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  1. Abstract

    The first fast radio burst (FRB) to be precisely localized was associated with a luminous persistent radio source (PRS). Recently, a second FRB/PRS association was discovered for another repeating source of FRBs. However, it is not clear what makes FRBs or PRS or how they are related. We compile FRB and PRS properties to consider the population of FRB/PRS sources. We suggest a practical definition for PRS as FRB associations with luminosity greater than 1029erg s−1Hz−1that are not attributed to star formation activity in the host galaxy. We model the probability distribution of the fraction of FRBs with PRS for repeaters and nonrepeaters, showing there is not yet evidence for repeaters to be preferentially associated with PRS. We discuss how FRB/PRS sources may be distinguished by the combination of active repetition and an excess dispersion measure local to the FRB environment. We use CHIME/FRB event statistics to bound the mean per-source repetition rate of FRBs to be between 25 and 440 yr−1. We use this to provide a bound on the density of FRB-emitting sources in the local universe of between 2.2 × 102and 5.2 × 104Gpc−3assuming a pulsar-like beamwidth for FRB emission. This density implies that PRS maymore »comprise as much as 1% of compact, luminous radio sources detected in the local universe. The cosmic density and phenomenology of PRS are similar to that of the newly discovered, off-nuclear “wandering” active galactic nuclei (AGN). We argue that it is likely that some PRS have already been detected and misidentified as AGN.

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  2. Abstract We present an analysis of a densely repeating sample of bursts from the first repeating fast radio burst, FRB 121102. We reanalyzed the data used by Gourdji et al. and detected 93 additional bursts using our single-pulse search pipeline. In total, we detected 133 bursts in three hours of data at a center frequency of 1.4 GHz using the Arecibo telescope, and develop robust modeling strategies to constrain the spectro-temporal properties of all of the bursts in the sample. Most of the burst profiles show a scattering tail, and burst spectra are well modeled by a Gaussian with a median width of 230 MHz. We find a lack of emission below 1300 MHz, consistent with previous studies of FRB 121102. We also find that the peak of the log-normal distribution of wait times decreases from 207 to 75 s using our larger sample of bursts, as compared to that of Gourdji et al. Our observations do not favor either Poissonian or Weibull distributions for the burst rate distribution. We searched for periodicity in the bursts using multiple techniques, but did not detect any significant period. The cumulative burst energy distribution exhibits a broken power-law shape, with the lower- andmore »higher-energy slopes of −0.4 ± 0.1 and −1.8 ± 0.2, with the break at (2.3 ± 0.2) × 10 37 erg. We provide our burst fitting routines as a Python package burstfit 4 4 https://github.com/thepetabyteproject/burstfit that can be used to model the spectrogram of any complex fast radio burst or pulsar pulse using robust fitting techniques. All of the other analysis scripts and results are publicly available. 5 5 https://github.com/thepetabyteproject/FRB121102« less
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  4. Abstract We present the localization and host galaxies of one repeating and two apparently nonrepeating fast radio bursts (FRBs). FRB 20180301A was detected and localized with the Karl G. Jansky Very Large Array to a star-forming galaxy at z = 0.3304. FRB20191228A and FRB20200906A were detected and localized by the Australian Square Kilometre Array Pathfinder to host galaxies at z = 0.2430 and z = 0.3688, respectively. We combine these with 13 other well-localized FRBs in the literature, and analyze the host galaxy properties. We find no significant differences in the host properties of repeating and apparently nonrepeating FRBs. FRB hosts are moderately star forming, with masses slightly offset from the star-forming main sequence. Star formation and low-ionization nuclear emission-line region emission are major sources of ionization in FRB host galaxies, with the former dominant in repeating FRB hosts. FRB hosts do not track stellar mass and star formation as seen in field galaxies (more than 95% confidence). FRBs are rare in massive red galaxies, suggesting that progenitor formation channels are not solely dominated by delayed channels which lag star formation by gigayears. The global properties of FRB hosts are indistinguishable from core-collapse supernovae and short gamma-ray bursts hosts, andmore »the spatial offset (from galaxy centers) of FRBs is mostly inconsistent with that of the Galactic neutron star population (95% confidence). The spatial offsets of FRBs (normalized to the galaxy effective radius) also differ from those of globular clusters in late- and early-type galaxies with 95% confidence.« less
  5. ABSTRACT With the upcoming commensal surveys for Fast Radio Bursts (FRBs), and their high candidate rate, usage of machine learning algorithms for candidate classification is a necessity. Such algorithms will also play a pivotal role in sending real-time triggers for prompt follow-ups with other instruments. In this paper, we have used the technique of Transfer Learning to train the state-of-the-art deep neural networks for classification of FRB and Radio Frequency Interference (RFI) candidates. These are convolutional neural networks which work on radio frequency-time and dispersion measure-time images as the inputs. We trained these networks using simulated FRBs and real RFI candidates from telescopes at the Green Bank Observatory. We present 11 deep learning models, each with an accuracy and recall above 99.5 per cent on our test data set comprising of real RFI and pulsar candidates. As we demonstrate, these algorithms are telescope and frequency agnostic and are able to detect all FRBs with signal-to-noise ratios above 10 in ASKAP and Parkes data. We also provide an open-source python package fetch (Fast Extragalactic Transient Candidate Hunter) for classification of candidates, using our models. Using fetch, these models can be deployed along with any commensal search pipeline for real-time candidate classification.
  6. ABSTRACT The analogy of the host galaxy of the repeating fast radio burst (FRB) source FRB 121102 and those of long gamma-ray bursts (GRBs) and superluminous supernovae (SLSNe) has led to the suggestion that young magnetars born in GRBs and SLSNe could be the central engine of repeating FRBs. We test such a hypothesis by performing dedicated observations of the remnants of six GRBs with evidence of having a magnetar central engine using the Arecibo telescope and the Robert C. Byrd Green Bank Telescope (GBT). A total of ∼20 h of observations of these sources did not detect any FRB from these remnants. Under the assumptions that all these GRBs left behind a long-lived magnetar and that the bursting rate of FRB 121102 is typical for a magnetar FRB engine, we estimate a non-detection probability of 8.9 × 10−6. Even though these non-detections cannot exclude the young magnetar model of FRBs, we place constraints on the burst rate and luminosity function of FRBs from these GRB targets.