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  1. Abstract

    Fast Radio Bursts (FRBs) are extragalactic radio transients that exhibit a distance-dependent dispersion of their signal, and thus can be used as cosmological probes. In this article we, for the first time, apply a model-independent approach to measure reionization from synthetic FRB data assuming these signals are detected beyond redshift 5. This method allows us to constrain the full shape of the reionization history as well as the CMB optical depthτwhile avoiding the problems of commonly used model-based techniques. A total of 100 localized FRBs, originating from redshifts 5–15, could constrain (at 68% confidence level) the CMB optical depth to within 11%, and the midpoint of reionization to 4%, surpassing current state-of-the-art CMB bounds and quasar limits. Owing to the higher numbers of expected FRBs at lower redshifts, theτconstraints are asymmetric (+14%, −7%), providing a much stronger lower limit. Finally, we show that the independent constraints on reionization from FRBs will improve limits on other cosmological parameters, such as the amplitude of the power spectrum of primordial fluctuations.

  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 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« less
  3. Abstract We report the discovery of a highly circularly polarized, variable, steep-spectrum pulsar in the Australian Square Kilometre Array Pathfinder (ASKAP) Variables and Slow Transients (VAST) survey. The pulsar is located about 1° from the center of the Large Magellanic Cloud, and has a significant fractional circular polarization of ∼20%. We discovered pulsations with a period of 322.5 ms, dispersion measure (DM) of 157.5 pc cm −3 , and rotation measure (RM) of +456 rad m −2 using observations from the MeerKAT and the Parkes telescopes. This DM firmly places the source, PSR J0523−7125, in the Large Magellanic Cloud (LMC). This RM is extreme compared to other pulsars in the LMC (more than twice that of the largest previously reported one). The average flux density of ∼1 mJy at 1400 MHz and ∼25 mJy at 400 MHz places it among the most luminous radio pulsars known. It likely evaded previous discovery because of its very steep radio spectrum (spectral index α ≈ −3, where S ν ∝ ν α ) and broad pulse profile (duty cycle ≳35%). We discuss implications for searches for unusual radio sources in continuum images, as well as extragalactic pulsars in the Magellanic Clouds and beyond.more »Our result highlighted the possibility of identifying pulsars, especially extreme pulsars, from radio continuum images. Future large-scale radio surveys will give us an unprecedented opportunity to discover more pulsars and potentially the most distant pulsars beyond the Magellanic Clouds.« less
    Free, publicly-accessible full text available May 1, 2023
  4. Abstract Using neural networks, we integrate the ability to account for Doppler smearing due to a pulsar’s orbital motion with the pulsar population synthesis package psrpoppy to develop accurate modeling of the observed binary pulsar population. As a first application, we show that binary neutron star systems where the two components have highly unequal mass are, on average, easier to detect than systems that are symmetric in mass. We then investigate the population of ultracompact (1.5 minutes ≤ P b ≤ 15 minutes) neutron star–white dwarf (NS–WD) and double neutron star (DNS) systems, which are promising sources for the Laser Interferometer Space Antenna gravitational-wave detector. Given the nondetection of these systems in radio surveys thus far, we estimate a 95% confidence upper limit of ∼1450 and ∼1100 ultracompact NS–WD and DNS systems in the Milky Way that are beaming toward the Earth, respectively. We also show that using survey integration times in the range 20 s–200 s with time-domain resampling will maximize the signal-to-noise ratio as well as the probability of detection of these ultracompact binary systems. Among all the large-scale radio pulsar surveys, those that are currently being carried out using archival data collected with the Arecibo radio telescopemore »have a ∼50%–80% chance of detecting at least one of these systems using current integration integration times and ∼80%–95% using optimal integration times in the next several years.« less
  5. Abstract Using Bayesian analyses we study the solar electron density with the NANOGrav 11 yr pulsar timing array (PTA) data set. Our model of the solar wind is incorporated into a global fit starting from pulse times of arrival. We introduce new tools developed for this global fit, including analytic expressions for solar electron column densities and open source models for the solar wind that port into existing PTA software. We perform an ab initio recovery of various solar wind model parameters. We then demonstrate the richness of information about the solar electron density, n E , that can be gleaned from PTA data, including higher order corrections to the simple 1/ r 2 model associated with a free-streaming wind (which are informative probes of coronal acceleration physics), quarterly binned measurements of n E and a continuous time-varying model for n E spanning approximately one solar cycle period. Finally, we discuss the importance of our model for chromatic noise mitigation in gravitational-wave analyses of pulsar timing data and the potential of developing synergies between sophisticated PTA solar electron density models and those developed by the solar physics community.
    Free, publicly-accessible full text available April 1, 2023
  6. ABSTRACT The origin of fast radio bursts (FRBs) still remains a mystery, even with the increased number of discoveries in the last 3 yr. Growing evidence suggests that some FRBs may originate from magnetars. Large, single-dish telescopes such as Arecibo Observatory (AO) and Green Bank Telescope (GBT) have the sensitivity to detect FRB 121102-like bursts at gigaparsec distances. Here, we present searches using AO and GBT that aimed to find potential radio bursts at 11 sites of past gamma-ray bursts that show evidence for the birth of a magnetar. We also performed a search towards GW170817, which has a merger remnant whose nature remains uncertain. We place $10\sigma$ fluence upper limits of ≈0.036 Jy ms at 1.4 GHz and ≈0.063 Jy ms at 4.5 GHz for the AO data and fluence upper limits of ≈0.085 Jy ms at 1.4 GHz and ≈0.098 Jy ms at 1.9 GHz for the GBT data, for a maximum pulse width of ≈42 ms. The AO observations had sufficient sensitivity to detect any FRB of similar luminosity to the one recently detected from the Galactic magnetar SGR 1935+2154. Assuming a Schechter function for the luminosity function of FRBs, we find that our non-detections favour a steep power-law index (α ≲ −1.1) and a large cut-off luminositymore »(L0 ≳ 1041 erg s−1).« less
  7. 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.
  8. Free, publicly-accessible full text available December 1, 2022
  9. Abstract We search NANOGrav’s 12.5 yr data set for evidence of a gravitational-wave background (GWB) with all the spatial correlations allowed by general metric theories of gravity. We find no substantial evidence in favor of the existence of such correlations in our data. We find that scalar-transverse (ST) correlations yield signal-to-noise ratios and Bayes factors that are higher than quadrupolar (tensor-transverse, TT) correlations. Specifically, we find ST correlations with a signal-to-noise ratio of 2.8 that are preferred over TT correlations (Hellings and Downs correlations) with Bayesian odds of about 20:1. However, the significance of ST correlations is reduced dramatically when we include modeling of the solar system ephemeris systematics and/or remove pulsar J0030+0451 entirely from consideration. Even taking the nominal signal-to-noise ratios at face value, analyses of simulated data sets show that such values are not extremely unlikely to be observed in cases where only the usual TT modes are present in the GWB. In the absence of a detection of any polarization mode of gravity, we place upper limits on their amplitudes for a spectral index of γ = 5 and a reference frequency of f yr = 1 yr −1 . Among the upper limits for eight generalmore »families of metric theories of gravity, we find the values of A TT 95 % = ( 9.7 ± 0.4 ) × 10 − 16 and A ST 95 % = ( 1.4 ± 0.03 ) × 10 − 15 for the family of metric spacetime theories that contain both TT and ST modes.« less
    Free, publicly-accessible full text available December 1, 2022