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Burst timescales and luminosities as links between young pulsars and fast radio bursts

Nature Astronomy volume 6, pages 393–401 (2022)Cite this article

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Abstract

Fast radio bursts (FRBs) are extragalactic radio flashes of unknown physical origin. Their high luminosities and short durations require extreme energy densities, such as those found in the vicinity of neutron stars and black holes. Studying the burst intensities and polarimetric properties on a wide range of timescales, from milliseconds down to nanoseconds, is key to understanding the emission mechanism. However, high-time-resolution studies of FRBs are limited by their unpredictable activity levels, available instrumentation and temporal broadening in the intervening ionized medium. Here we show that the repeating FRB 20200120E can produce isolated shots of emission as short as about 60 nanoseconds in duration, with brightness temperatures as high as 3 × 1041 K (excluding relativistic effects), comparable with ‘nano-shots’ from the Crab pulsar. Comparing both the range of timescales and luminosities, we find that FRB 20200120E observationally bridges the gap between known Galactic young pulsars and magnetars and the much more distant extragalactic FRBs. This suggests a common magnetically powered emission mechanism spanning many orders of magnitude in timescale and luminosity. In this Article, we probe a relatively unexplored region of the short-duration transient phase space; we highlight that there probably exists a population of ultrafast radio transients at nanosecond to microsecond timescales, which current FRB searches are insensitive to.

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Fig. 1: Burst B3 from FRB 20200120E exhibits sub-microsecond temporal structure.
Fig. 2: The polarimetric profiles, dynamic spectra, time-averaged spectra and polarization position angle (PPA) of the bursts detected from FRB 20200120E.
Fig. 3: Nanosecond to second transient phase space.

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Data availability

The data that support the plots and results in this study are available at: https://doi.org/10.5281/zenodo.5666802.

Code availability

The code used for the analysis and figures in this work can be found here: https://github.com/KenzieNimmo/FRB20200120E_timescales. The phased-array branch of SFXC can be accessed here: https://github.com/aardk/sfxc/tree/phased-array. The bolometer branch of SFXC can be accessed here: https://github.com/aardk/sfxc/tree/bolometer. DSPSR (which contains digifil) can be installed from here: http://dspsr.sourceforge.net/. PSRCHIVE can be installed from here: http://psrchive.sourceforge.net/. For burst searches the required software is PRESTO (https://github.com/scottransom/presto), SpS (https://github.com/danielemichilli/SpS), Heimdall (https://sourceforge.net/projects/heimdall-astro/) and FETCH (https://github.com/devanshkv/fetch).

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Acknowledgements

We thank W. van Straten for help with digifil. The European VLBI Network is a joint facility of independent European, African, Asian and North American radio astronomy institutes. Scientific results from data presented in this publication are derived from the following EVN project code: EK048. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No. 730562 (RadioNet) and 101004719 (OPTICON–RadioNet Pilot). A.B.P is a McGill Space Institute Fellow and a Fonds de Recherche du Quebec—Nature et Technologies (FRQNT) postdoctoral fellow. B.M. acknowledges support from the Spanish Ministerio de Economía y Competitividad under grant AYA2016-76012-C3-1-P and from the Spanish Ministerio de Ciencia e Innovación under grants PID2019-105510GB-C31 and CEX2019-000918-M of the Institut de Ciències del Cosmos of the Universitat de Barcelona (Unidad de Excelencia ‘María de Maeztu’ 2020–2023). C.L. was supported by the US Department of Defense through the National Defense Science & Engineering Graduate Fellowship Program. D.M. is a Banting Fellow. E.P. acknowledges funding from a Dutch Research Council (NWO) Veni Fellowship. F.K. acknowledges support from the Swedish Research Council. FRB research at the University of British Columbia is supported by a Natural Sciences and Engineering Research Council of Canada Discovery Grant and by the Canadian Institute for Advanced Research. J.P.Y. is supported by the National Program on Key Research and Development Project (2017YFA0402602). K.S. is supported by the National Science Foundation Graduate Research Fellowship Program. K.W.M. is supported by a National Science Foundation Grant (2008031). M.B. is supported by an FRQNT Doctoral Research Award. N.W. acknowledges support from the National Natural Science Foundation of China (Grant 12041304 and 11873080). P.S. is a Dunlap Fellow and a Natural Sciences and Engineering Research Council of Canada Postdoctoral Fellow. The Dunlap Institute is funded through an endowment established by the David Dunlap family and the University of Toronto. V.B. acknowledges support from the Engineering Research Institute Ventspils International Radio Astronomy Centre. Research by the AstroFlash group at University of Amsterdam, ASTRON and the Joint Institute for VLBI ERIC is supported in part by an NWO Vici grant (principal investigator J.W.T.H.; VI.C.192.045).

Author information

Authors and Affiliations

  1. ASTRON, Netherlands Institute for Radio Astronomy, Dwingeloo, the Netherlands

    K. Nimmo, J. W. T. Hessels, F. Kirsten & R. Blaauw

  2. Anton Pannekoek Institute for Astronomy, University of Amsterdam, Amsterdam, the Netherlands

    K. Nimmo, J. W. T. Hessels, M. P. Snelders, D. M. Hewitt, O. S. Ould-Boukattine & E. Petroff

  3. Department of Space, Earth and Environment, Chalmers University of Technology, Onsala Space Observatory, Onsala, Sweden

    F. Kirsten, J. E. Conway, O. Forssén, M. Lindqvist, W. Vlemmings & J. Yang

  4. Joint Institute for VLBI ERIC, Dwingeloo, the Netherlands

    A. Keimpema, B. Marcote & Z. Paragi

  5. Department of Astronomy and Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, NY, USA

    J. M. Cordes

  6. Max Planck Institute for Radio Astronomy, Bonn, Germany

    R. Karuppusamy

  7. School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK

    A. M. Archibald

  8. Engineering Research Institute Ventspils International Radio Astronomy Centre (ERI VIRAC) of Ventspils University of Applied Sciences (VUAS), Ventspils, Latvia

    V. Bezrukovs & A. Orbidans

  9. Department of Physics, McGill University, Montreal, Quebec, Canada

    M. Bhardwaj, E. Fonseca, D. Michilli, A. B. Pearlman & E. Petroff

  10. McGill Space Institute, McGill University, Montreal, Quebec, Canada

    M. Bhardwaj, E. Fonseca, D. Michilli, A. B. Pearlman & E. Petroff

  11. Istituto Nazionale di Astrofisica, Istituto di Radioastronomia Radiotelescopio di Noto, Noto, Italy

    S. T. Buttaccio

  12. Dunlap Institute for Astronomy & Astrophysics, University of Toronto, Toronto, Ontario, Canada

    T. Cassanelli, R. Mckinven, C. Ng & P. Scholz

  13. David A. Dunlap Department of Astronomy & Astrophysics, University of Toronto, Toronto, Ontario, Canada

    T. Cassanelli & R. Mckinven

  14. Istituto Nazionale di Astrofisica, Osservatorio Astronomico di Cagliari, Selargius, Italy

    A. Corongiu & G. Surcis

  15. Institute of Astronomy, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Toruń, Poland

    R. Feiler & M. Gawroński

  16. Department of Physics and Astronomy, West Virginia University, Morgantown, WV, USA

    E. Fonseca

  17. Center for Gravitational Waves and Cosmology, West Virginia University, Morgantown, WV, USA

    E. Fonseca

  18. Istituto Nazionale di Astrofisica, Istituto di Radioastronomia, Bologna, Italy

    M. Giroletti & G. Maccaferri

  19. Institute of Applied Astronomy of the Russian Academy of Sciences, St. Petersburg, Russia

    M. A. Kharinov, A. Melnikov & A. G. Mikhailov

  20. MIT Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    C. Leung, K. W. Masui, D. Michilli & K. Shin

  21. Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA

    C. Leung, K. W. Masui, D. Michilli & K. Shin

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

    A. B. Pearlman

  23. Sidrat Research, Toronto, Ontario, Canada

    M. Rahman

  24. Perimeter Institute for Theoretical Physics, Waterloo, Ontario, Canada

    K. M. Smith

  25. Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada

    I. H. Stairs

  26. Department of Astronomy and Astrophysics, Tata Institute of Fundamental Research, Mumbai, India

    S. P. Tendulkar

  27. National Centre for Radio Astrophysics, Pune, India

    S. P. Tendulkar

  28. Xinjiang Astronomical Observatory, Urumqi, China

    N. Wang & J. P. Yuan

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  1. K. Nimmo
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Contributions

K.N. led the data analysis, made the figures and wrote most of the manuscript. J.W.T.H. guided the work and made important contributions to the writing and interpretation. F.K. discovered the bursts and contributed to the analysis of the voltage data. A.K. adapted the SFXC code to create coherently dedispersed voltage data at the native time resolution. J.M.C. provided important insights into the data analysis strategy. M.P.S., D.M.H. and R.K. played supporting roles in the data acquisition and analysis. All other authors contributed significantly to laying the groundwork for this study, or aspects of the data acquisition or interpretation.

Corresponding author

Correspondence to K. Nimmo.

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The authors declare no competing interests.

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Nature Astronomy thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 The probability that the brightest 1–2 bin features in the 31.25 ns burst profiles are consistent with the local amplitude modulated noise distribution.

Panels a–c show the 31.25 ns resolution profiles (grey) with off burst noise (black) shown for comparison. The burst name and time resolution is shown in the top left corner and the frequency range averaged over to produce the burst profile in the top right corner of the panels. Panels d–f are zoomed-in profiles containing the highest S/N feature in the burst profile. The colored region represent the local region (time span ± 1.5625μs) used to determine the probability density function (pdf; panels g–i) and cumulative density function (cdf; panels j–l). Note that the feature at the center of the colored region is not added to the distribution, since this is the feature which we want to determine the significance of relative to the local distribution. An exponential distribution fit is overplotted (colored lines) on the pdf and cdf. The highest S/N feature is represented by the vertical dashed line on the cdf (where in the case of B3, there are two dashed lines since the feature is 2 bins wide), and the legend shows the probability (or 1-cdf) of these features. The horizontal dashed lines on panels d–f represent the 3σ levels for single-bin features, using this local distribution (also for 2-bin features in the case of B3).

Extended Data Fig. 2 Low time resolution 2D autocorrelation functions (ACFs) of the bursts detected from FRB 20200120E.

Panels f–j show the 2D ACF with colored contours overplotted representing the 2D Gaussian fit 1,2,3 and 4σ. The zero lag spike is not plotted. The ACF is computed using filterbank data generated with SFXC29, with time and frequency resolution of 8μs and 125 kHz, respectively. The data were dedispersed using a DM of 87.75 pc cm−3. Panels a–e show the frequency-averaged time ACF, with the frequency-averaged Gaussian fit overplotted, and similarly panels k–o show the time-averaged frequency ACF, with the time-averaged Gaussian fit overplotted. The time and frequency scales characterised in this plot, arise from the burst temporal width and frequency extent. The colored lines coordinate with other figures in this work (for example Figure 2 and Supplementary Figure 3).

Extended Data Fig. 3 Measurement of the scintillation bandwidth in the autocorrelation function (ACF) of each of the five bursts from FRB 20200120E.

Sub-figure a shows the time-averaged frequency ACF from Extended Data Figure 2 after subtracting the Gaussian fit (black). The Lorentzian fit to the central component is shown by the colored line. The burst name is shown in the top left of each panel, and the measured scintillation bandwidth (defined as the half-width at half-maximum of the Lorentzian80) is shown in the top right of each panel. Sub-figure b shows a colormap of the expected scattering timescale at 1.4 GHz as a function of Galactic longitude and latitude, from the NE2001 Galactic electron density model30. The sky positions of both FRB 20200120E and FRB 20180916B are shown by the black cross and white plus, respectively.

Extended Data Fig. 4 Dynamic spectrum of burst B3 from FRB 20200120E with time resolution 31.25 ns, temporal autocorrelation function (ACF) and power spectrum (PS).

Panel b shows the dynamic spectrum in the form of temporal profiles per subband. This data was generated with SFXC, and each subband has been coherently dedispersed to 87.7527 pc cm−3. Panel a shows the frequency-averaged burst profile. Panel c shows the average power spectrum (PS) of the four subbands containing significant burst structure in the top panel (grey), with a downsampled PS (factor 8) overplotted in black. The purple and blue lines represent fits to the PS of a red noise power law plus white noise model and a power law/white noise plus Lorentzian model, respectively. Panels d and e below show the residuals (2 × D/M, for data D and model M) of both models, matching the colors above. The dashed lines represent the perfect case of D = M. Panel f shows the average temporal ACF of the same four subbands (top panel, orange). For comparison the off burst ACF is also shown (grey). The residual of the average ACF subtracted the noise ACF is shown in panel g below, with the green and purple Lorentzian fits to the ACF residuals highlighting two distinct temporal scales in the data. Panel h shows a zoom in on the ACF residuals highlighting a third temporal scale by the cyan Lorentzian fit.

Extended Data Fig. 5 Dynamic spectrum, ACF and PS for burst B2 from FRB 20200120E.

Note the average ACF only shows one temporal scale (unlike the three seen for burst B3). Additionally, we only plot the red noise power law plus white noise model since any wide Lorentzian features are less apparent in this power spectrum, than the case of B3.

Extended Data Fig. 6 Dynamic spectrum, ACF and PS for burst B4 from FRB 20200120E.

Note the average ACF shows two temporal scales (unlike the 3 seen for burst B3). Additionally, we only plot the red noise power law plus white noise model since any wide Lorentzian features are less apparent in this power spectrum, than the case of B3.

Extended Data Fig. 7 Correlation coefficient between single time bin (1 μs) spectra of bursts B2, B3 and B4 from FRB 20200120E.

Panels a–c show the 1μs burst profile with the burst name and time resolution shown in the top left corner and the frequency range averaged over to produce the burst profile in the top right corner of each panel. Panels d–e show the correlation coefficient between single time bin spectra above a S/N threshold of 9 as a function of the time separation between bins. The color gradient indicates the geometric mean of the two time bins used to determine the correlation coefficient (darker color implying a higher geometric mean). Also plotted is a histogram of the correlation coefficients. The colored line represents the geometric mean S/N weighted correlation coefficient. The mean correlation coefficients are used to test for consistency with the scintillating, amplitude-modulated, polarized shot noise prediction (0.33 for 100% polarized emission35).

Extended Data Fig. 8 High time resolution polarimetric profile and polarization position angle (PPA) for burst B3 from FRB 20200120E.

Panels a–c show the PPA as a function of time, with the orange line representing the weighted best-fit line to the PPA. Only the PPAs above a linear S/N threshold of 5 are plotted. Panels d–f show the polarimetric profile of the burst sampled at 125 ns, with Stokes I (black), unbiased linear polarization (Everett & Weisberg63; red) and circular polarization (blue). The yellow and blue regions plotted on panels a and d represent the time ranges used for plotting panels b,e and panels c,f, respectively. This data was generated with SFXC, with 4 MHz channels and coherently (within subbands) and incoherently (between subbands) dedispersed to 87.7527 pc cm−3. The frequency information was averaged for the frequency range 1254 - 1430 MHz (visually, the extent of the burst in frequency), which, in this data product, corresponds to averaging by a factor of 44.

Supplementary information

Supplementary Information

Supplementary methods, Figs. 1–3 and Table 1.

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Nimmo, K., Hessels, J.W.T., Kirsten, F. et al. Burst timescales and luminosities as links between young pulsars and fast radio bursts. Nat Astron 6, 393–401 (2022). https://doi.org/10.1038/s41550-021-01569-9

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