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Register a new userSynthesizing the repeating FRB population using frbpoppy
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The observed Fast Radio Burst (FRB) population can be divided into one-off and repeating FRB sources. Either this division is a true dichotomy of the underlying sources, or selection effects and low activity prohibit us from observing repeat pulses from all constituents making up the FRB source population. We attempt to break this degeneracy through FRB population synthesis. With that aim we extend frbpoppy, which earlier only handled one-off FRBs, to also simulate repeaters. We next model the Canadian Hydrogen Intensity Mapping Experiment FRB survey (CHIME/FRB). Using this implementation, we investigate the impact of luminosity functions on the observed dispersion measure (DM) and distance distributions of both repeating and one-off FRBs. We show that for a single, intrinsically repeating source population with a steep luminosity function, selection effects should shape the DM distributions of one-off and repeating FRB sources differently. This difference is not yet observed. We next show how the repeater fraction over time can help in determining the repetition rate of an intrinsic source population. We simulate this fraction for CHIME/FRB, and show that a source population comprised solely of repeating FRBs can describe CHIME/FRB observations with the use of a flat luminosity function. From the outcome of these two methods we thus conclude that all FRBs originate from a single and mostly uniform population of varying repeaters. Within this population, the luminosity function cannot be steep, and there must be minor differences in physical or behaviour parameters that correlate with repeat rate.
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Fast Radio Bursts (FRBs) are radio transients of an unknown origin. Naturally, we are curious as to their nature. Enough FRBs have been detected for a statistical approach to parts of this challenge to be feasible. To understand the crucial link between detected FRBs and the underlying FRB source classes we perform FRB population synthesis, to determine how the underlying population behaves. The Python package we developed for this synthesis, frbpoppy, is open source and freely available. Our goal is to determine the current best fit FRB population model. Our secondary aim is to provide an easy-to-use tool for simulating and understanding FRB detections. It can compare surveys, or inform us of the intrinsic FRB population. frbpoppy simulates intrinsic FRB populations and the surveys that find them, to produce virtual observed populations. These resulting populations can then be compared with real data, allowing constrains to be placed on underlying physics and selection effects. We are able to replicate real Parkes and ASKAP FRB surveys, in terms of both detection rates and distributions observed. We also show the effect of beam patterns on the observed dispersion measure (DM) distributions. We compare four types of source models. The Complex model, featuring a range of luminosities, pulse widths and spectral indices, reproduces current detections best. Using frbpoppy, an open-source FRB population synthesis package, we explain current FRB detections and offer a first glimpse of what the true population must be.
The discovery that at least some Fast Radio Bursts (FRBs) repeat has ruled out cataclysmic events as the progenitors of these particular bursts. FRB~121102 is the most well-studied repeating FRB but despite extensive monitoring of the source, no underlying pattern in the repetition has previously been identified. Here, we present the results from a radio monitoring campaign of FRB~121102 using the 76-m Lovell telescope. Using the pulses detected in the Lovell data along with pulses from the literature, we report a detection of periodic behaviour of the source over the span of five years of data. We predict that the source is currently `off and that it should turn `on for the approximate MJD range $59002-59089$ (2020-06-02 to 2020-08-28). This result, along with the recent detection of periodicity from another repeating FRB, highlights the need for long-term monitoring of repeating FRBs at a high cadence. Using simulations, we show that one needs at least 100 hours of telescope time to follow-up repeating FRBs at a cadence of 0.5--3 days to detect periodicities in the range of 10--150 days. If the period is real, it shows that repeating FRBs can have a large range in their activity periods that might be difficult to reconcile with neutron star precession models.
Fast radio bursts (FRBs) are bright, coherent, short-duration radio transients of as-yet unknown extragalactic origin. FRBs exhibit a wide variety of spectral, temporal and polarimetric properties, which can unveil clues into their emission physics and propagation effects in the local medium. Here we present the high-time-resolution (down to 1 $mu$s) polarimetric properties of four 1.7-GHz bursts from the repeating FRB 20180916B, which were detected in voltage data during observations with the European VLBI Network (EVN). We observe a range of emission timescales spanning three orders of magnitude, with the shortest component width reaching 3-4 $mu$s (below which we are limited by scattering). This is the shortest timescale measured in any FRB, to date. We demonstrate that all four bursts are highly linearly polarised ($gtrsim 80%$), show no evidence for significant circular polarisation ($lesssim 15%$), and exhibit a constant polarisation position angle (PPA) during and between bursts. On short timescales ($lesssim 100$ $mu$s), however, there appear to be subtle (few degree) PPA variations across the burst profiles. These observational results are most naturally explained in an FRB model where the emission is magnetospheric in origin, as opposed to models where the emission originates at larger distances in a relativistic shock.
We report the detection of a single burst from the first-discovered repeating Fast Radio Burst source, FRB 121102, with CHIME/FRB, which operates in the frequency band 400-800 MHz. The detected burst occurred on 2018 November 19 and its emission extends down to at least 600 MHz, the lowest frequency detection of this source yet. The burst, detected with a significance of 23.7$sigma$, has fluence 12$pm$3 Jy ms and shows complex time and frequency morphology. The 34 ms width of the burst is the largest seen for this object at any frequency. We find evidence of sub-burst structure that drifts downward in frequency at a rate of -3.9$pm$0.2 MHz ms$^{-1}$. Our best fit tentatively suggests a dispersion measure of 563.6$pm$0.5 pc cm$^{-3}$, which is ${approx}$1% higher than previously measured values. We set an upper limit on the scattering time at 500 MHz of 9.6 ms, which is consistent with expectations from the extrapolation from higher frequency data. We have exposure to the position of FRB 121102 for a total of 11.3 hrs within the FWHM of the synthesized beams at 600 MHz from 2018 July 25 to 2019 February 25. We estimate on the basis of this single event an average burst rate for FRB 121102 of 0.1-10 per day in the 400-800 MHz band for a median fluence threshold of 7 Jy ms in the stated time interval.
Fast Radio Bursts (FRBs) are energetic, short, bright transients that occur frequently over the entire radio sky. The observational challenges following from their fleeting, generally one-off nature have prevented identification of the underlying sources producing the bursts. As the population of detected FRBs grows, the observed distributions of brightness, pulse width and dispersion measure now begin to take shape. Meaningful direct interpretation of these distributions is, however, made impossible by the selection effects that telescope and search pipelines invariably imprint on each FRB survey. Here we show that multi-dimensional FRB population synthesis can find a single, self-consistent population of FRB sources that can reproduce the real-life results of the major ongoing FRB surveys. This means that individual observed distributions can now be combined to derive the properties of the intrinsic FRB source population. The characteristics of our best-fit model for one-off FRBs agree with a population of magnetars. We extrapolate this model and predict the number of FRBs future surveys will find. For surveys that have commenced, the method we present here can already determine the composition of the FRB source class, and potentially even its subpopulations.
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