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A Fast Radio Burst discovered in FAST drift scan survey

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 Added by Weiwei Zhu
 Publication date 2020
  fields Physics
and research's language is English




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We report the discovery of a highly dispersed fast radio burst, FRB~181123, from an analysis of $sim$1500~hr of drift-scan survey data taken using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The pulse has three distinct emission components, which vary with frequency across our 1.0--1.5~GHz observing band. We measure the peak flux density to be $>0.065$~Jy and the corresponding fluence $>0.2$~Jy~ms. Based on the observed dispersion measure of 1812~cm$^{-3}$~pc, we infer a redshift of $sim 1.9$. From this, we estimate the peak luminosity and isotropic energy to be $lesssim 2times10^{43}$~erg~s$^{-1}$ and $lesssim 2times10^{40}$~erg, respectively. With only one FRB from the survey detected so far, our constraints on the event rate are limited. We derive a 95% confidence lower limit for the event rate of 900 FRBs per day for FRBs with fluences $>0.025$~Jy~ms. We performed follow-up observations of the source with FAST for four hours and have not found a repeated burst. We discuss the implications of this discovery for our understanding of the physical mechanisms of FRBs.



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Fast Radio Bursts are millisecond-duration astronomical radio pulses of unknown physical origin that appear to come from extragalactic distances. Previous follow-up observations have failed to find additional bursts at the same dispersion measures (i.e. integrated column density of free electrons between source and telescope) and sky position as the original detections. The apparent non-repeating nature of the fast radio bursts has led several authors to hypothesise that they originate in cataclysmic astrophysical events. Here we report the detection of ten additional bursts from the direction of FRB121102, using the 305-m Arecibo telescope. These new bursts have dispersion measures and sky positions consistent with the original burst. This unambiguously identifies FRB121102 as repeating and demonstrates that its source survives the energetic events that cause the bursts. Additionally, the bursts from FRB121102 show a wide range of spectral shapes that appear to be predominantly intrinsic to the source and which vary on timescales of minutes or shorter. While there may be multiple physical origins for the population of fast radio bursts, the repeat bursts with high dispersion measure and variable spectra specifically seen from FRB121102 support models that propose an origin in a young, highly magnetised, extragalactic neutron star.
In recent years, millisecond duration radio signals originating from distant galaxies appear to have been discovered in the so-called Fast Radio Bursts. These signals are dispersed according to a precise physical law and this dispersion is a key observable quantity which, in tandem with a redshift measurement, can be used for fundamental physical investigations. While every fast radio burst has a dispersion measurement, none before now have had a redshift measurement, due to the difficulty in pinpointing their celestial coordinates. Here we present the discovery of a fast radio burst and the identification of a fading radio transient lasting $sim 6$ days after the event, which we use to identify the host galaxy; we measure the galaxys redshift to be $z=0.492pm0.008$. The dispersion measure and redshift, in combination, provide a direct measurement of the cosmic density of ionised baryons in the intergalactic medium of $Omega_{mathrm{IGM}}=4.9 pm 1.3%$, in agreement with the expectation from WMAP, and including all of the so-called missing baryons. The $sim6$-day transient is largely consistent with a short gamma-ray burst radio afterglow, and its existence and timescale do not support progenitor models such as giant pulses from pulsars, and supernovae. This contrasts with the interpretation of another recently discovered fast radio burst, suggesting there are at least two classes of bursts.
The origin of fast radio bursts (FRBs), millisecond-duration flashes of radio waves that are visible at distances of billions of light-years, remains an open astrophysical question. Here we report the detection of the multi-component FRB 20191221A with the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst Project (CHIME/FRB), and the identification of a periodic separation of 216.8(1) ms between its components with a significance of 6.5 sigmas. The long (~ 3 s) duration and nine or more components forming the pulse profile make this source an outlier in the FRB population. We also report two additional FRBs, 20210206A and 20210213A, whose multi-component pulse profiles show some indication of periodic separations of 2.8(1) and 10.7(1) ms, respectively, suggesting the possible existence of a group of FRBs with complex and periodic pulse profiles. Such short periodicities provide strong evidence for a neutron-star origin of these events. Moreover, our detections favour emission arising from the neutron-star magnetosphere, as opposed to emission regions located further away from the star, as predicted by some models. Possible explanations for the observed periodicity include super-giant pulses from a neutron star that are possibly related to a magnetar outburst and interacting neutron stars in a binary system.
The Commensal Radio Astronomy Five-hundred-meter Aperture Spherical radio Telescope (FAST) Survey (CRAFTS) utilizes the novel drift-scan commensal survey mode of FAST and can generate billions of pulsar candidate signals. The human experts are not likely to thoroughly examine these signals, and various machine sorting methods are used to aid the classification of the FAST candidates. In this study, we propose a new ensemble classification system for pulsar candidates. This system denotes the further development of the pulsar image-based classification system (PICS), which was used in the Arecibo Telescope pulsar survey, and has been retrained and customized for the FAST drift-scan survey. In this study, we designed a residual network model comprising 15 layers to replace the convolutional neural networks (CNNs) in PICS. The results of this study demonstrate that the new model can sort >96% of real pulsars to belong the top 1% of all candidates and classify >1.6 million candidates per day using a dual--GPU and 24--core computer. This increased speed and efficiency can help to facilitate real-time or quasi-real-time processing of the pulsar-search data stream obtained from CRAFTS. In addition, we have published the labeled FAST data used in this study online, which can aid in the development of new deep learning techniques for performing pulsar searches.
Fast radio bursts (FRBs) are extremely luminous and brief radio flashes originating from other galaxies (Petroff et al. 2019). Progressing our understanding of the FRB phenomenon is limited by their large distances and unpredictable activity. The recent discovery of FRB 20200120E (Bhardwaj et al. 2021), in the direction of the M81 galaxy, offers the chance to study an exceptionally nearby repeating source. Here we conclusively prove that FRB 20200120E is associated with a globular cluster in the M81 galactic system, thereby confirming that it is 40 times closer than any other known extragalactic FRB (Marcote et al. 2020). Because such globular clusters host old stellar populations, this association challenges FRB models that invoke magnetars formed in a core-collapse supernova as powering FRB emission (e.g. CHIME/FRB Collaboration et al. 2020; Bochenek et al. 2020; Margalit & Metzger 2018; Murase et al. 2016). We propose that FRB 20200120E is a young, highly magnetised neutron star, formed via either accretion-induced collapse of a white dwarf or via merger of compact stars in a binary system. Alternative scenarios are giant pulses from millisecond pulsars and compact binary systems (Pooley et al. 2003), some either interacting through winds, magnetically, or actively accreting via a disc. Given the proximity of FRB 20200120E, our upper limits on associated persistent radio, X-ray and gamma-ray emission tightly constrain the possible source models.
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