Interpreting the distributions of FRB observables

Fast radio bursts (FRBs) are short-duration radio transients of unknown origin. Thus far, they have been blindly detected at millisecond timescales with dispersion measures (DMs) between 110--2600\,pc\,cm$^{-3}$. However, the observed pulse width, DM, and even brightness distributions depend strongly on the time and frequency resolution of the detection instrument. Spectral and temporal resolution also significantly affect FRB detection rates, similar to beam size and system-equivalent flux density (SEFD). I discuss the interplay between underlying FRB properties and instrumental response, and provide a generic formalism for calculating the \textit{observed} distributions of parameters given an intrinsic FRB distribution, focusing on pulse width and DM. I argue that if there exist many FRBs of duration $<<$\,1\,ms (as with giant pulses from Galactic pulsars) or events with high DM, they are being missed due to the deleterious effects of smearing. I outline how to optimise spectral and temporal resolution for FRB surveys that are throughput-limited. I also investigate how such effects may have been imprinted on the distributions of FRBs at real telescopes, like the different observed DMs at ASKAP and Parkes. Finally, I discuss the impact of intrinsic correlations between FRB parameters on detection statistics

Applying Deep Learning to Fast Radio Burst Classification

Upcoming Fast Radio Burst (FRB) surveys will search $\sim$10\,$^3$ beams on sky with very high duty cycle, generating large numbers of single-pulse candidates. The abundance of false positives presents an intractable problem if candidates are to be inspected by eye, making it a good application for artificial intelligence (AI). We apply deep learning to single pulse classification and develop a hierarchical framework for ranking events by their probability of being true astrophysical transients. We construct a tree-like deep neural network (DNN) that takes multiple or individual data products as input (e.g. dynamic spectra and multi-beam detection information) and trains on them simultaneously. We have built training and test sets using false-positive triggers from real telescopes, along with simulated FRBs, and single pulses from pulsars. Training of the DNN was independently done for two radio telescopes: the CHIME Pathfinder, and Apertif on Westerbork. High accuracy and recall can be achieved with a labelled training set of a few thousand events. Even with high triggering rates, classification can be done very quickly on Graphical Processing Units (GPUs). That speed is essential for selective voltage dumps or issuing real-time VOEvents. Next, we investigate whether dedispersion back-ends could be completely replaced by a real-time DNN classifier. It is shown that a single forward propagation through a moderate convolutional network could be faster than brute-force dedispersion; but the low signal-to-noise per pixel makes such a classifier sub-optimal for this problem. Real-time automated classification may prove useful for bright, unexpected signals, both now and in the era of radio astronomy when data volumes and the searchable parameter spaces further outgrow our ability to manually inspect the data, such as for SKA and ngVLA

Stellar prospects for FRB gravitational lensing

Gravitational lensing of fast radio bursts (FRBs) offers an exciting avenue for several cosmological applications. However, it is not yet clear how many such events future surveys will detect nor how to optimally find them. We use the known properties of FRBs to forecast detection rates of gravitational lensing on delay timescales from microseconds to years, corresponding to lens masses spanning fifteen orders of magnitude. We highlight the role of the FRB redshift distribution on our ability to observe gravitational lensing. We consider cosmological lensing of FRBs by stars in foreground galaxies and show that strong stellar lensing will dominate on microsecond timescales. Upcoming surveys such as DSA-2000 and CHORD will constrain the fraction of dark matter in compact objects (e.g. primordial black holes) and may detect millilensing events from intermediate mass black holes (IMBHs) or small dark matter halos. Coherent all-sky monitors will be able to detect longer-duration lensing events from massive galaxies, in addition to short time-scale lensing. Finally, we propose a new application of FRB gravitational lensing that will measure directly the circumgalactic medium of intervening galaxies

On detecting repetition from fast radio bursts

Fast radio bursts (FRBs) are bright, millisecond-duration radio pulses whose origins are unknown. To date, only one (FRB 121102) out of several dozen has been seen to repeat, though the extent to which it is exceptional remains unclear. We discuss detecting repetition from FRBs, which will be very important for understanding their physical origin, and which also allows for host galaxy localisation. We show how the combination of instrument sensitivity, beamshapes, and individual FRB luminosity functions affect the detection of sources whose repetition is not necessarily described by a homogeneous Poisson process. We demonstrate that the Canadian Hydrogen Intensity Mapping Experiment (CHIME) could detect many new repeating FRBs for which host galaxies could be subsequently localised using other interferometers, but it will not be an ideal instrument for monitoring FRB 121102. If the luminosity distributions of repeating FRBs are given by power-laws with significantly more dim than bright bursts, CHIME's repetition discoveries could preferentially come not from its own discoveries, but from sources first detected with lower-sensitivity instruments like the Australian Square Kilometer Array Pathfinder (ASKAP) in fly's eye mode. We then discuss observing strategies for upcoming surveys, and advocate following up sources at approximately regular intervalsand with telescopes of higher sensitivity, when possible. Finally, we discuss doing pulsar-like periodicity searching on FRB follow-up data, based on the idea that while most pulses are undetectable, folding on an underlying rotation period could reveal the hidden signal

A dispersion excess from pulsar wind nebulae and supernova remnants: Implications for pulsars and FRBs

Young pulsars and the pulsar wind nebulae (PWNe) or supernova remnants (SNRs) that surround them are some of the most dynamic and high-powered environments in our Universe. With the rise of more sensitive observations, the number of pulsar-SNR and PWN associations (hereafter, SNR/PWN) has increased, yet we do not understand to which extent this environment influences the pulsars' impulsive radio signals. We studied the dispersive contribution of SNRs and PWNe on Galactic pulsars, and considered their relevance to fast radio bursts (FRBs) such as FRB 121102. We investigated the dispersion measure (DM) contribution of SNRs and PWNe by comparing the measured DMs of Galactic pulsars in a SNR/PWN to the DM expected only from the intervening interstellar electrons, using the NE2001 model. We find that a two-$\sigma$ DM contribution of SNRs and PWNe to the pulsar signal exists, amounting to $21.1 \pm 10.6$ pc cm$^{-3}$. The control sample of pulsars unassociated with a SNR/PWN shows no excess. We model the SNR and PWN electron densities for each young pulsar in our sample and show that these indeed predict an excess of this magnitude. By extrapolating to the kind of fast-spinning, high magnetic field, young pulsars that may power FRBs, we show their SNR and PWN are capable of significantly contributing to the observed DM.Comment: 7 pages, 4 figures, 2 tables. Accepted for publication in A&

Deep Radio Interferometric Imaging with POLISH: DSA-2000 and weak lensing

Radio interferometry allows astronomers to probe small spatial scales that are often inaccessible with single-dish instruments. However, recovering the radio sky from an interferometer is an ill-posed deconvolution problem that astronomers have worked on for half a century. More challenging still is achieving resolution below the array's diffraction limit, known as super-resolution imaging. To this end, we have developed a new learning-based approach for radio interferometric imaging, leveraging recent advances in the classical computer vision problems of single-image super-resolution (SISR) and deconvolution. We have developed and trained a high dynamic range residual neural network to learn the mapping between the dirty image and the true radio sky. We call this procedure POLISH, in contrast to the traditional CLEAN algorithm. The feed forward nature of learning-based approaches like POLISH is critical for analyzing data from the upcoming Deep Synoptic Array (DSA-2000). We show that POLISH achieves super-resolution, and we demonstrate its ability to deconvolve real observations from the Very Large Array (VLA). Super-resolution on DSA-2000 will allow us to measure the shapes and orientations of several hundred million star forming radio galaxies (SFGs), making it a powerful cosmological weak lensing survey and probe of dark energy. We forecast its ability to constrain the lensing power spectrum, finding that it will be complementary to next-generation optical surveys such as Euclid

Eating Disorders in Men: A Comprehensive Summary

Eating disorders (EDs) have detrimental effects on an individual’s physical and mental health, along with significant interpersonal, social and economic effects. Furthermore, men who are suffering with an ED face unique challenges with this. Men suffering with EDs have historically received little attention within ED research, diagnosis and intervention. However, the number of men suffering with these issues is significant and growing. Understanding of EDs tend to ignore male experiences, meaning many are left to suffer in silence until the ED has developed to a critical point. However, many now recognize the need to understand the issues facing men suffering with an ED. By improving our understanding, we can better improve early detection, diagnosis and treatment for those who are suffering. This paper aims to provide a comprehensive general introduction to this growing area of research and it is hoped that it will be of good use to interested researchers, students and the general public. Prevalence, presentation, history, diagnosis and more will be covered in order to provide a well-rounded understanding of EDs in men