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Delayed radio flares from a tidal disruption event

Nature Astronomy volume 5, pages 491–497 (2021)Cite this article

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Abstract

Radio observations of tidal disruption events (TDEs)—when a star is tidally disrupted by a supermassive black hole (SMBH)—provide a unique laboratory for studying outflows in the vicinity of SMBHs and their connection to accretion onto the supermassive black hole. Radio emission has been detected in only a handful of TDEs so far. Here we report the detection of delayed radio flares from an optically discovered TDE. Our prompt radio observations of the TDE ASASSN-15oi showed no radio emission until the detection of a flare six months later, followed by a second and brighter flare years later. We find that the standard scenario, in which an outflow is launched briefly after the stellar disruption, is unable to explain the combined temporal and spectral properties of the delayed flare. We suggest that the flare is due to the delayed ejection of an outflow, perhaps following a transition in accretion states. Our discovery motivates observations of TDEs at various timescales and highlights a need for new models.

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Fig. 1: The radio luminosity of a handful of TDEs as a function of time.
Fig. 2: The evolution of the peak flux density and frequency of the delayed radio emission from ASASSN-15oi.
Fig. 3: Comparison of the temporal evolution of the X-ray luminosity with the optically thin radio luminosity in ASASSN-15oi.

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Data availability

The ASASSN-15oi radio data, presented in several figures, can be found in Supplementary Table 1. The raw VLA data are available via the NRAO archive at https://archive.nrao.edu/archive/advquery.jsp. The collection of radio data of other TDEs can be found in ref. 35. The ASASSN-15oi X-ray emission measurements can be found in ref. 25. Any additional data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

Tools to analyse the VLA data can be found on the NRAO website at http://go.nature.com/2MEGye3.

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Acknowledgements

We thank T. Piran, E. Nakar and R. Fender for useful discussions. A.H. was suported by grants from the I-CORE Program of the Planning and Budgeting Committee and the Israel Science Foundation (ISF), and from the US–Israel Binational Science Foundation (BSF). I.A. is a CIFAR Azrieli Global Scholar in the Gravity and the Extreme Universe Program and acknowledges support from that program, from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement number 852097), from the Israel Science Foundation (grant number 2752/19), from the United States – Israel Binational Science Foundation (BSF), and from the Israeli Council for Higher Education Alon Fellowship. We thank the NRAO staff for approving and scheduling the VLA observations. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. We thank the Swift TOO team. This research has made use of data and/or software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC), which is a service of the Astrophysics Science Division at NASA/GSFC. This research has made use of the CIRADA cutout service at http://cutouts.cirada.ca/, operated by the Canadian Initiative for Radio Astronomy Data Analysis (CIRADA). CIRADA is funded by a grant from the Canada Foundation for Innovation 2017 Innovation Fund (Project 35999), as well as by the Provinces of Ontario, British Columbia, Alberta, Manitoba and Quebec, in collaboration with the National Research Council of Canada, the US National Radio Astronomy Observatory and Australia’s Commonwealth Scientific and Industrial Research Organisation.

Author information

Authors and Affiliations

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

    A. Horesh

  2. Astrophysics Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA

    S. B. Cenko

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

    S. B. Cenko

  4. The School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel

    I. Arcavi

  5. CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, Ontario, Canada

    I. Arcavi

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  1. A. Horesh
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A.H. led the radio observing campaign, the data analysis and modelling, the interpretation and the manuscript preparation. S.B.C and I.A. contributed to the interpretation of the results and to the manuscript preparation.

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Correspondence to A. Horesh.

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Extended data

Extended Data Fig. 1 VLA K-band images of the position of the optical TDE candidate ASASSN-15oi, before and after radio detection.

The left panel (a) presents the third VLA image we obtained of this field 3 months after optical discovery on 2015 Nov 12, still showing a null-detection. The right panel (b) presents the image from our forth VLA observation on 2016 Feb 12 which reveals a delayed radio flare, 6 months after optical discovery. The synthesized beam size is shown as a white ellipse at the bottom left corner of the images. The flux density scale is identical in both images.

Extended Data Fig. 2 The full observed broadband spectral evolution of the delayed radio flare from ASASSN-15oi.

Each of the radio broadband spectra is from a different observing epoch, starting from the initial detection of the delayed flare on 182 days and up to 576 days after optical discovery. Data from each epoch is represented by a different marker shape and color as noted in the legend (a dashed line connecting the data has been added for convenience). The error bars represent the image noise and flux calibration error added in quadrature (see Supplementary Table 1).

Extended Data Fig. 3 Best fit single-epoch spectral models of the radio flare.

Observing epochs at Δt=182, 190, 197 days are represented in purple, yellow and red, respectively. The broadband spectrum in each single epoch was fitted independently, thus not including any modeling of the temporal evolution. The errors of the data modeled here include the flux density calibration error and image noise added in quadrature. The left panel (a) presents the best-fit homogeneous SSA model33. The middle panel (b) shows the best-fit models of the radio flare spectra using the internal free-free absorption model53. The right panel (c) is the best-fit models using the inhomogeneous SSA model55. Out of the three models that we try here, the latter model is the best match to the spectral data presented in this figure (see details in Methods).

Extended Data Fig. 4 Comparison of the temporal evolution of the observed optically thin radio emission with different rising and declining power-law functions.

The presented radio emission is at a frequency of 15 GHz (black solid line and markers). The various power-law functions for both the rise of the emission (since the last non-detection) and its decline are presented as dashed curves (representing various predictions, see details in Methods). The black triangle represents a 3σ non-detection limit (based on the average between the 22 GHz and 6 GHz limits).

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Supplementary Table 1.

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Horesh, A., Cenko, S.B. & Arcavi, I. Delayed radio flares from a tidal disruption event. Nat Astron 5, 491–497 (2021). https://doi.org/10.1038/s41550-021-01300-8

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