3 (2017).

    Article  ADS  Google Scholar 

  10. Wang, X. Y. & Liu, R. Y. Tidal disruption jets of supermassive black holes as hidden sources of cosmic rays: explaining the IceCube TeV–PeV neutrinos. Phys. Rev. D 93, 083005 (2016).

    Article  ADS  Google Scholar 

  11. Lunardini, C. & Winter, W. High energy neutrinos from the tidal disruption of stars. Phys. Rev. D 95, 123001 (2017).

    Article  ADS  Google Scholar 

  12. Stein, R., Franckowiak, A., Necker, J., Gezari, S. & Velzen, S. V. Candidate counterparts to IceCube-191001A with ZTF. Astron. Telegr. 13160 (2019).

  13. Graham, M. J. et al. The Zwicky Transient Facility: science objectives. Publ. Astron. Soc. Pac. 131, 078001 (2019).

    Article  ADS  Google Scholar 

  14. Nordin, J. et al. TNS Astronomical Transient Report 33340 (2019).

  15. Nicholl, M. et al. ePESSTO+ classification of optical transients. Astron. Telegr. 12752 (2019).

  16. van Velzen, S. et al. Seventeen tidal disruption events from the first half of ZTF survey observations: entering a new era of population studies. Preprint at https://arxiv.org/abs/2001.01409 (2020).

  17. van Velzen, S. et al. Late-time UV observations of tidal disruption flares reveal unobscured, compact accretion disks. Astrophys. J. 878, 82 (2019).

    Article  ADS  Google Scholar 

  18. Mummery, A. & Balbus, S. A. The spectral evolution of disc dominated tidal disruption events. Mon. Not. R. Astron. Soc. 492, 5655–5674 (2020).

    Article  ADS  Google Scholar 

  19. McConnell, N. J. & Ma, C. P. Revisiting the scaling relations of black hole masses and host galaxy properties. Astrophys. J. 764, 184 (2013).

    Article  ADS  Google Scholar 

  20. Auchettl, K., Guillochon, J. & Ramirez-Ruiz, E. New physical insights about tidal disruption events from a comprehensive observational inventory at X-ray wavelengths. Astrophys. J. 838, 149 (2017).

    Article  ADS  Google Scholar 

  21. Wevers, T. et al. Black hole masses of tidal disruption event host galaxies II. Mon. Not. R. Astron. Soc. 487, 4136–4152 (2019).

    Article  ADS  Google Scholar 

  22. van Velzen, S. et al. The first tidal disruption flare in ZTF: from photometric selection to multi-wavelength characterization. Astrophys. J. 872, 198 (2019).

    Article  ADS  Google Scholar 

  23. Morlino, G. & Caprioli, D. Strong evidence for hadron acceleration in Tycho’s supernova remnant. Astron. Astrophys. 538, A81 (2012).

    Article  ADS  Google Scholar 

  24. Eftekhari, T., Berger, E., Zauderer, B. A., Margutti, R. & Alexander, K. D. Radio monitoring of the tidal disruption event Swift J164449.3+573451. III. Late-time jet energetics and a deviation from equipartition. Astrophys. J. 854, 86 (2018).

    Article  ADS  Google Scholar 

  25. Horesh, A. et al. An early and comprehensive millimetre and centimetre wave and X-ray study of SN 2011dh: a non-equipartition blast wave expanding into a massive stellar wind. Mon. Not. R. Astron. Soc. 436, 1258–1267 (2013).

    Article  ADS  Google Scholar 

  26. Barniol Duran, R., Nakar, E. & Piran, T. Radius constraints and minimal equipartition energy of relativistically moving synchrotron sources. Astrophys. J. 772, 78 (2013).

    Article  ADS  Google Scholar 

  27. Polatidis, A. G. & Conway, J. E. Proper motions in compact symmetric objects. Publ. Astron. Soc. Aust. 20, 69–74 (2003).

    Article  ADS  Google Scholar 

  28. Alexander, K. D., Berger, E., Guillochon, J., Zauderer, B. A. & Williams, P. K. G. Discovery of an outflow from radio observations of the tidal disruption event ASASSN-14li. Astrophys. J. Lett. 819, L25 (2016).

    Article  ADS  Google Scholar 

  29. Krolik, J., Piran, T., Svirski, G. & Cheng, R. M. ASASSN-14li: a model tidal disruption event. Astrophys. J. 827, 127 (2016).

    Article  ADS  Google Scholar 

  30. Pasham, D. R. & van Velzen, S. Discovery of a time lag between the soft X-ray and radio emission of the tidal disruption flare ASASSN-14li: evidence for linear disk–jet coupling. Astrophys. J. 856, 1 (2018).

    Article  ADS  Google Scholar 

  31. Strotjohann, N. L., Kowalski, M. & Franckowiak, A. Eddington bias for cosmic neutrino sources. Astron. Astrophys. 622, L9 (2019).

    Article  ADS  Google Scholar 

  32. Hillas, A. M. The origin of ultra-high-energy cosmic rays. Annu. Rev. Astron. Astrophys. 22, 425–444 (1984).

    Article  ADS  Google Scholar 

  33. IceCube Collaboration et al. Multimessenger observations of a flaring blazar coincident with high-energy neutrino IceCube-170922A. Science 361, eaat1378 (2018).

    Article  ADS  Google Scholar 

  34. Blaufuss, E., Kintscher, T., Lu, L. & Tung, C. F. The next generation of IceCube real-time neutrino alerts. In Proc. 36th International Cosmic Ray Conference (ICRC2019) 1021 (PoS, 2019).

  35. Murase, K., Guetta, D. & Ahlers, M. Hidden cosmic-ray accelerators as an origin of TeV–PeV cosmic neutrinos. Phys. Rev. Lett. 116, 071101 (2016).

    Article  ADS  Google Scholar 

  36. Stein, R. Search for neutrinos from populations of optical transients. In Proc. 36th International Cosmic Ray Conference (ICRC2019) 1016 (PoS, 2019).

  37. Coughlin, M. W. et al. 2900 square degree search for the optical counterpart of short gamma-ray burst GRB 180523B with the Zwicky Transient Facility. Publ. Astron. Soc. Pac. 131, 048001 (2019).

    Article  ADS  Google Scholar 

  38. Stein, R. IceCube-200107A: IceCube observation of a high-energy neutrino candidate event. GCN Circ. 26655 (2020).

  39. Masci, F. J. et al. The Zwicky Transient Facility: data processing, products, and archive. Publ. Astron. Soc. Pac. 131, 018003 (2019).

    Article  ADS  Google Scholar 

  40. Patterson, M. T. et al. The Zwicky Transient Facility Alert Distribution System. Publ. Astron. Soc. Pac. 131, 018001 (2019).

    Article  ADS  Google Scholar 

  41. Stein, R. & Reusch, S. robertdstein/ampel_followup_pipeline: V1.1 Release (Zenodo, 2020); https://doi.org/10.5281/zenodo.4048336

  42. Nordin, J. et al. Transient processing and analysis using AMPEL: alert management, photometry, and evaluation of light curves. Astron. Astrophys. 631, A147 (2019).

    Article  MathSciNet  Google Scholar 

  43. Mahabal, A. et al. Machine learning for the Zwicky Transient Facility. Publ. Astron. Soc. Pac. 131, 038002 (2019).

    Article  ADS  Google Scholar 

  44. Soumagnac, M. T. & Ofek, E. O. catsHTM: a tool for fast accessing and cross-matching large astronomical catalogs. Publ. Astron. Soc. Pac. 130, 075002 (2018).

    Article  ADS  Google Scholar 

  45. Gaia Collaboration et al. Gaia Data Release 2. Summary of the contents and survey properties. Astron. Astrophys. 616, A1 (2018).

    Article  Google Scholar 

  46. Tachibana, Y. & Miller, A. A. A morphological classification model to identify unresolved PanSTARRS1 sources: application in the ZTF real-time pipeline. Publ. Astron. Soc. Pac. 130, 128001 (2018).

    Article  ADS  Google Scholar 

  47. Chambers, K. C. et al. The Pan-STARRS1 Surveys. Preprint at https://arxiv.org/abs/1612.05560 (2016).

  48. Wright, E. L. et al. The Wide-field Infrared Survey Explorer (WISE): mission description and initial on-orbit performance. Astron. J. 140, 1868–1881 (2010).

    Article  ADS  Google Scholar 

  49. Aartsen, M. G. et al. Time-integrated neutrino source searches with 10 years of IceCube data. Phys. Rev. Lett. 124, 051103 (2020).

    Article  ADS  Google Scholar 

  50. Steele, I. A. et al. The Liverpool Telescope: performance and first results. Proc. SPIE 5489, https://doi.org/10.1117/12.551456 (2004).

  51. Blagorodnova, N. et al. The SED Machine: a robotic spectrograph for fast transient classification. Publ. Astron. Soc. Pac. 130, 035003 (2018).

    Article  ADS  Google Scholar 

  52. Rigault, M. et al. Fully automated integral field spectrograph pipeline for the SEDMachine: pysedm. Astron. Astrophys. 627, A115 (2019).

    Article  Google Scholar 

  53. Fremling, C. et al. PTF12os and iPTF13bvn. Two stripped-envelope supernovae from low-mass progenitors in NGC 5806. Astron. Astrophys. 593, A68 (2016).

    Article  Google Scholar 

  54. van Velzen, S. On the mass and luminosity functions of tidal disruption flares: rate suppression due to black hole event horizons. Astrophys. J. 852, 72 (2018).

    Article  ADS  Google Scholar 

  55. Roming, P. W. A. et al. The Swift Ultra-Violet/Optical Telescope. Space Sci. Rev. 120, 95–142 (2005).

    Article  ADS  Google Scholar 

  56. Gehrels, N. et al. The Swift Gamma-Ray Burst Mission. Astrophys. J. 611, 1005–1020 (2004).

    Article  ADS  Google Scholar 

  57. van Velzen, S., Mendez, A. J., Krolik, J. H. & Gorjian, V. Discovery of transient infrared emission from dust heated by stellar tidal disruption flares. Astrophys. J. 829, 19 (2016).

    Article  ADS  Google Scholar 

  58. Lu, W., Kumar, P. & Evans, N. J. Infrared emission from tidal disruption events—probing the pc-scale dust content around galactic nuclei. Mon. Not. R. Astron. Soc. 458, 575–581 (2016).

    Article  ADS  Google Scholar 

  59. Miller, J. S. & Stone, R. P. S. The Kast Double Spectrograph. Technical Report No. 66 (Lick Observatory, 1993).

  60. Oke, J. B. et al. The Keck Low-Resolution Imaging Spectrometer. Publ. Astron. Soc. Pac. 107, 375–385 (1995).

    Article  ADS  Google Scholar 

  61. Garcia-Rissmann, A. et al. An atlas of calcium triplet spectra of active galaxies. Mon. Not. R. Astron. Soc. 359, 765–780 (2005).

    Article  ADS  Google Scholar 

  62. Burrows, D. N. et al. The Swift X-Ray Telescope. Space Sci. Rev. 120, 165–195 (2005).

    Article  ADS  Google Scholar 

  63. Jansen, F. et al. XMM-Newton Observatory. I. The spacecraft and operations. Astron. Astrophys. 365, L1–L6 (2001).

    Article  ADS  Google Scholar 

  64. HI4PI Collaboration et al. HI4PI: a full-sky H i survey based on EBHIS and GASS. Astron. Astrophys. 594, A116 (2016).

  65. Arnaud, K. A. in Astronomical Data Analysis Software and Systems V (eds Jacoby, G. H. & Barnes, J.) 17 (Astronomical Society of the Pacific, 1996).

  66. Zwart, J. T. L. et al. The Arcminute Microkelvin Imager. Mon. Not. R. Astron. Soc. 391, 1545–1558 (2008).

    Article  ADS  Google Scholar 

  67. Hickish, J. et al. A digital correlator upgrade for the Arcminute MicroKelvin Imager. Mon. Not. R. Astron. Soc. 475, 5677–5687 (2018).

    Article  ADS  Google Scholar 

  68. Perrott, Y. C. et al. AMI galactic plane survey at 16 GHz—II. Full data release with extended coverage and improved processing. Mon. Not. R. Astron. Soc. 453, 1396–1403 (2015).

    Article  ADS  Google Scholar 

  69. McMullin, J. P., Waters, B., Schiebel, D., Young, W. & Golap, K. in Astronomical Data Analysis Software and Systems XVI (eds Shaw, R. A. et al.) 127 (Astronomical Society of the Pacific, 2007).

  70. Atwood, W. B. et al. The Large Area Telescope on the Fermi Gamma-ray Space Telescope mission. Astrophys. J. 697, 1071–1102 (2009).

    Article  ADS  Google Scholar 

  71. Wood, M. et al. Fermipy: an open-source Python package for analysis of Fermi-LAT Data. In Proc. 35th International Cosmic Ray Conference (ICRC2017) 824 (PoS, 2017).

  72. Garrappa, S. & Buson, S. Fermi-LAT gamma-ray observations of IceCube-191001A. GCN Circ. 25932 (2019).

  73. The Fermi-LAT collaboration. Fermi Large Area Telescope Fourth Source Catalog. Astrophys. J. Suppl. Ser. 247, 33 (2020).

  74. Pursimo, T. et al. The Micro-Arcsecond Scintillation-Induced Variability (MASIV) survey. III. Optical identifications and new redshifts. Astrophys. J. 767, 14 (2013).

    Article  ADS  Google Scholar 

  75. Garrappa, S., Buson, S. & Fermi-LAT Collaboration. Fermi-LAT gamma-ray observations of IceCube-191001A. GCN Circ. 25932 (2019).

  76. Diltz, C., Böttcher, M. & Fossati, G. Time dependent hadronic modeling of flat spectrum radio quasars. Astrophys. J. 802, 133 (2015).

    Article  ADS  Google Scholar 

  77. Gao, S., Fedynitch, A., Winter, W. & Pohl, M. Modelling the coincident observation of a high-energy neutrino and a bright blazar flare. Nat. Astron. 3, 88–92 (2019).

    Article  ADS  Google Scholar 

  78. Ayala, H. IceCube-191001A: HAWC follow-up. GCN Circ. 25936 (2019).

  79. van Velzen, S. et al. A radio jet from the optical and x-ray bright stellar tidal disruption flare ASASSN-14li. Science 351, 62–65 (2016).

    Article  ADS  Google Scholar 

  80. Foreman-Mackey, D., Hogg, D. W., Lang, D. & Goodman, J. emcee: the MCMC Hammer. Publ. Astron. Soc. Pac. 125, 306 (2013).

    Article  ADS  Google Scholar 

  81. Guillochon, J. et al. MOSFiT: Modular Open Source Fitter for Transients. Astrophys. J. Suppl. Ser. 236, 6 (2018).

    Article  ADS  Google Scholar 

  82. Granot, J. & van der Horst, A. J. Gamma-ray burst jets and their radio observations. Publ. Astron. Soc. Aust. 31, e008 (2014).

    Article  ADS  Google Scholar 

  83. Fong, W., Berger, E., Margutti, R. & Zauderer, B. A. A decade of short-duration gamma-ray burst broadband afterglows: energetics, circumburst densities, and jet opening angles. Astrophys. J. 815, 102 (2015).

    Article  ADS  Google Scholar 

Download references

Acknowledgements

We thank C. Lunardini, A. MacFadyen, B. Metzger, A. Mummery, A. Pizzuto, N. Stone, A. Taylor and W. Winter for discussions. We also thank the IceCube Collaboration for publishing high-energy neutrino alerts. We thank S. Digel, K. Fang, D. Horan, M. Kerr, V. Paliya and J. Racusin for feedback provided during a Fermi collaboration review. R.S. is grateful to NYU for facilitating a visit to develop this work. M.K. is grateful for the hospitality received from Columbia University and NYU during a sabbatical visit. This work was supported by the Initiative and Networking Fund of the Helmholtz Association through the Young Investigator Group programme (A.F.). S.v.V. is supported by the James Arthur Postdoctoral Fellowship. This research was partially supported by the Australian Government through the Australian Research Council’s Discovery Projects funding scheme (project DP200102471). The work of M.B. is supported through the South African Research Chair Initiative of the National Research Foundation and the Department of Science and Innovation of South Africa, under SARChI Chair grant no. 64789. Any opinion, finding and conclusion or recommendation expressed in this material is that of the authors and the NRF does not accept any liability in this regard. A.H. acknowledges support by the I-Core Program of the Planning and Budgeting Committee and the Israel Science Foundation. The UCSC transient team is supported in part by NSF grant AST-1518052, NASA/Swift grant 80NSSC19K1386, the Gordon & Betty Moore Foundation, the Heising-Simons Foundation and a fellowship from the David and Lucile Packard Foundation to R.J.F. V.Z.G. is a Moore–Sloan, WRF Innovation in Data Science and DIRAC Fellow. A.G.-Y.’s research is supported by the EU via ERC grant no. 725161, the ISF GW Excellence Center, an IMOS space infrastructure grant and BSF/Transformative and GIF grants, as well as the Benoziyo Endowment Fund for the Advancement of Science, the André Deloro Institute for Advanced Research in Space and Optics, the Veronika A. Rabl Physics Discretionary Fund, Paul and Tina Gardner, Yeda-Sela and the WIS-CIT joint research grant; A.G.-Y. is the recipient of the Helen and Martin Kimmel Award for Innovative Investigation. M.R. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 759194-USNAC). The work of D.S. was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. The work of S.R. was supported by the Helmholtz Weizmann Research School on Multimessenger Astronomy, funded through the Initiative and Networking Fund of the Helmholtz Association, DESY, the Weizmann Institute, the Humboldt University of Berlin and the University of Potsdam. This work is based on observations obtained with the Samuel Oschin telescope 48-inch and the 60-inch telescope at the Palomar Observatory as part of the ZTF project. ZTF is supported by the National Science Foundation under grant no. AST-1440341 and a collaboration including Caltech, IPAC, the Weizmann Institute for Science, the Oskar Klein Center at Stockholm University, the University of Maryland, the University of Washington, Deutsches Elektronen-Synchrotron and Humboldt University, Los Alamos National Laboratories, the TANGO Consortium of Taiwan, the University of Wisconsin at Milwaukee and Lawrence Berkeley National Laboratories. Operations are conducted by COO, IPAC and UW. SED Machine is based upon work supported by the National Science Foundation under grant no. 1106171. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. The MeerKAT telescope is operated by the South African Radio Astronomy Observatory, which is a facility of the National Research Foundation, an agency of the Department of Science and Innovation. The work was supported by the GROWTH project funded by the National Science Foundation Partnership in International Research and Education program under grant no. 1545949. GROWTH is a collaborative project between the California Institute of Technology (United States), Pomona College (United States), San Diego State University (United States), Los Alamos National Laboratory (United States), University of Maryland College Park (United States), University of Wisconsin at Milwaukee (United States), Tokyo Institute of Technology (Japan), National Central University (Taiwan), Indian Institute of Astrophysics (India), Inter-University Center for Astronomy and Astrophysics (India), Weizmann Institute of Science (Israel), The Oskar Klein Centre at Stockholm University (Sweden) and Humboldt University (Germany). The Liverpool Telescope is operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias with financial support from the UK Science and Technology Facilities Council. Research at Lick Observatory is partially supported by a gift from Google. The Fermi-LAT Collaboration acknowledges support for LAT development, operation and data analysis from NASA and DOE (United States), CEA/Irfu and IN2P3/CNRS (France), ASI and INFN (Italy), MEXT, KEK and JAXA (Japan) and the K.A. Wallenberg Foundation, the Swedish Research Council and the National Space Board (Sweden). Science analysis support in the operations phase from INAF (Italy) and CNES (France) is also acknowledged. This work was performed in part under DOE contract DE-AC02-76SF00515. IceCube Neutrino Observatory is a facility of the National Science Foundation operated at the US Amundsen–Scott South Pole Station under the US Antarctic Program.

Author information

Authors and Affiliations

  1. Deutsches Elektronen-Synchrotron DESY, Zeuthen, Germany

    Robert Stein, Marek Kowalski, Anna Franckowiak, Simone Garrappa, Jannis Necker, Simeon Reusch & Jakob van Santen

  2. Institut für Physik, Humboldt-Universität zu Berlin, Berlin, Germany

    Robert Stein, Marek Kowalski, Anna Franckowiak, Simone Garrappa, Valery Brinnel, Jannis Necker, Jakob Nordin & Simeon Reusch

  3. Center for Cosmology and Particle Physics, New York University, New York, NY, USA

    Sjoert van Velzen & Glennys R. Farrar

  4. Department of Astronomy, University of Maryland, College Park, MD, USA

    Sjoert van Velzen, Suvi Gezari, Sara Frederick, Tomás Ahumada, Virginia Cunningham, Erica Hammerstein & Charlotte Ward

  5. Leiden Observatory, Leiden University, Leiden, The Netherlands

    Sjoert van Velzen

  6. Columbia Astrophysics Laboratory, Columbia University in the City of New York, New York, NY, USA

    Marek Kowalski

  7. Joint Space-Science Institute, University of Maryland, College Park, MD, USA

    Suvi Gezari & S. Bradley Cenko

  8. International Centre for Radio Astronomy Research—Curtin University, Perth, Australia

    James C. A. Miller-Jones

  9. Racah Institute of Physics, The Hebrew University of Jerusalem, Jerusalem, Israel

    Itai Sfaradi & Assaf Horesh

  10. Hartebeesthoek Radio Astronomy Observatory, SARAO, Krugersdorp, South Africa

    Michael F. Bietenholz

  11. Department of Physics and Astronomy, York University, Toronto, Ontario, Canada

    Michael F. Bietenholz

  12. Astrophysics, Department of Physics, University of Oxford, Oxford, UK

    Rob Fender

  13. Department of Astronomy, University of Cape Town, Rondebosch, South Africa

    Rob Fender & Patrick Woudt

  14. Division of Physics, Mathematics, and Astronomy, California Institute of Technology, Pasadena, CA, USA

    Igor Andreoni, Andrew Drake, Matthew J. Graham, Mansi M. Kasliwal, Ashish A. Mahabal & Yuhan Yao

  15. Caltech Optical Observatories, California Institute of Technology, Pasadena, CA, USA

    Justin Belicki, Rick Burruss, Michael Feeney & Hector Rodriguez

  16. DIRAC Institute, Department of Astronomy, University of Washington, Seattle, WA, USA

    Eric C. Bellm & V. Zach Golkhou

  17. Centre for Space Research, North-West University, Potchefstroom, South Africa

    Markus Böttcher

  18. Astroparticle Physics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA

    S. Bradley Cenko & Leo P. Singer

  19. School of Physics and Astronomy, University of Minnesota, Minneapolis, MN, USA

    Michael W. Coughlin

  20. Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA, USA

    Ryan J. Foley, Tiara Hung, Charles D. Kilpatrick & César Rojas-Bravo

  21. Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot, Israel

    Avishay Gal-Yam & Maayane T. Soumagnac

  22. The eScience Institute, University of Washington, Seattle, WA, USA

    V. Zach Golkhou

  23. The Oskar Klein Centre, Department of Physics, Stockholm University, AlbaNova, Stockholm, Sweden

    Ariel Goobar

  24. IPAC, California Institute of Technology, Pasadena, CA, USA

    George Helou, Russ R. Laher, Frank J. Masci, Ben Rusholme & David L. Shupe

  25. Institute of Astronomy, National Tsing Hua University, Hsinchu, Taiwan

    Albert K. H. Kong

  26. Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA, USA

    Thomas Kupfer

  27. Center for Data Driven Discovery, California Institute of Technology, Pasadena, CA, USA

    Ashish A. Mahabal

  28. Astrophysics Research Institute, Liverpool John Moores University, Liverpool, UK

    Daniel A. Perley & Kirsty Taggart

  29. Université Lyon, Université Claude-Bernard Lyon 1, CNRS/IN2P3, IP2I Lyon, Villeurbanne, France

    Mickael Rigault

  30. The Oskar Klein Centre, Department of Astronomy, Stockholm University, AlbaNova, Stockholm, Sweden

    Jesper Sollerman

  31. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Maayane T. Soumagnac

  32. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

    Daniel Stern

Authors
  1. Robert Stein
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sjoert van Velzen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marek Kowalski
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anna Franckowiak
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Suvi Gezari
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. James C. A. Miller-Jones
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sara Frederick
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Itai Sfaradi
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Michael F. Bietenholz
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Assaf Horesh
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Rob Fender
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Simone Garrappa
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Tomás Ahumada
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Igor Andreoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Justin Belicki
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Eric C. Bellm
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Markus Böttcher
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Valery Brinnel
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Rick Burruss
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. S. Bradley Cenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Michael W. Coughlin
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Virginia Cunningham
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Andrew Drake
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Glennys R. Farrar
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Michael Feeney
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Ryan J. Foley
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Avishay Gal-Yam
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. V. Zach Golkhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  29. Ariel Goobar
    View author publications

    You can also search for this author in PubMed Google Scholar

  30. Matthew J. Graham
    View author publications

    You can also search for this author in PubMed Google Scholar

  31. Erica Hammerstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  32. George Helou
    View author publications

    You can also search for this author in PubMed Google Scholar

  33. Tiara Hung
    View author publications

    You can also search for this author in PubMed Google Scholar

  34. Mansi M. Kasliwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  35. Charles D. Kilpatrick
    View author publications

    You can also search for this author in PubMed Google Scholar

  36. Albert K. H. Kong
    View author publications

    You can also search for this author in PubMed Google Scholar

  37. Thomas Kupfer
    View author publications

    You can also search for this author in PubMed Google Scholar

  38. Russ R. Laher
    View author publications

    You can also search for this author in PubMed Google Scholar

  39. Ashish A. Mahabal
    View author publications

    You can also search for this author in PubMed Google Scholar

  40. Frank J. Masci
    View author publications

    You can also search for this author in PubMed Google Scholar

  41. Jannis Necker
    View author publications

    You can also search for this author in PubMed Google Scholar

  42. Jakob Nordin
    View author publications

    You can also search for this author in PubMed Google Scholar

  43. Daniel A. Perley
    View author publications

    You can also search for this author in PubMed Google Scholar

  44. Mickael Rigault
    View author publications

    You can also search for this author in PubMed Google Scholar

  45. Simeon Reusch
    View author publications

    You can also search for this author in PubMed Google Scholar

  46. Hector Rodriguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  47. César Rojas-Bravo
    View author publications

    You can also search for this author in PubMed Google Scholar

  48. Ben Rusholme
    View author publications

    You can also search for this author in PubMed Google Scholar

  49. David L. Shupe
    View author publications

    You can also search for this author in PubMed Google Scholar

  50. Leo P. Singer
    View author publications

    You can also search for this author in PubMed Google Scholar

  51. Jesper Sollerman
    View author publications

    You can also search for this author in PubMed Google Scholar

  52. Maayane T. Soumagnac
    View author publications

    You can also search for this author in PubMed Google Scholar

  53. Daniel Stern
    View author publications

    You can also search for this author in PubMed Google Scholar

  54. Kirsty Taggart
    View author publications

    You can also search for this author in PubMed Google Scholar

  55. Jakob van Santen
    View author publications

    You can also search for this author in PubMed Google Scholar

  56. Charlotte Ward
    View author publications

    You can also search for this author in PubMed Google Scholar

  57. Patrick Woudt
    View author publications

    You can also search for this author in PubMed Google Scholar

  58. Yuhan Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

R.S. first identified AT2019dsg as a candidate neutrino source, performed the neutrino analysis and was the primary author of the manuscript. M.K., R.S. and S.v.V. developed the multizone model. G.R.F., M.K. and R.S. performed the neutrino modelling. A.F., J. Necker, R.S. and S.R. scheduled and analysed ZTF ToO observations. J.C.A.M.-J. and S.v.V. contributed the VLA observations. A.H., R.J.F. and I.S. contributed the AMI-LA observations. M.F.B., M.B., R.J.F., J.C.A.M.-J. and P.W. contributed the MeerKAT observations. S. Gezari and S.v.V. requested and reduced the Swift-UVOT data. D.A.P. and K.T. contributed the Liverpool Telescope observations. S.B.C., S.F. and S. Gezari performed X-ray observations and data analysis. S. Garrappa analysed Fermi gamma-ray data. S.R. and S.v.V. analysed the ZTF data. J.B., E.C.B., R.B., S.B.C., V.C., M.F., V.Z.G., A.G., M.J.G, G.H., M.M.K., T.K., R.R.L., A.A.M, F.J.M., H.R., B.R., D.L.S. and M.T.S contributed to the implementation of ZTF. T.A., I.A., M.W.C., M.M.K. and L.P.S. enabled ZTF ToO observations. A.D., R.J.F., M.J.G., S. Gezari, E.H., T.H., M.M.K., C.D.K., M.R., C.R.-B., D.S, C.W. and Y.Y. contributed to spectroscopic observations and data reduction. R.S. developed the ToO analysis pipeline. V.B., J. Nordin and J.v.S. developed AMPEL, and contributed to the ToO analysis infrastructure. A.G.-Y., A.K.H.K. and J.S. contributed to the manuscript and discussions. All authors reviewed the contents of the manuscript.

Corresponding authors

Correspondence to Robert Stein, Sjoert van Velzen or Marek Kowalski.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

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

Extended data

Extended Data Fig. 1 Spectroscopic evolution of AT2019dsg.

The public classification spectrum taken with the NTT[15] is plotted in blue, along with later spectra from LDT, Lick, Keck and P200. Each is plotted in arbitrary units, offset for display purposes. The Balmer lines are highlighted in cyan, the HeII lines in gray, and the Bowen fluorescence lines (OIII at 3760Å, NIII at 4100Å and 4640Å) in black. Telluric lines are marked with +.

Extended Data Fig. 2 X-ray count map from XMM-Newton.

The image was taken 50 days after discovery. The green circle indicates the source region, while the red circular region was used to measure the background. The best-fit position derived from optical observations is spatially-coincident with the center of the X-ray source region.

Extended Data Fig. 3 Soft X-ray spectrum of AT2019dsg.

Panel (a) shows the photon flux as a function of energy in blue, from the XMM Newton spectrum taken on 2019 May 30. The spectrum was fitted with an absorbed disk blackbody model, shown in black. Panel (b) shows the ratio of the data to the model, with the horizontal orange line indicating unity. Error bars represent 1σ intervals.

Extended Data Fig. 4 Peak frequency and peak flux density of the radio observations.

The time (Δt) is measured in the observer frame relative to MJD 58582.8, the date of discovery for AT2019dsg.

Extended Data Fig. 5 Properties of radio-emitting region.

These values are inferred from the synchrotron peak flux and peak frequency (see Extended Data Fig. 4), where R is the region radius, E is the non-thermal energy, B is the magnetic field strength and ne is the density of non-thermal electrons. Except for Δt, all quantities are reported as log10 with the uncertainty (68% CL) listed in brackets.

Extended Data Fig. 6 LAT count map of the Region Of Interest (ROI).

The map shows the integrated search period G3, showing the IC191001A 90% localisation region in orange. The position of AT2019dsg is marked by a white star. The neutrino best-fit position is marked with a orange ‘ × ’. Two gamma-ray sources are significantly detected (≥ 5 σ) in the ROI but outside the neutrino uncertainty region as marked with white crosses. There is no excess consistent with the position of AT2019dsg.

Extended Data Fig. 7 Gamma-ray energy flux upper-limits for AT2019dsg.

The values are derived assuming a point-source with power-law index Γ=2.0 at the position of AT2019dsg, integrated over the analysis energy range 0.1-800 GeV.

Extended Data Fig. 8 LAT lightcurve for Fermi-J2113.8+1120.

The flux is derived in the 0.1-800 GeV energy range for the source during the time interval G3, with evenly spaced binning of 28 days. Vertical error bars represent 1σ intervals, horizontal bars denote bin width. 2σ upper limits are shown for bins with TS≤9. The orange dashed vertical line marks the arrival time of IC-191001A. Since this source lies outside the reported 90% error region (see Extended Data Fig. 6), and given that the LAT lightcurve shows no obvious correlation with the neutrino arrival time, we conclude that it is unlikely to be associated with the neutrino.

Supplementary information

Supplementary Information

Supplementary Discussion, Fig. 1 and Tables 1–5.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Stein, R., Velzen, S.v., Kowalski, M. et al. A tidal disruption event coincident with a high-energy neutrino. Nat Astron 5, 510–518 (2021). https://doi.org/10.1038/s41550-020-01295-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41550-020-01295-8

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing