Observing superluminous supernovae and long gamma ray bursts as potential birthplaces of repeating fast radio bursts
G. H. Hilmarsson, L. G. Spitler, E. F. Keane, T. M. Athanasiadis, E. Barr, M. Cruces, X. Deng, S. Heyminck, R. Karuppusamy, M. Kramer, S. P. Sathyanarayanan, V. Ventakraman Krishnan, G. Wieching, J. Wu, O. Wucknitz
MMNRAS , 1–11 (2019) Preprint 30 September 2020 Compiled using MNRAS L A TEX style file v3.0
Observing superluminous supernovae and long gamma ray bursts aspotential birthplaces of repeating fast radio bursts
G. H. Hilmarsson (cid:63) , L. G. Spitler , E. F. Keane , T. M. Athanasiadis , E. Barr ,M. Cruces , X. Deng , , S. Heyminck , R. Karuppusamy , M. Kramer , ,S. P. Sathyanarayanan , V. Venkatraman Krishnan , G. Wieching , J. Wu O. Wucknitz Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, D-53121 Bonn, Germany SKA Organisation, Jodrell Bank Observatory, Lower Withington, Macclesfield, Cheshire, SK11 9FT, UK CSIRO Astronomy and Space Science, Australia Telescope National Facility, PO box 76, Epping NSW 1710, Australia Jodrell Bank Centre for Astrophysics, University of Manchester, Alan Turing Building, MP13 9PL, UK
Last updated 2015 May 22; in original form 2013 September 5
ABSTRACT
Superluminous supernovae (SLSNe) and long gamma ray bursts (LGRBs) have been proposedas progenitors of repeating Fast Radio Bursts (FRBs). In this scenario, bursts originate fromthe interaction between a young magnetar and its surrounding supernova remnant (SNR). Sucha model could explain the repeating, apparently non-Poissonian nature of FRB121102, whichappears to display quiescent and active phases. This bursting behaviour is better explainedwith a Weibull distribution, which includes parametrisation for clustering. We observed 10SLSNe/LGRBs for 63 hours, looking for repeating FRBs with the Effelsberg-100 m radiotelescope, but have not detected any bursts. We scale the burst rate of FRB121102 to anFRB121102-like source inhabiting each of our observed targets, and compare this rate to ourupper burst rate limit on a source by source basis. By adopting a fiducial beaming fractionof 0.6, we obtain 99.99% and 83.4% probabilities that at least one, and at least half of ourobserved sources are beamed towards us respectively. One of our SLSN targets, PTF10hgi,is coincident with a persistent radio source, making it a possible analogue to FRB121102.We performed further observations on this source using the Effelsberg-100 m and Parkes-64 m radio telescopes. Assuming that PTF10hgi contains an FRB121102-like source, theprobabilities of not detecting any bursts from a Weibull distribution during our observationsare 14% and 16% for Effelsberg and Parkes respectively. We conclude by showing that asurvey of many short observations increases burst detection probability for a source withWeibull distributed bursting activity.
Key words: transients: fast radio bursts – transients: gamma-ray bursts – transients: supernovae– methods: observational
Fast Radio Bursts (FRBs) are bright, highly dispersed, millisecond-duration radio transients of unknown origin. Since their inauguraldetection (Lorimer et al. 2007), close to 100 FRB discoveries havebeen published (Petroff et al. 2016). FRBs are believed to be ex-tragalactic due to their high dispersion measures (DM), which farexceed the expected Galactic DM contribution. This belief has stren-thened as FRBs have been increasingly localized to host galaxies(Chatterjee et al. 2017; Bannister et al. 2019; Ravi et al. 2019; (cid:63) E-mail: [email protected] frbcat.org Prochaska et al. 2019; Marcote et al. 2020). While most FRBs de-tected so far have been single events, FRB121102 was the first tobe seen to repeat (Spitler et al. 2016), and recently nine repeatingFRBs have also been detected at CHIME (CHIME/FRB Collabora-tion et al. 2019; The CHIME/FRB Collaboration et al. 2019). Therepeating nature of some FRBs suggest that there are possibly twopopulations of FRBs, repeating and non-repeating.FRB121102 has been localized to a host galaxy (Michilli et al.2018), and its host identified as a low-metallicity dwarf galaxy at aredshift of z = . ∗ ∼ . × M (cid:12) and a star formation rate of 0.23 M (cid:12) peryear (Bassa et al. 2017). A compact persistent radio source witha projected size of < 0.7 pc was detected alongside FRB121102 © 2019 The Authors a r X i v : . [ a s t r o - ph . H E ] S e p G. H. Hilmarsson et al. (Marcote et al. 2017) and was determined to be co-located to withina projected distance of < 40 pc to the bursting source.Evidence for coincidence between FRB121102 and the persis-tent radio source, along with the identification of the host galaxy,led to the suggestion of two types of progenitor models: a magnetarwind nebula containing a young magnetar, embedded within a su-pernova remnant (SNR) (Metzger et al. 2017); or a low luminosityactive galactic nucleus (AGN) acting as the persistent radio source,with the bursting activity either originating from the AGN itself(Romero et al. 2016), or through interaction with a nearby neutronstar (NS) (e.g. Zhang 2018a). In the case of FRB121102, the AGNmodel was initially thought unlikely, as dwarf galaxies rarely con-tain AGNs, along with the fact that no evidence of an AGN in theoptical spectrum was observed (Tendulkar et al. 2017). However,a recent survey has shown that AGNs can be found offset fromthe optical center of dwarf galaxies (Reines et al. 2020). Addition-ally, the recently observed large and decreasing rotation measures(RMs) of FRB121102 ( ∼ rad/m ) (Michilli et al. 2018), havedrawn analogies between the system and the Galactic center mag-netar, J1745-2900 ( ∼ − ) and Sagittarius A* system(Desvignes et al. 2018).Supernovae occur from the collapse of massive stars into blackholes (BHs) or NSs. In some rare cases the remnant BH or NS pow-ers a relativistic jet into the circumstellar medium (Woosley 1993),and internal shocks within these jets can produce long gamma-raybursts (LGRBs) (Rees & Meszaros 1994). Type-I superluminous su-pernovae (SLSNe) are a subclass of supernovae which are hydrogenpoor, orders of magnitude more luminous, have shorter decay timesthan the typical Type-I supernovae, and have been postulated to bethe precursor of LGRBs (Gal-Yam 2019). The high luminosity ispowered by a newly-born magnetar, where the magnetar spin-dowonrate is tied to the short decay time (Greiner et al. 2015). In additionto producing a fast-spinning NS with a strong magnetic field thatcould produce more luminous radio bursts than Galactic NSs, Type-I SLSNe and the resulting LGRBs also seem to occur more oftenin low-mass, low-metallicity galaxies (Fruchter et al. 2006; Perleyet al. 2016). Type-I SLSNe and LGRBs can therefore explain therepeating nature of FRB121102 and its coincident persistent radiosource. Note that throughout this paper, any mention of SLSNe isexclusively referring to Type-I SLSNe.For FRB121102, the persistent radio source’s luminosity isconsistent with a model of radio emission from an SNR which ispowered by a young magnetar (Metzger et al. 2017). A radio burstcould therefore originate from the magnetosphere of such a mag-netar in a similar fashion to pulsar giant pulses (Cordes & Wasser-man 2016). Similarities in burst properties between FRB121102and the Crab pulsar have been observed, although whether giantpulses from the Crab can be scaled to the energies of FRB121102is unclear (see Hessels et al. 2019, and discussion therein). Alter-natively, Metzger et al. (2019) have modelled FRBs as synchrotronmaser emissions from within an SNR. In that scenario, a central en-gine releases ultrarelativistic particles which collide with a mildlyrelativistic magnetized ion-electron shell. The deceleration of theshell through forward shocks would then produce FRBs through asynchrotron maser mechanism. Metzger et al. (2019) illustrate bothproduction of FRBs within a large frequency range, 0.1–10 GHz,and the apparently dormant and clustering phases of bursts observedfrom FRB121102.Shortly after the explosion, an SNR is optically thick at radiofrequencies, so radio bursts from an embedded magnetar cannotbe detected. If the SNR is mainly ionized by the reverse shock, itcan be probed at radio frequencies after a timescale of centuries (Piro 2016). However, assuming that along with the reverse shockof the supernova ejecta, the SNR is photoionized from within bythe magnetar, the SNR becomes optically thin at the frequency ofthe bursting emission after t ≈ ν − / yrs (Metzger et al. 2017).At 1.4 and 6 GHz, t is 8.7 and 4.9 yrs respectively, in the emittedframe.In this work we have identified and observed nine SLSNe andLGRBs as suitable sources for a targeted repeating FRB search athigh frequencies (5.3–9.3 GHz) with the Effelsberg 100-m RadioTelescope. The motivation for choosing this frequency range is thatthe SNR model allows for younger, and hence more, sources to beobservable; and that FRB121102 has been observed to emit at thesefrequencies (Gajjar et al. 2018). We later added PTF10hgi to our5.3–9.3 GHz survey and observed it during commissioning time forthe phased array feed (PAF) receiver at Effelsberg at 1.4 GHz andwith the ultra wideband low (UWL) Parkes 64-m Radio Telescopereceiver (0.7–4.0 GHz). This addition was made following the dis-covery of a radio source coincident with the SLSN PTF10hgi at6 GHz with the VLA (Eftekhari et al. 2019). This is the first de-tection of a persistent radio source coincident with SLSNe/LGRBs,and it could be analogous to FRB121102’s persistent radio source.If an FRB were to be detected from PTF10hgi it would prove the the-orised connection between FRBs and SLSNe/LGRBs. Additionally,the age of PTF10hgi was roughly nine years at the time of observ-ing, so its SNR should be only recently optically thin at 1.4 GHz.With our wide range of frequencies we could potentially observethe optically thick-thin transition of the SNR.Similar surveys have been performed recently: Law et al.(2019) observed 10 SLSN using the Karl G. Jansky Very LargeArray (VLA) for 8.5 hrs at 3 GHz, where they managed to detectedthe persistent radio source of PTF10hgi in their radio image search-ing. Men et al. (2019) observed five LGRBs and one short GRB for20 hrs using the Robert C. Byrd Green Bank Telescope (GBT) at820 MHz and 2 GHz, and the Arecibo Radio Telescope at 1.4 GHz.Madison et al. (2019) observed six short GRBs, which originatefrom the merger of neutron stars and could leave behind a magnetarcapable of producing repeating FRBs, for 20 hrs using the GBT at2 GHz and Arecibo at 1.4 GHz. No FRBs were detected in thesesurveys. Our obsevations were carried out using The Effelsberg 100-m RadioTelescope in Effelsberg, Germany; and The Parkes 64-m RadioTelescope in New South Wales, Australia. The receivers used atEffelsberg were the S45mm single pixel receiver, and the PAF;and at Parkes, the UWL receiver. These will be described in theirrespective subsections below.The selection process for our targets was as follows. A listof SLSNe and LGRBs was gathered from the Open SupernovaCatalog (Guillochon et al. 2017) and the Swift GRB Catalog with each source being older than five years, and at a maximumredshift of 0.4. The age cut-off was conservatively set to five yearsto include only SNRs which are optically thin in the observing bandof the receiver. The redshift limit was set with respect to detectionsof FRB121102 at Effelsberg: By combining the radiometer equation(Dicke 1946) and the brightness drop-off of the inverse square law, https://sne.space https://swift.gsfc.nasa.gov/archive/grb_table.html MNRAS , 1–11 (2019)
LSNe/LGRBs as birthplaces of FRBs it follows that a detection with a signal to noise (S/N) of 40 at aredshift z = . z = . dspsr from the pulsar analysis software library psrchive . For42.3 of our total 63 observing hours, we observed our original ninetargets with the S45mm receiver for 1–2 hrs each time with a ∼ = DM MW + DM MWhalo + DM IGM + DM host , (1)where DM MW and DM MWhalo are the DM contribution of the MilkyWay (MW) and its halo, respectively, DM
IGM is the contributionof the intergalactic medium (IGM), and DM host is the contributionof the host galaxy and the local environment of the source. TheDM MW varies between different lines of sight (LoS), but in generaldoes not exceed 100 pc cm − for LoSs away from the Galacticplane, which is the case for most of our targets. Using the Galacticelectron density model YMW16 (Yao et al. 2017), we obtain DM MW values between 22 and 143 pc cm − for our targets. We assume aDM MWhalo value of 50–80 pc cm − (Prochaska & Zheng 2019).To estimate the DM IGM we use the relation z ∼ DM /
855 pc cm − (Zhang 2018b) reulting in a DM IGM range of 66-311 pc cm − . Theestimated DM IGM from recent FRB localisations are in agreementwith this relation (Bannister et al. 2019; Ravi et al. 2019). Note thatLoS variations might vary from 100 to 250 pc cm − for DM IGM for our redshift range depending on models for halos’ gas profile ofionized baryons (McQuinn 2014, Fig. 1, bottom panel). The DM host component can vary between FRB progenitor models, types of hostgalaxies and local environments, orientation of the host galaxy,and the LoS to the source through its host (Walker et al. 2018).The DM host estimate for FRB121102 is in the range of 55–225 pccm − (Tendulkar et al. 2017). Using this range for our DM host , theestimated total DM of our targets falls in the range of 220–700 pccm − . The S45mm receiver is located in the secondary focus of The Effels-berg Telescope, and yields 4 GHz of bandwidth between either 4–8GHz or 5.3–9.3 GHz. The receiver has an SEFD of 18 Jy. All theobservations made using this receiver in this work are in the 5.3–9.3GHz mode, except for the observations of PTF10hgi, which weretaken in the 4–8 GHz mode. The data are recorded with full Stokesusing two ROACH2 backends, each capturing 2 GHz of the band, http://psrchive.sourceforge.net/ with a 131 µ s sampling rate, and a 0.976562 MHz channel band-width across 4096 channels. The resultant data are in a DistributedAquisition and Data Analysis (DADA) format , from which Stokes I is extracted.During the observaion on 22nd October 2018, a problem oc-curred with the S45mm receiver, resulting in poor attenuation levelsmaking the receiver temporarily inoperable, and the use of a dif-ferent receiver was needed. The S60mm receiver on Effelsberg wasused instead, with 500 MHz of bandwidth at 4.6–5.1 GHz, 82 µ ssampling rate, 512 channels with 0.976562 MHz bandwidth, andan SEFD of 18 Jy. The data are recorded as sub-banded SIGPROC filterbanks, which are a stream of n-bit numbers corresponding tomultiple polarization and/or frequency channels over time, and areconcatenated before processing. The Effelsberg PAF (Deng et al. 2018) is a dense array of antennaelements installed at the telescope’s primary focus, adapted from themodels used by ASKAP (Hay & O’Sullivan 2008; Johnston et al.2008). Its 188 elements form a checkerboard shape over a 1.2 mdiameter circle and the output of these elements are combined toform beams, controlled by varying the element weights.In its current state, the Effelsberg PAF can produce 22 beams,with 230 MHz of bandwidth centered at 1337 MHz, and an SEFD of34 Jy. Currently the data are recorded and stored on disk as total in-tensity DADA files with 512 channels of 0.449074 MHz bandwidtheach, and a 216 µ s sampling time. The data can also be recorded asbaseband data. This will be used in future surveys for real-time pro-cessing, where we will use the raw voltage data captured from a ringbuffer to create full Stokes files with significantly higher frequencyand time resolutions than our standard filterbanks. The UWL receiver (Dunning et al. 2015) is a wideband receiverat the Parkes telescope with an SEFD of 25 Jy. It has a bandwidthof 3.3 GHz, ranging from 0.7 to 4 GHz. The data were recordedin two different modes with the MEDUSA backend: full Stokes,with a sampling time of 1024 µ s and a channel bandwdith of 2MHz across 1664 channels for the first observation; and Stokes I ,with a sampling time of 256 µ s and 0.5 MHz channel bandwidthacross 6656 channels for the latter two observations. The 256 µ sdata were downsampled by a factor of four for consistency and toreduce computation time during analysis. The data are in a PulsarFlexible Image Transport System (PSRFITS) format (Hotan et al.2004). All data products are initially converted to SIGPROC filterbankformat before being processed. For the S45mm, S60mm, and UWLdata, the
PRESTO (Ransom 2011) software package was used forsingle pulse searching. We used PRESTO ’s rfifind to identify radiofrequency interference (RFI) in the data and create an RFI mask toapply to the data. The data were dedispersed from 0–2000 pc cm − in steps of 2 pc cm − for the S45mm and S60mm data, and in steps http://psrdada.sourceforge.net http://sigproc.sourceforge.net github.com/scottransom/presto MNRAS000
PRESTO (Ransom 2011) software package was used forsingle pulse searching. We used PRESTO ’s rfifind to identify radiofrequency interference (RFI) in the data and create an RFI mask toapply to the data. The data were dedispersed from 0–2000 pc cm − in steps of 2 pc cm − for the S45mm and S60mm data, and in steps http://psrdada.sourceforge.net http://sigproc.sourceforge.net github.com/scottransom/presto MNRAS000 , 1–11 (2019)
G. H. Hilmarsson et al.
Table 1.
Properties of the observed SLSNe/LGRBs.
From left to right : Source name, discovery date, right ascension (RA) and declination (DEC) in J2000coordinates, sources redshift ( z ), the type of source, i.e. whether it’s an LGRB or SLSN, and the average estimated total DM (pc cm − ).Source name Discovery date RA DEC z Type DM [pc cm − h m s -02 ◦ (cid:48) (cid:48)(cid:48) h m s +38 ◦ (cid:48) (cid:48)(cid:48) h m s +51 ◦ (cid:48) (cid:48)(cid:48) h m s +51 ◦ (cid:48) (cid:48)(cid:48) h m s +47 ◦ (cid:48) (cid:48)(cid:48) h m s +67 ◦ (cid:48) (cid:48)(cid:48) h m s -08 ◦ (cid:48) (cid:48)(cid:48) h m s +46 ◦ (cid:48) (cid:48)(cid:48) h m s -21 ◦ (cid:48) (cid:48)(cid:48) h m s +06 ◦ (cid:48) (cid:48)(cid:48) Table 2.
List of observations in a chronological order for each source.
From left to right : Source name, the dates and starting times for each observation (inUTC and MJD), observation duration, and the frequency range of the observation.Source name UT Date UTC MJD Duration [min] Frequency [GHz]GRB050826 20170630 11:18:41 57934.47131 58 5.3–9.3GRB050826 20171128 22:21:04 58085.93130 147 5.3–9.3GRB050826 20180330 16:31:30 58207.68854 120 5.3–9.3GRB050826 20181023 00:46:50 58414.03252 60 4.6–5.1GRB050826 20181023 04:08:30 58414.17257 60 4.6–5.1GRB051109B 20171128 16:03:34 58085.66194 120 5.3–9.3GRB051109B 20180330 09:23:50 58207.39155 90 5.3–9.3GRB051109B 20181022 17:00:20 58413.70856 60 4.6–5.1GRB111225A 20171128 18:12:54 58085.75896 120 5.3–9.3GRB111225A 20180330 11:06:51 58207.46309 46 5.3–9.3GRB111225A 20180330 18:35:50 58207.77488 51 5.3–9.3GRB111225A 20181022 18:12:00 58413.75833 60 5.3–9.3PTF09cnd 20170630 13:21:01 57934.55626 48 5.3–9.3PTF09cnd 20180330 05:11:30 58207.21632 120 5.3–9.3PTF09cnd 20181022 22:37:30 58413.94271 60 4.6–5.1PTF10uhf 20170630 15:17:01 57934.63682 55 5.3–9.3PTF10uhf 20180330 07:17:50 58207.30405 120 5.3–9.3PTF10uhf 20181022 21:36:40 58413.90046 60 4.6–5.1PTF10bjp 20170630 12:27:31 57934.51911 48 5.3–9.3PTF10bjp 20171129 01:26:14 58086.05988 120 5.3–9.3PTF10bjp 20180330 01:01:20 58207.04259 120 5.3–9.3PTF10bjp 20180330 14:08:10 58207.58900 18 5.3–9.3PTF10bjp 20181022 19:31:50 58413.81377 60 4.6–5.1SN2010gx 20171129 04:41:44 58086.19565 14 5.3–9.3SN2010gx 20180329 22:57:00 58206.95625 120 5.3–9.3PTF12dam 20170630 14:23:11 57934.59943 50 5.3–9.3PTF12dam 20171129 03:38:04 58086.15144 60 5.3–9.3PTF12dam 20180330 03:09:40 58207.13171 120 5.3–9.3PTF12dam 20181022 20:35:00 58413.85764 60 4.6–5.1LSQ12dlf 20171128 20:17:54 58085.84576 120 5.3–9.3LSQ12dlf 20180330 12:01:00 58207.50069 120 5.3–9.3LSQ12dlf 20181022 23:43:40 58413.98866 60 4.6–5.1PTF10hgi 20190205 18:48:31 58519.78369 42 0.7–4PTF10hgi 20190210 02:24:52 58524.10060 155 4–8PTF10hgi 20190220 20:15:55 58534.84439 44 0.7–4PTF10hgi 20190308 01:14:42 58550.05187 160 4–8PTF10hgi 20190323 23:54:29 58565.99618 216 1.222-1.452PTF10hgi 20190324 22:54:32 58566.95454 236 1.222-1.452PTF10hgi 20190325 23:18:01 58567.97085 90 1.222-1.452PTF10hgi 20190326 23:11:26 58568.96627 236 1.222-1.452PTF10hgi 20190830 05:05:15 58725.21198 55 0.7–4 MNRAS , 1–11 (2019)
LSNe/LGRBs as birthplaces of FRBs of 1 pc cm − for the UWL data, and subsequently searched forsingle pulses using PRESTO ’s single_pulse_search.py with aS/N threshold of 7. PRESTO searches for single pulses by dedispersing the data andconvolving the dedispersed time series with boxcar filters of varyingwidths to optimise the S/N.
PRESTO uses a pre-determined list ofboxcar widths to use, so by setting a maximum candidate width,
PRESTO will search using boxcars up to that width. We search upto the nearest boxcar width of 20 ms, which is 19.6 ms. We set thislimit as FRBs tend not to have widths greater than a few ms at ourobserved frequencies, and 20 ms is roughly the DM sweep in theS45mm band for the lower limit of the estimated DMs of our targets.We also compute the spectral modulation index of the candi-dates, which evaluates the fractional variation of a candidate acrossits spectrum and distinguishes narrowband RFI from broadband sig-nals (Spitler et al. 2012). The candidate’s modulation index, m I , iscalculated as the normalized standard deviation of intensity acrossfrequency, and must be below the modulation index threshold, m I , threshold = √ N ν ( S / N ) min , (2)where N ν is the number of frequency channels, and ( S / N ) min isthe signal to noise threshold applied to the data. The candidateswere then plotted and analysed by eye with a DM over time plotwith marker sizes increasing with S/N. Promising candidates werefurther inspected using PRESTO ’s waterfaller.py plotting tool,which shows the the candidate’s dynamic spectrum and can bedownsampled and subbanded at will.For the PAF data, the GPU based single pulse search software HEIMDALL was used. This was done to handle the vast amountof multibeam data taken, and to exploit HEIMDALL ’s coincidencingcapabilities.
HEIMDALL ’s single pulse searching uses the same con-volution method as
PRESTO , but achieves much greater processingspeeds by utilising GPUs rather than CPUs. For the Effelsberg PAF,every frequency channel is calibrated independently, and channelsaffected by RFI stronger than the calibration source have undefinedpointing positions, resulting in so-called badly beamformed chan-nels. A considerable portion of the channels in the PAF data neededto be zapped during the processing due to both badly beamformedchannels, and channels persistently contaminated with RFI. Thesechannels amounted to 89 MHz, or 39% of the PAF band, and wereflagged to be ignored by
HEIMDALL . The data were dedispersedfrom 0–2000 pc cm − . The DM steps in HEIMDALL are determinedby the pulse broadening induced by the size of the DM step, soeach DM trial is a function of the previous DM value and the dataparameters (Levin 2012). An initial detection threshold of S/N = HEIMDALL groups candidates which are close in DMand time, and the group’s candidate with the highest S/N is thecandidate given by
HEIMDALL . This multi-beam data needed to becoincidenced in order to identify false candidates appearing acrossmany beams simultaneously, so the single pulse candidates wereran through
HEIMDALL ’s coincidencer . The candidates were thensifted further in order to reduce the large number of false positiveswith low DMs and large widths: an increased S/N threshold of 8, alow DM threshold of 20 pc cm − , and a maximum candidate widthof 28 ms were applied. In addition, candidates detected in mulit-ple beams go through further sifting. By taking the beam with thestrongest S/N as the reference point, the other beam detections needto occur within the adjacent beams for the candidate to pass the sourceforge.net/projects/heimdall-astro sifting. The remaining candidates were then run through our ownplotting tool which plots dedispersed time series, dynamic spec-trum, and a dedispersed dynamic spectrum. The dynamic spectracan also be downsampled and subbanded by factors of our choosing.These plots were then inspected by eye.We are aware of potential difficulties due to the DM sweepacross the 4–8 GHz band. For a DM of 500 pc cm − the sweepis 50 ms, so a narrowband signal might be difficult to distinguishfrom zero-DM RFI. At the start of each observation we do howeverobserve the pulsar B0355+54, which has a DM of 57 pc cm − , andare able to detect its single pulses. From the 63 hours of observational data, we have not detected anysingle pulses from any of the sources observed above our fluencelimits of 0.04 ( w ms / ms ) / Jy ms for the S45mm receiver, 0.53 ( w ms / ms ) / Jy ms for the PAF receiver, and 0.07 ( w ms / ms ) / Jyms for the UWL receiver, for burst widths of w ms ms.Assuming Poissonian statistics, we can estimate the upper-limit to the rate of bursts emitted above our detection thresholdon a source-by-source basis (Gehrels 1986, Table 1). We also esti-mate the burst rate of an FRB121102-like source from each of theSLSNe/LGRBs observed. The C-band results from the observedSLSNe/LGRBs and the PTF10hgi results with the PAF and UWLreceivers are shown in their respective following subsections.To estimate the rate of an FRB121102-like source at differentlocations we make use of a brightness distribution power-law, R = R (cid:18) EE (cid:19) γ , (3)where R and E are the rate and energy, respectively, R and E arevalues for a reference source, and γ is the FRB brightness distribu-tion power-law index. Here we use γ = − . ± .
17 as estimatedby James (2019) independently of instrumental sensitivity by com-bining the multi-telescope observing campaign of FRB121102 (1.4and 3 GHz, Law et al. 2017) and the GBT BL observations (6 GHz,Gajjar et al. 2018). An index of γ = − . ± . γ are inconsistent with each other, poten-tially due to Arecibo’s survey probing unprecedentedly low burstenergies of FRB121102, or its high sensitivity (Gourdji et al. 2019).We choose γ = − . ± .
17 because the sensitivity of Effelsbergis closer to GTB and VLA than Arecibo, and this value is partiallyderived from detections in C-band.The rate calculation also requires a relation between fluenceand energy of a transient, considered specifically for the case ofFRBs as Macquart & Ekers (2018) F ( ν ) = ( + z ) + α ∆ ν FRB E π D L , (4)where ∆ ν FRB is the intrinsic bandwidth of an FRB, z is the source’sredshift, α is the spectral index, E is the total energy of a burst, and D L is the luminosity distance to the bursting source. The spectralindex for FRBs is not well constrained, and given the absence ofinformation we assume a flat spectrum with α = github.com/ghenning/PAFcode MNRAS000
17 because the sensitivity of Effelsbergis closer to GTB and VLA than Arecibo, and this value is partiallyderived from detections in C-band.The rate calculation also requires a relation between fluenceand energy of a transient, considered specifically for the case ofFRBs as Macquart & Ekers (2018) F ( ν ) = ( + z ) + α ∆ ν FRB E π D L , (4)where ∆ ν FRB is the intrinsic bandwidth of an FRB, z is the source’sredshift, α is the spectral index, E is the total energy of a burst, and D L is the luminosity distance to the bursting source. The spectralindex for FRBs is not well constrained, and given the absence ofinformation we assume a flat spectrum with α = github.com/ghenning/PAFcode MNRAS000 , 1–11 (2019)
G. H. Hilmarsson et al.
FRB121102 have smaller fractional bandwidth (Hessels et al. 2019,Fig. 1), so Eq. 4 can be written as the observed fluence averagedacross the observing band, ∆ ν , (James 2019, Eq. 8) F = ( + z ) ∆ ν E π D L . (5)We can then estimate the rate of bursts from FRB121102-like sources located at different luminosity distances/redshifts, forsurveys with different sensitivities by combining eqs. 3 and 5: R = R (cid:18) FF (cid:19) γ (cid:18) + z + z (cid:19) γ (cid:18) D L D L , (cid:19) γ (cid:18) ∆ ν ∆ ν (cid:19) γ , (6)with the subscripts of 0 being the values for FRB121102, and F being the fluence limit. The 95% confidence level (CL) upper-limit to the burst rates weobtain from our observations, assuming Poissonian statistics, are inthe range of 0.4–1.4 bursts/hr and are shown in Table 3 and Fig. 1.Observing campaigns of FRB121102 at high frequencies havereported various average burst rates. Gajjar et al. (2018) reported21 detections in a single 6 hr observation at the Green Bank Tele-scope (GBT) using the 4–8 GHz Breakthrough Listen (BL) DigitalBackend. Spitler et al. (2018) have three detections in 22 hrs withthe 4.6–5.1 GHz, S60mm receiver at Effelsberg in an observingcampaign spanning 4 months.We also have obtained a rate of 0.012 + . − . bursts/hr (1 σ error) from an ongoing campaign using the 4–8 GHz, S45mmreceiver at Effelsberg (Hilmarsson et al. 2020). In that campaign,which yields a single detection from 86 hrs of observations spanningtwo years, FRB121102 is observed for 2–3 hours at a time with aroughly two week cadence (with gaps due to telescope/receivermaintenance). This rate is more robust than previously reportedrates in the sense that it is a long-term average consisting of multipleobservations, and does not depend on a single bursting phase. It isalso obtained using the same observational setup as in this work.Using the burst rate of FRB121102 from Hilmarsson et al.(2020) of 0.012 + . − . bursts/hr, we estimate the burst rate of anFRB121102-like source located at each of the SLSNe/LGRBs ob-served. Since we are working with the same observational setupand identical bursts at different locations, we can simplify Eq. 6 bysetting ( F / F ) γ and ( ∆ ν / ∆ ν ) γ to 1: R = R (cid:18) + z + z (cid:19) γ (cid:18) D L D L , (cid:19) γ . (7)The hypothetical rate of an FRB121102-like source located atour sources of interest can be found in Table 3, and is shown inFig. 1. There we have also estimated the number of bursts we wouldhave expected to see from an FRB121102-like source during ourobservations, as well as how long we need to observe each sourcewithout a detection in order to constrain our estimated rates, i.e. theobservation time required for the upper limit to the rate to reach thescaled rate.The scaled rates from FRB121102 are influenced by thedifference in luminosity distance between FRB121102 and theSLSNe/LGRBs, yet they do fall within the 1 σ range of FRB121102’srate at C-band. This also implies that the time needed to constrain the All uncertainties in burst rates reported here are 1 σ errors. Figure 1.
Scaled burst event rates of the observed sources at C-band.
Graybar : 1 σ burst event rate range of FRB121102 at C-band. Black dots : Scaledburst event rate of an FRB121102-like source located at our SLSNe/LGRBstargets.
Red arrows : 95% CL upper limit rates based on the non-detectionof our observations. scaled rates reaches impractical observation times for most of thesources (upwards of 300 hours). However, three of our sources,GRB051109B, PTF12dam, and PTF10hgi, have luminosity dis-tances less than FRB121102, and therefore have a higher scaledrate than FRB121102. Since no bursts were detected in this work,constraining the scaled rates of these three sources is quite a feasibletask for further surveys.
We repeat the analysis from the previous section for the 13 hrs ofPTF10hgi data taken with the PAF and the 2.3 hrs taken with theUWL. In order to do so, we use the rate from a recent FRB121102survey (28 bursts in 116 hrs) performed at L-band using the P217mm7-beam (SEFD =
17 Jy) receiver at the Effeslberg telescope. Theaverage burst rate is 0.24 + . − . bursts/hr above a fluence of 0.14 ( w ms / ms ) / Jy ms (Cruces et al. 2020).This rate must to be scaled to the PAF and UWL receivers,which we do using Eq. 6. For the factor of ( F / F ) γ we use theradiometer equation (Dicke 1946) F = SEFD S/N (cid:112) n p ∆ ν √ w , (8)where SEFD is the system equivalent flux density, S/N is the sig-nal to noise, n p is the number of polarizations, ∆ ν is the receiverbandwidth, and w is the burst width. The rate conversion from Eq.6 then becomes R = R (cid:18) SEFDSEFD (cid:19) γ (cid:18) ∆ ν ∆ ν (cid:19) γ / (cid:18) + z + z (cid:19) γ (cid:18) D L D L , (cid:19) γ , (9)where the last two bracketed terms are equal to 1 when con-verting rates for the same source. The FRB121102 burst ratescaled to the PAF and UWL receivers is 0 . + . − . bursts/hr above0.53 ( w ms / ms ) / Jy ms, and 0 . + . − . bursts/hr above 0.07 ( w ms / ms ) / Jy ms respectively. Note that we are scaling burstenergies to different observing bandwidths, so under the assump-tion that R ( E ) does not depend on the central frequency of theobserving bandwidth we add an additional term of ( ∆ ν / ∆ ν ) to Eq.9 when scaling from the P217mm receiver to the PAF and UWLreceivers.The resulting rate, obtained by using Eq. 9, for an FRB121102-like source located at PTF10hgi is 0 . + . − . bursts/hr for the PAF MNRAS , 1–11 (2019)
LSNe/LGRBs as birthplaces of FRBs Table 3.
Results from the burst rate analysis of the observed sources.
From left to right : The observing band, source name, total observing time ( T obs. ), 95%confidence (CL) upper rate limit ( R UL ), luminosity distance ( D L ), the scaled burst rate from an FRB121102-like source ( R FRB121102 ), the expected number ofbursts from our observations based on the scaled rates ( N exp. ), and the observing time required to constrain the scaled rate ( T constr. ; i.e. the time needed for the95% CL upper rate limit to reach the scaled rate). The luminosity distance and burst rate of FRB121102 are added for reference. Top : S45mm receiver results.
Center : PAF receiver results.
Bottom : Parkes UWL results.Obs. band [GHz] Source name T obs [hr] R UL [hr − ] D L [Mpc] R FRB121102 [hr − ] N exp T constr [hr]4–8 FRB121102 - - 950 0.012 + . − . - -GRB050826 7.4 0.41 1550 0.01 0.04 582GRB051109B 4.5 0.67 370 0.06 0.27 50GRB111225A 4.6 0.65 1550 0.01 0.02 582PTF09cnd 3.8 0.79 1320 0.01 0.03 447PTF10uhf 3.9 0.77 1500 0.01 0.02 550PTF10bjp 6.1 0.49 1930 0.01 0.02 831SN2010gx 2.2 1.4 1150 0.01 0.02 358PTF12dam 4.8 0.62 500 0.03 0.17 85LSQ12dlf 5 0.60 1270 0.01 0.04 420PTF10hgi 5.3 0.57 460 0.04 0.21 731.2–1.4 FRB121102 - - 950 0.11 + . − . - -PTF10hgi 13.0 0.41 a
460 0.4 + . − . a + . − . - -PTF10hgi 2.3 2.26 a
460 2.2 + . − . aa receiver, and 2 . + . − . bursts/hr for the UWL receiver. From the 13hour observations with the PAF, we would have expected to detect4–7 bursts on average by assuming this rate. We exclude this rateat the 99% confidence level for such a source inhabiting PTF10hgi.Likewise, for the 2.3 hour observations with the UWL receiver wewould have expected 4–6 bursts on average, and exclude this rateat the 99% confidence level. The results are shown in the bottomsection of Table 3 and in Fig. 2.The fact that we do not detect any bursts and rule out the rate ofan FRB121102-like source with a Poissonian distributed burstingactivity inhabiting PTF10hgi can be interpreted in various ways: i) The most straightforward reason is that PTF10hgi simply doesnot contain a repeating FRB source, or at the very least not a sourceas active as FRB121102, as FRB121102 might be an abnormallyactive bursting source (e.g. Palaniswamy et al. 2018). ii)
The as-sumption that FRBs are related to young magnetars within SNRsmight not be correct. iii)
The FRB121102-like source may have beenobserved during a quiescent state, so no bursts were emitted duringour observations. If this were the case, it would directly imply thatthe bursting activity of the source is non-Poissonian. iv)
PTF10hgi’sage was roughly nine years at the time of the observations, so theSNR could be at the threshold of being optically thin at 1.4 GHz(Metzger et al. 2017). The SNR could simply still be opaque at1.4 GHz, meaning that we cannot observe emitted bursts at thatfrequency, given that the emission has to travel through the SNR. v) The emission might be beamed and the bursts were not beamedtowards us at the time of observing, so we were unable to detectbursts from the source.
Emission mechanisms that generate luminous radio emissions aregenerally beamed, so a beaming fraction for our model should betaken into consideration. The beaming fraction, f , is the fractionof the celestial sky covered by the radio beam, and in the case ofrotation it is how much is covered during a single rotation. Figure 2.
Scaled burst event rates of PTF10hgi for different receivers.
Gray bars : 1 σ burst event rate range of FRB121102 at receiver. Black dots :Scaled burst event rate of an FRB121102-like source located at PTF10hgi.
Red/Green arrows : 95/99.5% CL upper limits to the rates.
The coherent emission process by a single unit (particle orbunch of particles) has a beaming opening angle of 1 / γ p , where γ p is the Lorentz factor of the unit. Cordes & Chatterjee (2019) discussthree possibilities of FRB beaming geometries. First is a relativisticjet comprised of emission from multiple incoherent units, and whosebeaming is thus much greater than from the coherent emission of asingle unit. Second is a relativistic jet rotating around an axis, wherethe beam sweeps out an annulus shaped area during each revolution,similar to pulsars. Third is quasi-isotropic emission from a sphericalshell.Within the magnetar model framework, two distinct locationsof emission have been discussed in the literature: a synchrotronmaser mechanism from relativistic shocks in the material surround-ing the magnetar (Lyubarsky 2014; Beloborodov 2017), and pulsar-like emission in the magnetosphere (Kumar et al. 2017; Yang &Zhang 2018). Metzger et al. (2019) model a synchrotron maser in abaryon-loaded shell that can produce bursts over the full area of theSNR, relating to the aforementioned third beaming gemoetry. The MNRAS000
The coherent emission process by a single unit (particle orbunch of particles) has a beaming opening angle of 1 / γ p , where γ p is the Lorentz factor of the unit. Cordes & Chatterjee (2019) discussthree possibilities of FRB beaming geometries. First is a relativisticjet comprised of emission from multiple incoherent units, and whosebeaming is thus much greater than from the coherent emission of asingle unit. Second is a relativistic jet rotating around an axis, wherethe beam sweeps out an annulus shaped area during each revolution,similar to pulsars. Third is quasi-isotropic emission from a sphericalshell.Within the magnetar model framework, two distinct locationsof emission have been discussed in the literature: a synchrotronmaser mechanism from relativistic shocks in the material surround-ing the magnetar (Lyubarsky 2014; Beloborodov 2017), and pulsar-like emission in the magnetosphere (Kumar et al. 2017; Yang &Zhang 2018). Metzger et al. (2019) model a synchrotron maser in abaryon-loaded shell that can produce bursts over the full area of theSNR, relating to the aforementioned third beaming gemoetry. The MNRAS000 , 1–11 (2019)
G. H. Hilmarsson et al.
Figure 3.
Probability that at least half of a list of observed sources wouldbe beamed towards us (P > geometric probability of having a burst pointed towards an observeris therefore 1. Similarly, Beloborodov (2019) proposes that FRBsare produced in an electron-positron plasma in the helical-B windsof a rotating magnetar, where the geometric probability is on theorder of π steradians over the celestial sphere. The lower limit tothe beaming fraction of a burst is 1 / γ p for a single emitting unit.If multiple units are emitting, then the beaming fraction of a singleFRB follows the first beaming scenario previously described. Theprobability of a burst being directed towards an observer dependson the rate of burst generation and the beaming of each burst, butthe details are beyond the scope of this paper.However, we can estimate beaming fractions relating to thesecond, pulsar-like beaming geometry using the Crab pulsar, whichhas been used to model extragalactic FRBs (Cordes & Wasserman2016). We estimate the beaming fraction of the pulsar-like emissionas a function of the opening angle of the emission beam, ρ , andthe angle between the rotation and magnetic axes, α (Tauris &Manchester 1998, Eq. 7). For the Crab, α is estimated to be between45 and 70 degrees (Lyne et al. 2013), and ρ can be calculated fromthe pulsar’s period (Everett & Weisberg 2001, Eq. 7). The period ofthe Crab is 33.3 ms (Manchester et al. 2005), resulting in ρ = ◦ .Thus the beaming fraction of the Crab is between 0.5–0.7.Assuming a fiducial beaming fraction value of 0.6, there isa 99.99% probability that at least one of our sources is beamedtowards us and an 83.4% probability of at least half being beamedtowards us. We also plot the probability that half or more of targetedsources are beamed towards us, P ( > ) , as a function of variousnumber of sources, N , and beaming fractions in Fig. 3. From thisfigure we see that P ( > ) consistently reaches above 70% for f > . N > Repeating bursts from FRB121102 have hitherto been treated asif they follow the Poissonian process, which describes discrete,stochastically occurring events with a known average time betweenthem. A Poisson distribution describes the probability to observe a atnf.csiro.au/research/pulsar/psrcat/ number of events following the Poisson process for an certain timeperiod (e.g. an observation).FRB121102 does not appear to follow this process.FRB121102 goes through phases of quiescence and activity (Spitleret al. 2016; Law et al. 2017), i.e. observed bursts appear clusteredtogether. A better way to describe bursts from FRB121102 might bewith a Weibull distribution, which has a more complex parametriza-tion than a Poissonian distrubution. A Weibull distribution has ashape parameter, k , which describes the degree of clustering; a rateparameter r ; and is written as Oppermann et al. (2018, Eq. 2): W( δ | k , r ) = k δ − [ δ r Γ ( + / k )] γ e −[ δ r Γ ( + / k )] k , (10)where δ are the intervals between subsequent bursts and Γ is thegamma function. For k =
1, the Weibull distribution becomes aPoissoinan distribution. If k <
1, a clustering with small intervalsbetween bursts is favoured, so if a burst is detected, and observer ismore likely to detect subsequent bursts on a short timescale after-wards. Oppermann et al. (2018) performed an analysis on L-bandobservations of FRB121102 in order to estimate k and r . Theyfind that the posterior mean values of the shape parameter and rateare k = . + . − . and r = . + . − . bursts/hr, respectively. Theyalso find that the Poissonian case of k = k = . + . − . anda rate of r = . + . − . bursts/hr. These Weibull analysis rates areconsistent with the Poissonian rate of 0 . + . − . bursts/hr above 0.14 ( w ms / ms ) / Jy ms from Cruces et al. (2020).We can estimate the probability of not detecting a burst from asource with Weibull-distributed bursting activity for an observationof duration ∆ obs as Oppermann et al. (2018, Eq. 18): P ( N = | k , r ) = Γ ( / k ) Γ i (cid:16) / k , ( ∆ obs r Γ ( + / k )) k (cid:17) k Γ ( + / k ) , (11)where r is the bursting rate, Γ is the gamma function, and Γ i isthe incomplete gamma function. The likelihood for multiple ob-servations can be obtained by multiplying the probabilities of eachindividual observation, given that the cadence of the observationsis greater than the spacing between bursts.We can estimate this probability for our 13 hr PAF observationsat L-band of PTF10hgi (consisting of four separate observationsof 1.5–4 hrs, see Table 2). We use the values from Cruces et al.(2020) of k = .
39 and r = .
27 bursts/hr. First we need to scalethis rate from FRB121102 to PTF10hgi and from the P217mmreceiver to the PAF receiver using Eq. 9, resulting in a rate of r = .
43 bursts/hr. The resulting probability of not detecting aburst from these observations, assuming that PTF10hgi contains anFRB121102-like source, is 14%.We repeat this analysis for the UWL observations, which werethree observations of 42, 44, and 55 minutes, using the same shapefactor and rate. The scaled rate of PTF10hgi from the P217mm tothe UWL receiver is 2.42 bursts/hr, and we obtain a 16% probabilityof not detecting a burst from these observations.To perform the same calculations for the S45mm receiverobservations, a burst event analysis for C-band observations ofFRB121102 is needed in order to estimate the shape parameter k and rate r . This analysis is beyond the scope of this work, howeverwe plot the probability of detecting zero bursts as a function of theshape parameter and rate. We illustrate two cases: the observationsof PTF10hgi with the S45mm receiver presented here, and a hypo-thetical survey of 24 3-hr sessions (i.e. the time required to constrainthe upper rate limit, see Table 3), shown in Fig. 4. There we see MNRAS , 1–11 (2019)
LSNe/LGRBs as birthplaces of FRBs Figure 4.
Probability of detecting zero bursts, P ( N = ) , for a Weibulldistributed bursting activity of a source as a function of shape parameter, k , and rate r . Left : Probabilities from our two (5.3 hr in total) observationsof PTF10hgi at C-band.
Right : Probabilities from a hypothetical 72 hourobserving campaign (24 × that the probability of not detecting any bursts rapidly decreaseswith increasing k , and that we can already exclude the L-band pa-rameters from our observations. The lack of bursts detected fromFRB121102 at C-band, compared to L-band detections, might leadone to believe that k and r are frequency dependent, with both be-ing lower at higher frequencies. If we were to continue obseringPTF10hgi at C-band in the same fashion until we have reached thetime to constrain the Poisson rate, we could also place constraintson k and r . This hypothetical survey of 72 hrs shows that there is 0%chance of not detecting a burst for k (cid:62) . r (cid:62) .
03 burst/hr,and would constrain the upper-limit of k to ∼ . In this work we investigate the possibility of SLSNe/LGRBs hostingFRB121102-like progenitors. We have observed 10 targets for 63hours using the S45mm (5.3–9.3 GHz) and PAF (1.2–1.5 GHz)receivers at Effelsberg and the UWL receiver (0.7–4 GHz) at Parkes,but have found no bursts.By assuming an FRB121102-like source is located at our ob-served targets, we have estimated their scaled burst rates with respectto luminosity distance, redshift, and telescope sensitivity. We havealso calculated the upper limit rate for each source, based on ournon-detections. The rate upper limits do not constrain any of thescaled rates at C-band, but the scaled rates for three of our sources,GRB051109B, PTF12dam, and PTF10hgi, can be constrained witha reasonable amount of observing time.PTF10hgi is a source of particular interest, as a persistent radiosource which is coincident with the SLSN was recently detected.This system could be analogous to FRB121102, and detecting anFRB originating from it could be instrumental in deciphering theenigmatic nature of these bursts. We have therefore spent 5.3 hrs ob-serving PTF10hgi at 6 GHz with the S45mm receiver, 13 hrs at 1.4GHz during the commissioning of the PAF receiver at Effelsberg,and 2.3 hrs at 2.4 GHz with the UWL receiver at Parkes. We did notdetect any bursts from those observations, and rule out at the 99%CL the scaled PAF and UWL rates at L-band of an FRB121102-likesource inhabiting PTF10hgi. There are several possibilities for whywe have not detected any bursts: i) PTF10hgi does not contain anFRB121102-like source, ii)
FRBs might not be related to youngmagnetars within SNRs, iii) the source was observed during a qui- escent state, iv)
PTF10hgi’s SNR might still be opaque at L-band, v) or bursts from the source are simply not beamed towards us,When we adopt a beaming fraction of 0.6 for our sources weshow there is 99.99% chance that at least one of our hypotheticaltargets would be beamed towards us, and an 83.4% probability thatat least five of them are beamed towards us. From Fig. 3 we notethat for beaming fractions larger than 0.6, at least half of the sourceswill consistently have a high probability of being beamed towardsus. The clustering of bursts from FRB121102 could be better ex-plained with a Weibull rather than a Poissonian distribution (Op-permann et al. 2018). Using a shape factor of k = .
39 and a scaledrate of 0.43 bursts/hr for a Weibull distribution (Cruces et al. 2020)we estimate a 14% probability of not detecting a burst from ourPAF receiver observations of PTF10hgi, assuming it contains anFRB121102-like source. By using the same shape factor and a rateof 2.42 bursts/hr for our UWL observations we estimate a 16%probability of not detecting a burst. We do not have an estimate ofthe shape factor at C-band, however we plot the probability of notdetecting a burst as a function of k and r for our S45mm receiverobservations of PTF10hgi in Fig. 4, and show that the L-band rateand shape factor are already excluded.We have several recommendations for future surveys whichmay follow up this work. By assuming that SLSNe/LGRBs containFRB121102-like sources, we must expect that they also have clus-tering of emission, along with periods of dormancy. We should alsoassume that the bursts are beamed to some degree. Therefore wesuggest that observing multiple sources for short periods of time ona regular basis would be ideal. The advantage of observing a sourcewhich has clustered burst phases across multiple short observationsrather than a few (or one) long observations is shown in Fig. 5. Therewe plot the probability of detecting zero bursts for a survey totaling73 hrs across different number of observations as a function of burstrate for a source with different shape factors. As we move furtheraway from the Poissonian case of k =
1, it becomes increasinglyimportant to split a survey into multiple observations in order tomaximize the probability of detecting a burst. Since the rate scalingis dependent on distance, choosing sources closer than FRB121102is advised. Finally, SLSNe/LGRBs with coincident persistent radiosources, like PTF10hgi, should be the primary sources to observefor future surveys of this kind; they should preferably be observed athigher frequencies, as we cannot be certain that the SNR is transpar-ent at L-band. The UWL might be the ideal instrument for followingup on this work for two reasons: i) The SNR of the targets observedhere are most likely transparent in at least the upper part of UWL’sband, making the optically thick-thin transition potentially observ-able with a single receiver. ii)
The scaled FRB121102 UWL ratesare higher than the ones for the S45mm receiver. This implies thatthe time needed to constrain the 95% CL upper rate limits of thetargets observed in this work with the UWL is much less than forthe S45mm receiver. We show in Table 4 that these times rangebetween 1–16 hrs.Recent localisations of FRBs (Bannister et al. 2019; Raviet al. 2019; Prochaska et al. 2019; Marcote et al. 2020) have re-vealed host galaxies differing from FRB121102, with them beinglenticular or spiral in shape, and more massive. The localisationof FRB180916.J1058+65 (Marcote et al. 2020) is of particular in-terest, as it is the only other localised repeating FRB. The host ofFRB180916.J1058+65 is a spiral galaxy and is both more massiveand has higher metallicity than the host of FRB121102, renderingit different to hosts of SLSNe/LGRBs as well. This bursting sourcealso has no persistent radio counterpart, and the burst absolute RM
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MNRAS000 , 1–11 (2019) G. H. Hilmarsson et al.
Table 4.
Burst rates of an FRB121102-like source located at the targetsobserved in this work.
From left to right : Source name, burst rate of anFRB121102-like source scaled to the UWL receiver, and the observing timerequired to constrain those rates at the 95% confidence level.Source name R FRB121102 [hr − ] T constr [hr]GRB050826 0.3 11GRB051109B 3.2 1GRB111225A 0.3 11PTF09cnd 0.4 8PTF10uhf 0.3 10PTF10bjp 0.2 16SN2010gx 0.4 7PTF12dam 1.9 2LSQ12dlf 0.4 8PTF10hgi 2.2 1 value is roughly 100 rad m − , three orders of magnitude lowerthan FRB121102. The two bursting sources are however both lo-calised within star forming regions of their respective host galaxies.FRB180916.J1058+65 still fits within the framework of a magnetarembedded in an SNR if the system is a few hundred years old (Mar-cote et al. 2020). By then the persistent radio source would havefaded and the RM decreased to the observed value. This begs thequestion whether or not the host galaxy of FRB121102 is a typicalhost of repeating FRBs. Expanding future surveys like in this workto include galaxies similar to hosts of other localised FRBs couldbe more fruitful. ACKNOWLEDGEMENTS
Based on observations with the 100-m telescope of the MPIfR(Max-Planck-Institut für Radioastronomie) at Effelsberg. Some ofthe results of this paper have been derived using the
FRUITBAT package (Batten 2019). The Parkes radio telescope is funded bythe Commonwealth of Australia for operation as a National Facilitymanaged by CSIRO. The time for this project was allocated fromthe Director’s Discretionary Time under the Project ID PX048. Wethank Vincent Morello for assisting with our Parkes observations,and C. R. H. Walker for excellent comments and discussions. LGS isa Lise Meitner independent research group leader and acknowledgessupport from the Max Planck Society. We thank the referees for theircomments which helped improving this manuscript.
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LSNe/LGRBs as birthplaces of FRBs Figure 5.
Probability of detecting zero bursts as a function of burst rate for hypothetical 73 hr surveys spanning different numbers of observations (colours).Different shape factors, k , are shown in each panel. As expected a single long observation has the highest probability of detecting zero bursts from a Weibulldistribution, with the probability decreasing with number of observations.This paper has been typeset from a TEX/L A TEX file prepared by the author.MNRAS000