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A long-duration gamma-ray burst with a peculiar origin

Abstract

It is generally believed that long-duration gamma-ray bursts (GRBs) are associated with massive star core collapse1, whereas short-duration GRBs are associated with mergers of compact star binaries2. However, growing observations3,4,5,6 have suggested that oddball GRBs do exist, and several criteria (prompt emission properties, supernova/kilonova associations and host galaxy properties) rather than burst duration only are needed to classify GRBs physically7. A previously reported long-duration burst, GRB 060614 (ref. 3), could be viewed as a short GRB with extended emission if it were observed at a larger distance8 and was associated with a kilonova-like feature9. As a result, it belongs to the type I (compact star merger) GRB category and is probably of binary neutron star (NS) merger origin. Here we report a peculiar long-duration burst, GRB 211211A, whose prompt emission properties in many aspects differ from all known type I GRBs, yet its multiband observations suggest a non-massive-star origin. In particular, substantial excess emission in both optical and near-infrared wavelengths has been discovered (see also ref. 10), which resembles kilonova emission, as observed in some type I GRBs. These observations point towards a new progenitor type of GRBs. A scenario invoking a white dwarf (WD)–NS merger with a post-merger magnetar engine provides a self-consistent interpretation for all the observations, including prompt gamma rays, early X-ray afterglow, as well as the engine-fed11,12 kilonova emission.

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Fig. 1: The temporal and spectral behaviours of GRB 211211A.
Fig. 2: GRB 211211A in already classified clusters.
Fig. 3: The multiwavelength observations and fitting models.

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Data availability

The processed data are presented in the tables and figures of the paper, which are available on reasonable request. The authors point out that the data used in the paper are publicly available, whether through the Fermi/GBM data archive, the Swift data archive or GCN circulars.

Code availability

On reasonable request, the code (mostly in Python) used to produce the results and figures will be provided.

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Acknowledgements

This work is supported by the National Key Research and Development Programs of China (2018YFA0404204, 2018YFA0404602, 2022YFF0711404), the National Natural Science Foundation of China (grant nos. 11833003, U2038105, 12121003, 11922301, 12041306 and 12103089), the science research grants from the China Manned Space Project with no. CMS-CSST-2021-B11, the Natural Science Foundation of Jiangsu Province (grant no. BK20211000) and the Program for Innovative Talents, Entrepreneur in Jiangsu. S.A. and B.Z. acknowledge support from the Top Tier Doctoral Graduate Research Assistantship (TTDGRA) and Nevada Center for Astrophysics at the University of Nevada, Las Vegas. We acknowledge the use of public data from the Fermi Science Support Center, the Swift Science Data Centre and GCN circulars reported by several facilities. We thank X. Liu, Y.-Z. Meng and Z.-K. Peng for helpful comments.

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Contributions

B.-B.Z. and J.Y. initiated the study. B.-B.Z., B.Z., J.Y. and S.A. coordinated the scientific investigations of the event. J.Y. processed and analysed the Fermi/GBM and Swift data. J.Y. and Z.-K.L. calculated the spectral lags. J.Y., X.I.W. and H.-J.L. calculated the amplitude parameter. J.Y., Y.-H.Yang and Y.-H.Yin fitted the Amati relation. J.Y. and Y.L. contributed to the information about the host galaxy. J.Y. contributed to the afterglow analysis and modelling. S.A. provided the engine-fed kilonova model. J.Y. and S.A. performed theoretical modelling of the engine-fed kilonova. J.Y. and S.A. contributed to the magnetic-bubble and spin-down models. B.Z. and S.A. developed the WD–NS merger scenario. B.Z., S.A. and J.Y. investigated other progenitor models. J.Y., B.-B.Z., B.Z. and S.A. wrote the manuscript, with contributions from all authors.

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Correspondence to Bin-Bin Zhang or Bing Zhang.

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Extended data figures and tables

Extended Data Fig. 1 The multiwavelength light curves of prompt emissions and spectral lags.

a, The scaled multiwavelength light curves obtained from Fermi/GBM (blue) and Swift/BAT (red) data for GRB 211211A and Swift/BAT (black) data for GRB 060614. For comparison, we reduce the trigger time of GRB 060614 by 5 s. bd, The spectral lags between each of the higher-energy bands and the lowest-energy band calculated for the main emission, extended emission and whole burst of GRB 211211A. The lags in blue and red are derived from Fermi/GBM and Swift/BAT data, respectively. The horizontal black lines and grey shaded areas in b and c show the spectral lags and their uncertainties of GRB 060614, respectively. All error bars on data points represent their 1σ confidence level.

Extended Data Fig. 2 The T90 distributions.

a, The T90 distribution (grey histogram) of the short GRB (T90 < 2 s) sample from the fourth Fermi/GBM catalogue35 fit with a single log-normal distribution (solid black line). GRB 211211A (with 13-s main emission) and GRB 060614 (with 6-s main emission) are highlighted in red and blue, respectively. b, The T90 distribution (grey histogram) of the whole GRB sample from the fourth Fermi/GBM catalogue fit with a two-component log-normal mixture model (solid black line). The two components responsible for short and long GRB populations are shown with grey dashed and dotted lines, respectively. GRB 211211A (with 13-s main emission) and GRB 060614 (with 6-s main emission) are highlighted in red and blue, respectively.

Extended Data Fig. 3 The α, Ep and flux F correlation diagrams.

ad, The linear fits to α–logF, logEp–logF, logEpα and logEp,z–logEγ,iso relations during the main emission phase (blue) and the extended emission phase (magenta). The solid and dashed lines show the best-fit correlations and 3σ error bands, respectively. All error bars on data points represent their 1σ confidence level. e,f, The distributions of the best-fit α and Ep obtained from time-resolved spectral fits.

Extended Data Fig. 4 The X-ray afterglow of GRB 211211A fit with the SBPL function.

The X-ray afterglow in PC mode is shown with grey error bars. The two-segment and three-segment SBPL models are represented by blue and red lines, respectively. On the basis of the statistics (stat/dof, BIC and AICc), the data favours the three-segment SBPL model more than the two-segment SBPL model. The differences in BIC and AICc between the two-segment and three-segment SBPL models are ΔBIC = 2.54 and ΔAICc = 5.42, respectively. Such ‘strength of evidence’ (that is, ΔBIC and ΔAICc) also positively supports the three-segment SBPL model.

Extended Data Fig. 5 The fit of the afterglow plus engine-fed kilonova model to multiwavelength data.

a, Corner plot of the posterior probability distributions of the parameters. The red error bars represent the 1σ uncertainties. b, Afterglow-subtracted observations and best-fitting engine-fed kilonova model. The detections and upper limits of the afterglow-subtracted observations are shown with solid circles and downward arrows, respectively. The best-fit models in different bands are presented with solid lines.

Extended Data Table 1 Spectral fitting results and corresponding energy flux in each time interval of GRB 211211A
Extended Data Table 2 The best-fit parameters of linear models for α–logF, logEp–logF, logEpα and logEp,z–logEγ,iso correlations
Extended Data Table 3 The temporal and spectral profiles of X-ray afterglows
Extended Data Table 4 Ultraviolet, optical and near-infrared observations of GRB 211211A
Extended Data Table 5 The best-fit parameters of the afterglow and engine-fed kilonova models

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Yang, J., Ai, S., Zhang, BB. et al. A long-duration gamma-ray burst with a peculiar origin. Nature 612, 232–235 (2022). https://doi.org/10.1038/s41586-022-05403-8

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