Presented in fulfillment of the requirements of the degree of Doctor of Philosophy. February, 2016

Transcription

1 The transient radio sky observed with the Parkes radio telescope Emily Brook Petroff Presented in fulfillment of the requirements of the degree of Doctor of Philosophy February, 2016 Faculty of Science, Engineering, and Technology Swinburne University

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3 i Toute la sagesse humaine sera dans ces deux mots: attendre et espérer. All of human wisdom is summed up in these two words: wait and hope. The Count of Monte Cristo, Aléxandre Dumas

4 ii Abstract This thesis focuses on the study of time-variable phenomena relating to pulsars and fast radio bursts (FRBs). Pulsars are rapidly rotating neutron stars that produce radio emission at their magnetic poles and are observed throughout the Galaxy. The source of FRBs remains a mystery their high dispersion measures may imply an extragalactic and possibly cosmological origin; however, their progenitor sources and distances have yet to be verified. We first present the results of a 6-year study of 168 young pulsars to search for changes in the electron density along the line of sight through temporal variations in the pulsar dispersion measure. Only four pulsars exhibited detectable variations over the period of the study; it is argued that these variations are due to the movement of ionized material local to the pulsar. Our upper limits on DM variations in the other pulsars are consistent with the scattering predicted by current models of turbulence in the free electron density along these lines of sight through the interstellar medium (ISM). We also present new results of a search for single pulses from Fast Radio Bursts (FRBs), including a full analysis of the data from the High Time Resolution Universe (HTRU) survey at intermediate and high Galactic latitudes. No new FRBs were found in the intermediate latitude survey and five new bursts were found at high latitudes. The unexpected dearth at intermediate latitudes is found to be inconsistent (with 99% confidence) with an isotropic distribution using previously published rates. From the 9 FRBs at high latitude an all-sky rate can be derived with the largest sample of FRBs to date of R FRB (F 0.6 Jyms)> (95%) FRBs sky 1 day 1,orR FRB (F 2Jyms)= (95%) FRBs sky 1 day 1. Although lower than previously published estimates, these rates are still inconsistent with results at intermediate latitudes. The FRBs from the HTRU survey were re-observed in a detailed follow-up campaign to place limits on possible repeating sources. No repetition was detected from any of the FRBs; however, a new burst was discovered in real-time during these observations: FRB Polarization information for the burst was preserved by the real-time search pipeline at Parkes, and the burst was found to be 21±7% circularly polarized. Multiwavelength follow-up was also performed and no variability was detected in the field related to the burst. These observations placed the first limits on an afterglow. The full search of the HTRU intermediate and high latitude survey also resulted in the discovery of 50 perytons, seemingly dispersed terrestrial signals of unknown origin. We present conclusive evidence that perytons are caused by on-site microwave ovens producing sparks in a non-linear shut down phase. Based on the properties of the perytons and FRBs

5 we conclude that the observed FRBs cannot be produced by the microwave ovens on site and an astrophysical origin remains highly favored. iii

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7 Acknowledgments v It s difficult to find the words to fully express my gratitude to all the people who deserve it. There were a lot of people who helped make this happen from when I decided I wanted a PhD when I was twelve. Early thanks are due to Bill Lamb, Rosa Hemphill, Catherine Garland, and all the people at Oregon Episcopal School who let me do my own thing as well as to Cindy Blaha and everyone in the Carleton College physics department. I owe my love of pulsars and my introduction to radio astronomy to the one and only Joel Weisberg. Thank you, Joel, for working patiently with me for over three years at Carleton and for introducing me to Australia and to Parkes. I would never be here writing this if it weren t for you. Before going any further enormous and heartfelt thanks go to my amazing supervisors: Willem van Straten, Simon Johnston, and Matthew Bailes. Willem thank you for providing support, encouragement, counsel, and wisdom over the last three years. Your good judgment has helped me navigate the world of research and made me a better person. Simon thank you for giving me one of the greatest gifts a supervisor ever could, the space and freedom to speak my mind. I ve been learning from you since my first trip to the ATNF back in 2009 and it has been an honour. Matthew thank you for showing me what quality research looks like and giving me something to aspire to. Wisdom doesn t just come from supervisors. I m grateful to the friends who I have had along the way who have taught me in one way or another. Jonathan, thank you for the book recommendations, the debates, the coding lessons, the chocolate, and saving me from my terrible cooking. Dave, thank you for your endless positivity, your encyclopedic movie knowledge, and for basically carrying our team at trivia (bonus points for your specific Star Trek theme song knowledge). Jonathan and Dave, thanks for making Scotch Saturday happen. Tyler, thank you for being a friend through thick and thin, laughing with me, and showing me how a good thesis is done. Rebecca, thank you for being you, for having an infectious amount of happiness about the world around you and for picking me up whenever I got down. Evan, thank you for your counsel and for being willing to listen when asked and give advice when greatly needed. Ewan, thank you for always encouraging me to do my best, push outside my comfort zone, not be afraid, and for reminding me that things will turn out OK. Enormous thanks to Andrew for answering my questions from the embarrassingly simple to the ridiculously technical. And a great big thank you to the rest of the pulsar group for everything along the way: Paul, Stefan, Pablo, Fabian, Manisha, Shivani, Vivek,

8 vi Vikram, Damien and Ian. I would also like to acknowledge all the mentors who have given me advice, support, direction, and encouragement in one way or another during these past three years (in no particular order): Katie Mack, Bryan Gaensler, Brian Schmidt, Elaine Sadler, Tamara Davis, Naomi McClure-Griffiths, Michael Childress, Fang Yuan, Chris Blake, Alan Duffy, Virginia Kilborn, Karl Glazebrook, Jeff Cooke, Michael Murphy, Sarah Maddison, Tyler Pritchard, George Hobbs, Antonia Rowlinson, Dick Manchester, Keith Bannister, Tara Murphy, Kate Gunn, Sue Lester, Elizabeth Thackray, John Sarkissian, John Reynolds, Phil Edwards, Brett Presig, Mal Smith, JP Macquart, Cath Trott, Ron Ekers, Ben Stappers, Andrea Possenti, Jasson Hessels, Aris Karastergiou, Sarah Burke-Spolaor, David Champion, and Michael Kramer. Swinburne, CSIRO, CAASTRO, and Parkes have been supportive and fantastic environments in which to work and I wish I could thank the entire community individually. You ve all encouraged, motivated, inspired, and impressed me during my time here. Believe it or not I would also like to thank those out there who caused me pain, both mental and physical the ones who said I d never make it. Proving you wrong has been one of the most rewarding experiences of my life. Natasha, thank you for being my best friend for 10 years and reminding me every time I come back why Portland is home. Norma, thank you for being my biffle, my other Wonder Twin, and my robot unicorn. Special thanks to Hallie, Becca, Bizou, Tug, and Sanny, even though you re not people and you ll never read this. Pakey, thank you for listening; I aspire to be as good of a person as you. Erica, just thank you. Thank you for being my sister. I d especially like to thank my mom and dad for supporting me from the very beginning, giving me all a daughter could want, and always being on the other side of the door, or the phone, or the Skype call when I wanted to quit and said I couldn t do it, saying Yes you can. I love you both more than anything.

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10 viii Declaration The work presented in this thesis has been carried out in the Centre for Astrophysics & Supercomputing at Swinburne University of Technology (Hawthorn, VIC), the Australia Telescope National Facility/CSIRO Astronomy and Space Sciences (Marsfield, NSW) and the CSIRO Parkes radio telescope (Parkes, NSW) between 2012 and This thesis contains no material that has been accepted for the award of any other degree or diploma. To the best of my knowledge, this thesis contains no material previously published or written by another author, except where due reference is made in the text of the thesis. The content of the chapters listed below has appeared in refereed journals. Minor alterations have been made to the published papers in order to maintain argument continuity and consistency of spelling and style. Chapter 3 has been published in Monthly Notices of the Royal Astronomical Society, 435, 1610, 2013, as Dispersion measure variations in a sample of 168 pulsars, authored by E. Petroff, M. J. Keith, S. Johnston, W. van Straten, and R. M. Shannon. Chapter 4 has been published in Astrophysical Journal Letters, 789, L26,2014,as An absence of fast radio bursts at intermediate galactic latitudes, authored by E. Petroff, W. van Straten, S. Johnston, M. Bailes, E. D. Barr, S. D. Bates, N. D. R. Bhat, M. Burgay, S. Burke-Spolaor, D. Champion, P. Coster, C. Flynn, E. F. Keane, M. J. Keith, M. Kramer, L. Levin, C. Ng, A. Possenti, B. W. Stappers, C. Tiburzi, and D. Thornton. Chapter 5 has been published in Monthly Notices of the Royal Astronomical Society, 451, 3933, 2015, as Identifying the source of perytons at the Parkes radio telescope, authored by E. Petroff, E. F. Keane, E. D. Barr, J. E. Reynolds, J. Sarkissian, P. G. Edwards, J. Stevens, C. Brem, A. Jameson, S. Burke-Spolaor, S. Johnston, N. D. R. Bhat, P. Chandra, S. Kudale, S. Bhandari. Chapter 6 (excluding Section 6.2) has been published in Monthly Notices of the Royal Astronomical Society, , 2015, as A survey of FRB fields: Limits on repeatability, authored by E. Petroff, S. Johnston, E. F. Keane, W. van Straten, M. Bailes, E. D. Barr, B. R. Barsdell, S. Burke-Spolaor, M. Caleb, D. J. Champion, C. Flynn, A. Jameson, M. Kramer, C. Ng, A. Possenti, B. W. Stappers. Chapter 7 has been published in Monthly Notices of the Royal Astronomical Society, 477, 246, 2015, as A real-time fast radio burst: polarization and multi-wavelength

11 ix follow-up, authored by E. Petroff, M. Bailes, E. D. Barr, B. R. Barsdell, N. D. R. Bhat, F. Bian, S. Burke-Spolaor, M. Caleb, D. Champion, P. Chandra, G. Da Costa, C. Delvaux, C. Flynn, N. Gehrels, J. Greiner, A. Jameson, S. Johnston, M. M. Kasliwal, E. F. Keane, S. Keller, J. Kocz, M. Kramer, G. Leloudas, D. Malesani, J. S. Mulchaey, C. Ng, E. O. Ofek, D. A. Perley, A. Possenti, B. P. Schmidt, Yue Shen, B. W. Stappers, P. Tisserand, W. van Straten, C. Wolf. Emily Petroff Melbourne, Victoria, Australia 2015

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13 For my family xi

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15 Contents Abstract Acknowledgements Declaration List of Figures List of Tables i iv vii xvi xviii 1 Introduction Transient radio astronomy Pulsars Dispersion Scattering Interstellar scintillation Faraday rotation Pulsar searches and rotating radio transients Fast Radio Bursts Distances, energies, and brightness temperature FRB rates and progenitor theories Pulse propagation Perytons Thesis outline Technological Introduction Data acquisition The Parkes radio telescope Detecting single pulses The heimdall pipeline Real-time searches The High Time Resolution Universe survey Dispersion measure variations of young pulsars Introduction Observations xiii

16 xiv Contents 3.3 Analysis Results - Detections PSR J PSR J PSR J PSR J Results - Upper limits Conclusions An Absence of Fast Radio Bursts at Intermediate Latitudes Introduction Analysis and Results Discussion Dispersion in the ISM Scattering in the ISM Sky Temperature Scintillation Sensitivity Map Summary Conclusions Identifying the source of perytons Introduction Observations Results Three perytons Prevalence of GHz signals at Parkes Archival perytons Generating perytons The Peryton Cluster of 1998 June Discussion Relevance to FRBs Differences in observed properties What is FRB ? Deciphering new transient events Conclusions

17 Contents xv 6 Discovery and follow-up of FRBs at high latitudes Introduction Search of the HTRU high latitude survey Burst properties Updated FRB rates and Latitude Distribution Parkes follow-up Data processing Follow-up Results Discussion Total time Multi-day observations of FRB Follow-up of FRB Conclusions A real-time fast radio burst Introduction Real-Time Transient Pipeline Parkes real-time detection of FRB FRB Follow-up at Other Telescopes Parkes Radio Telescope Australia Telescope Compact Array Giant Metrewave Radio Telescope Swift X-Ray Telescope Gamma-Ray Burst Optical/Near-Infrared Detector Swope Telescope Palomar Transient Factory Magellan Telescope SkyMapper Effelsberg Radio Telescope Keck Spectroscopy Nordic Optical Telescope Spectroscopy Interpretation and Discussion Polarization Possible connection with FRB Limits on a varying counterpart Host galaxies

18 xvi Contents 7.6 Conclusions Conclusions Major Findings of the Thesis Future Directions Bibliography 138 Appendices A Glossary 139 B Derivation of Bayesian probabilities 141 B.1 Derivation B.2 Justification

19 List of Figures 1.1 The radio transient parameter space The Galactic distribution of radio pulsars Spectrum of a radio pulse from a pulsar Kolmogorov power law of interestellar turbulence A cartoon of the scatter broadening of a pulse by a thin screen of plasma Spectrum and pulse profile of FRB (the Lorimer Burst) Spectrum of a peryton signal detected at the Parkes radio telescope The Parkes multibeam receiver Recovered signal-to-noise ratio of a pulse using different single pulse search codes Overview plot of heimdall outputs for a single pointing The heimdall processing pipeline for filterbank data DM measurements of PSR J over 2000 days DM measurements of PSR J since DM measurements of PSR J DM measurements of PSR J DM measurements of PSR J Upper limits on ddm/dt for pulsars with no detected DM variations Galactic effects on a simulated FRB pulse with strong scattering Galactic effects on a simulated FRB pulse with no scattering The time frequency structure of the three January perytons RFI monitor spectra for the three January perytons Data from the Parkes and ATCA RFI monitors at the times of the perytons Histogram of narrow RFI spikes detected at Parkes A bright peryton detected during tests of the Parkes microwave ovens Azimuth and elevation positions with direct line of sight between Parkes receiver and the Woolshed microwave oven FRB and peryton distributions in time of day and DM Pulse profiles of the 5 new FRBs from the high latitude survey Probability of detection for repeating progenitors for FRB xvii

20 xviii List of Figures 7.1 Spectrum and pulse profile of FRB Full polarization profile of FRB FRB multi-wavelength couterpart magnitude limits from follow-up observations All-sky distribution of the known FRBs

21 List of Tables 2.1 Properties of central, inner, and outer rings of the 21-cm multibeam receiver Survey regions of the low, intermediate, and high latitude components of HTRU South Pulsars with DM variations over 6 years above 3 levels Measurements of DM and ddm/dt for all pulsars in the Fermi sample Properties of the perytons from 2015 January Repeating progenitor models for FRBs and their timescales Observed properties of the 9 FRBs from the HTRU high latitude survey Derived cosmological properties of the 9 FRBs from the HTRU high latitude survey Total hours of follow-up observations for 8 FRBs from HTRU Summary of targeted observations for FRB Observed properties of FRB Derived cosmological properties of FRB Follow-up observations conducted at 12 telescopes for FRB xix

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23 1 Introduction Within the past decade it has become possible to observe time-variable radio sources with unprecedented sensitivity at high time and frequency resolution thanks, in part, to advances in radio astronomical instrumentation and signal processing. The experimental methods of time-variable radio astronomy, such as observations of pulsars and radio transients, provide a window into events and processes not observable through other techniques. In this chapter we describe different types of transient radio sources, some of which will be discussed in-depth in this work, and give some examples of their unique uses as probes of the ionized baryons in the near-vacuum of space. The first section of this chapter details the history of transient radio astronomy and different types of radio transients. The second section discusses the discovery of pulsars and their use as probes of the interstellar medium. The third section introduces the recently discovered fast radio bursts and their exciting potential as probes of the intergalactic medium over cosmological distances. 1.1 Transient radio astronomy An astronomical transient is an event of short duration relative to the timescales typical of events in the Universe. Different definitions of transients exist but for the purposes of this thesis astronomical transients are defined in the following three ways: sources that appear and disappear on timescales observable by humans that have no known counterpart; sources that appear and disappear on timescales observable by humans that are associated with known one-off events; or sources that emit short-duration emission which may be highly sporadic. Transient phenomena in the skies have been recorded for centuries; early examples include the observation of a guest star in the night sky in the year 1054 A.D. The nearby supernova, which created the Crab Nebula, is the birthplace of one of the youngest known 1

24 2 Chapter 1. Introduction neutron stars (Mayall & Oort, 1942). More recently, telescopes probing the entire electromagnetic spectrum, from gamma-rays and X-rays down to radio frequencies, have detected fainter and more distant variable and transient phenomena. Beginning in 1933 with the study of the radio background at 20 MHz by Karl Jansky (Jansky, 1933a,b), observations of the radio sky offered a surprising new window into the physics of our own Galaxy and beyond. Radio transients were first observed in the form of non-thermal Solar emission at MHz correlating with periods of high sunspot activity (Appleton, 1945). As radio instrumentation improved and larger radio observatories were constructed, sensitivity to the variability of astrophysical sources increased. Refraction of radio frequencies in the Earth s ionosphere was first observed in the late 1940 s as changes in brightness of stable radio sources over time (Hey et al., 1946). However, radio stars observed with the most advanced radio telescopes of the time were seen to fluctuate in brightness on levels that could not be explained with ionospheric effects. It was realized that the cause of these fluctuations was scintillation, or twinkling, of radio light not within the ionosphere but rather in the ionized material in the Solar System produced by the Sun (Hewish, 1955). The discovery of interplanetary scintillation opened the doors to the sub-discipline of time-domain radio astronomy and the first detections of radio pulses. In 1967 a source was discovered that emitted highly periodic, bright pulses, each lasting only 30 ms the discovery of the first pulsar (Hewish et al., 1968). Pulsars are rapidly rotating neutron stars and sources of strong radio emission when fortuitously oriented towards the observer. Pulsar astronomy has become a rich and vibrant field and pulsars themselves can be used as excellent probes of gravitation (Kramer et al., 2006; Hulse & Taylor, 1975), condensed matter physics (Antoniadis et al., 2013), and the interstellar medium of the Galaxy (Keith et al. 2013, see also Section 1.2). In the 50 years since the discovery of pulsars, several classes of radio transients have been discovered and studied. Some of these other radio sources and their defining properties and timescales include the following: i. Solar bursts. The Sun is a strong source of transient radio emission emitting several types of bursts labeled Types I V on a variety of timescales. Type I solar bursts last for only 1 second and are caused by plasma radiation during periods of sunspot activity; Type III bursts last for several seconds as sub-relativistic electrons accelerate away from the solar surface; and Type II flares emission that originates in outward propagating shock waves can continue for up to 30 minutes. Storms of burst activity have also been observed on the Sun that can last for days to weeks (Dulk, 1985). Most

25 1.1. Transient radio astronomy 3 types of solar bursts are caused by instabilities and variations in the solar plasma (Melrose, 1980) and are typically detected below 200 MHz. ii. Brown dwarfs. Periodic bright transient emission has been observed for a small number of brown dwarfs and low mass stars (Hallinan et al., 2007, 2008). The emission, caused by the electron cyclotron maser instability, originates at the magnetic poles of the star and is up to 100% circularly polarized. For the known pulsing dwarf stars, pulses last for several minutes and repeat on timescales of 2 3 hours, the rotation period of the star (Hallinan et al., 2008). All radio detections of these pulses have been made between 3 5 GHz (Osten et al., 2009; Route & Wolszczan, 2013). iii. Flare stars. Bursts of incoherent emission have been recorded from nearby M dwarfs for over 50 years (Lovell, 1963); however, more recent observations have revealed radio flares of highly circularly polarized coherent emission at frequencies of 1 GHz (Osten, 2008). The coherent flares take place on timescales of a few minutes but are also seen to exhibit temporal variations of the order of a millisecond believed to be intrinsic to the source of the flare on the stellar surface (Osten & Bastian, 2008). The emission mechanism of these coherent flares remains an open question, however the electron cyclotron maser instability observed from brown dwarfs is preferred (Osten, 2008). iv. Radio afterglows from supernovae and gamma-ray bursts. Long-lived radio emission has been detected from supernovae (SNe, Weiler et al., 1982; Sramek et al., 1984) and gamma-ray bursts (GRBs, Kulkarni et al., 1998) in the form of a radio afterglow following the peaked emission in the optical (for SNe, Weiler et al., 1982) and the gamma-ray and X-ray (for GRBs, Galama et al., 1998). Radio emission has been observed in connection with Type Ib/c, and Type II (core collapse) events peaking at various timescales with respect to the optical transient. Type Ib/c radio emission is seen to peak nearly simultaneously with the optical peak, whereas Type II emission peaks months after the optical maximum (e.g. Weiler et al., 2002). The source of the radio emission from supernovae is thought to be the collision of the supernova shock wave into the ionized circumstellar medium producing incoherent synchrotron radiation visible across a range of radio frequencies (Weiler et al., 1982). Whereas optical brightening of supernovae can be observed for many days before and after the peak, gamma-ray bursts are of much shorter duration; e.g. as a canonical long gamma-ray burst, caused by the rapid collapse of a high-mass star into a black hole (Woosley & Bloom, 2006), is visible only on second timescales at gamma-ray frequencies (Weiler et al., 2002). Only a subset of GRBs have observed radio counterparts;

26 4 Chapter 1. Introduction based on available data, Chandra & Frail (2012) estimate approximately 31% of GRBs have detectable radio afterglows. Afterglows of GRBs are observed in X-ray, optical, and radio as the columnized jet from the GRB moves through the interstellar medium near the source and produces incoherent synchrotron radiation. As the jet travels further away from the source the energy of the emission decreases resulting in an afterglow spectrum that peaks first in X-rays then optical and finally radio frequencies (van Paradijs et al., 2000). Radio afterglows are seen anywhere from 0 to 80 days post-burst (Chandra & Frail, 2012). v. Unknown origin. A subset of radio transients have been detected only once, and no rigorous physical model exists for their progenitors. Of this small subset, the Wow signal is likely the most widely known. The signal was detected as a 72-second peak of radio emission at 1.4 GHz during a drift scan of the sky for signals as part of the Search for Extraterrestrial Intelligence (SETI) at Ohio State University (Kraus, 1979). A terrestrial origin was determined to be unlikely based on the detection in only one of two beams on the sky. A proposed explanation of the signal was artificial boosting of the source brightness due to interstellar scintillation, but a VLA search of the detection region revealed no sources at that frequency in a search with 100 times the sensitivity of the original detection receiver making scintillation an unlikely cause (Gray & Marvel, 2001). Ultimately no conclusive evidence has been put forward for the signal s astrophysical or terrestrial origin and it remains an anomaly. For each of these sources we can calculate a brightness temperature, or the temperature required to produce the observed radio intensity from a black body radiating in the classical Raleigh-Jeans part of the Planck spectrum (Lorimer & Kramer, 2004, 3.4). For a source at a distance D with a width (or duration) W and peak flux S emitted at a frequency the brightness temperature will be S.D T B & W 2 Jy.kpc 2 K. (1.1) GHz.ms It has been shown by Kellermann et al. (1969) that brightness temperatures above T B K cannot be produced by incoherent emission processes such as synchrotron radiation and must instead be produced through coherent emission processes, although coherent synchrotron emission may still be possible at these high brightness temperatures (Caroff & Scargle, 1970). Typical brightness temperatures for classes of short-duration radio transients are of the order of K for solar bursts, K for pulses from brown dwarfs and 10 14

27 1.2. Pulsars 5 K for the coherent radio flares from flare stars (Dulk, 1985; Hallinan et al., 2008; Osten, 2008). Single pulses from pulsars stand out from the transient classes listed above in their extremely short duration (second to nanosecond timescales) and relatively high brightness temperatures. The observed single pulses from pulsars span several orders of magnitudes ranging from T B K for the least energetic observable pulses to Kfor the nanosecond bursts of coherent emission from the Crab pulsar (Hankins et al., 2003; Lorimer & Kramer, 2004, 3.4). The radio transient parameter space is presented in Figure 1.1, from Macquart et al. (2015). The single pulses from pulsars occupy an extreme area of this parameter space high brightness temperatures and short transient timescales; however the pulses from the emerging population of sources called Fast Radio Bursts (FRBs) are more extreme still. Since these pulses are thought to originate from outside the Galaxy (see Section 1.3) the inferred brightness temperatures and peak luminosities of the progenitors are required to be 10 orders of magnitude greater than the pulses from normal pulsars. These two classes of extreme phenomena, pulsars and fast radio bursts, are discussed in the following sections. 1.2 Pulsars Pulsars were discovered through their periodic single pulses in 1967 (Hewish et al., 1968) and since then a population of over 2000 pulsars has been discovered 1 (Manchester et al., 2005). Soon after their discovery the link was made between the observed periodic pulses and the theoretical objects called neutron stars (NSs) thought to be formed in the gravitational collapse of an intermediate mass star during a supernova (Baade & Zwicky, 1934). It is now widely accepted that the pulsar emission is from rapidly rotating, highly magnetized neutron stars and is generated in the open magnetic field line region at the star s magnetic poles. As the star spins, the highly focused beams of radiation from the poles sweep across the sky like a lighthouse and if one of these beams intersects the line of sight with Earth the star is seen as a pulsar. The pulsar emission mechanism is poorly understood (Melrose, 1992). The radio emission is thought to be generated by charged particles accelerated along open magnetic field lines at the polar caps; however, the actual process by which this occurs is unknown. Pulsar emission is also relatively broadband most pulsars are observable from GHz down to 100s and even 10s of MHz in frequency with a spectral index of between 1.4 and 2 (i.e. 1 For a complete list of known pulsars see the pulsar catalogue

28 6 Chapter 1. Introduction Figure 1.1 The parameter space of radio transients reproduced from Macquart et al. (2015) illustrating the wide range of transient radio phenomena. Several classes of transients are labeled including solar bursts, flare stars, single pulses from pulsars, and fast radio bursts. Lines of constant brightness temperature are shown diagonally. Sources in the blue triangle produce radio emission through incoherent emission processes, at T B apple K and coherent emission processes occur above this boundary. The 1 kpc and 1 Gpc sensitivity curves are shown for Parkes (black), and two components of the Square Kilometre Array(SKA): SKA1-LOW (pink), and SKA1-MID (grey).

29 1.2. Pulsars 7 pulsars are brighter at lower frequencies), although some exhibit spectral turnover and have lower flux densities than expected at lower frequencies (Karastergiou et al., 2014). More recently, gamma-ray emission has been detected from both young and old pulsars (Abdo et al., 2009). The gamma-ray emission peak is typically offset from the peak radio pulse suggesting that emission at high energies takes place in the pulsar magnetosphere, further from the surface than the narrowly-beamed radio emission (Weltevrede et al., 2010a). The pulsar population can be divided into two general categories the normal (or canonical) pulsars and the millisecond pulsars (MSPs). Canonical pulsars represent the majority of the pulsar population and have spin periods P 500 ms and period derivatives P ss 1 ; in contrast millisecond pulsars have typical values of P 5 ms and P ss 1 (Lorimer & Kramer, 2004, 1.3). The evolutionary histories of these two classes are also very different. MSPs are formed when a canonical pulsar in a binary system accretes mass from a companion into a disk around the neutron star; the accretion from this disk onto the NS surface is responsible for spinning up the pulsar (Alpar et al., 1982). Approximately 80% of MSPs still reside within binary systems (Grégoire & Knödlseder, 2013). As pulsars are descendants of main sequence stars, their population is highly concentrated in the plane of the Galaxy (see Figure 1.2); however, many pulsars are moving at high velocities out of the plane, possibly due to natal kicks (van den Heuvel & van Paradijs, 1997). Consequently the older age, and by extension longer travel time, of the MSP population results in a more uniform distribution on the sky than the canonical pulsar population. The incredibly stable periods of pulsars, especially of the MSPs, make pulsars excellent probes of gravity and extreme physics (Matsakis et al., 1997; Lattimer & Prakash, 2007; Hobbs et al., 2012). Through precision timing of pulsars the dynamics of the binary systems, the parameters of their orbits, and the masses of their companions can be measured extremely accurately. For example, the energy lost in the decaying orbit of the NS-NS system observed via the pulsar PSR B agrees with the expected emission of gravitational waves predicted by general relativity to within 0.3%: the first detection, although indirect, of gravitational radiation (Taylor et al., 1979; Weisberg et al., 2010). Similarly, precise determination of neutron star masses in the double pulsar system PSRs J A&B allowed the most stringent test of general relativity in the strong-field regime (to 99.5% precision; Kramer et al., 2006) by comparing the observed properties of the relativistic orbit with the parameters predicted by general relativity. Besides being excellent probes of gravity, pulsars are powerful tools for studying the interstellar medium (ISM) of our Galaxy. As radio pulses travel through the Galaxy they

30 8 Chapter 1. Introduction Figure 1.2 The distribution of known pulsars in Galactic longitude and latitude in an Aitoff projection. The figure includes normal pulsars (black circles), MSPs (blue triangles), and RRATs (red stars). experience propagation effects caused by the ionized material in the ISM. The four main effects on a radio pulse traveling through the ISM are dispersion, scintillation, scattering, and Faraday rotation which we will discuss in the next four subsections. Dispersive effects on plane waves are most pronounced at low frequencies, thus astrophysical radio pulses are ideal for studies of the magnetoionic medium along the line of sight to the source Dispersion Dispersion is observed as the frequency-dependent group velocity of radio waves. In the interstellar medium, radio signals experience a delay that is proportional to the integrated electron column density along the line of sight, such that the time delay between two frequencies high and low will be apple low 2 t = GHz high 2 GHz R d 0 n ed` ms (1.2) pc cm 3 where the integral R d 0 n ed` is the integrated electron density n e along the line of sight to a source at distance d (Ekers & Moffet, 1968). This frequency-dependent delay can be seen in the frequency-time spectrum of a pulsar in Figure 1.3. The integral in Equation 1.2 is commonly defined as the dispersion measure (DM) which can be determined for a pulse

31 1.2. Pulsars 9 Figure 1.3 The frequency-time spectrum of the radio pulsar J over a range of 64 frequency channels between 710 and 760 MHz as a function of pulse phase. The pulse experiences a frequency dependent delay as it travels through the ionized interstellar medium causing the pulsar pulse to arrive later in lower frequency channels. The pulsar signal has been summed over several pulse periods to achieve a high signal to noise ratio. recorded over a finite bandwidth by measuring the time delay as a function of frequency. DM measurements for pulsars combined with electron density models of the Galaxy are used to estimate distances to Galactic pulsars. The most commonly used model of this type is NE2001, developed by Cordes & Lazio (2002), which models an elaborate, multicomponent Galaxy accounting for spiral arms, thin and thick disks, and an outer halo. Distances estimated via DM are calibrated against parallax distances; however, these measurements are possible for only about 2% of the pulsar population (Brisken et al., 2002). As such this model is highly uncertain and errors of the order of a factor of two in the model-derived distances are to be expected, especially in regions such as the Galactic halo where the population of pulsars is sparse. DM is measured in units of pc cm 3 and typical values for Galactic pulsars range from only 2 pc cm 3 for the closest sources to >1700 pc cm 3 for pulsars near the centre of our Galaxy (Eatough et al., 2013). For most purposes, a pulsar s dispersion measure is treated as a constant, however some studies over multi-year timescales have detected dispersion measure variations due to changes in the amount of ionized material along the line of sight (Hamilton et al., 1985; Backer et al., 1993). Most variations reported in the literature have been attributed to supernova remnants or pulsar wind nebulae local to the pulsar; however,

32 10 Chapter 1. Introduction some studies have shown variations on timescales of a few years due to the structure of the ISM on larger scales (Keith et al., 2013). The interstellar medium is believed to contain turbulence within the larger smooth distribution of ionized material. The spectral energy density scale of interstellar turbulence is thought to obey a power law between large (10 18 m) and small (10 6 m) spatial scales, q, suchthat P 3N (q) CNq 2 (1.3) represents the power spectrum of the electron density P 3N with a spectral index and a structure coefficient CN 2 (Armstrong et al., 1981). This spectrum is thought to be consistent with a Kolmogorov power law described by = 11/3, shown in Figure 1.4. Turbulent interstellar material is probed on various scales by different types of observable phenomena, from rotation measure variations at the largest scales, to dispersion measure variations on intermediate scales, to weak interstellar scintillation at the smallest scales (Armstrong et al., 1995). Variations in pulsar dispersion properties on day to decade timescales are able to probe various regimes of this power law. The turbulent plasma in the ISM is also the cause of the scattering and scintillation phenomena described in the following sections Scattering Multi-path propagation through a turbulent ISM can produce an exponential scattering tail on the trailing edge of the pulsar pulse (Armstrong et al., 1995). The simplest model that can reproduce the observed results of scattering in the ISM is that of a single thin screen (Williamson, 1972). In this approximation, a plane wave experiences distortions due to propagation through a screen of inhomogeneous plasma. The scattering effect is maximized when the scattering screen is located halfway between the source and the observer. In this model the wave experiences a number of phase variations as it travels through the plasma; these arise from the deflection of light by an angle 0, which also produces a broadened image of the source with angular radius d such that e2 d = 0 /2= 2 m e p n p e d a 2 (1.4) where n e is the perturbation in electron density, a is the width of the screen, d is the distance to the source, and is the frequency. The intensity distribution of the light coming from the pulsar through the screen has an angular dependence which also corresponds to a geometric time delay t. The intensity of the scattered pulse as a function of time is

33 1.2. Pulsars 11 Figure 1.4 The power law relation between spectral energy density and spatial scale for turbulence in the ionized ISM in terms of spatial wavenumber, or (spatial scale) 1,and spectral density. A line representing a spectral index of 4 (dot-dashed) and a Kolmogorov spectral index of 11/3 (dotted) are shown. Figure reproduced from Armstrong et al. (1995). given by I( t) / exp( c t/ 2 d d) e t/ d (1.5) where d is defined as the scattering timescale. From Eq. 1.4: d = 2 d d c = e4 4 2 m 2 e n 2 e a d 4 / d 4. (1.6) From this equation we see that the scattering timescale is dependent on distance and heavily dependent on observing frequency. Thus scattering is stronger at larger distances and often correlates with DM. The relation in Eq. 1.6 is a theoretical approximation based upon a single thin screen. In reality the interstellar medium is made up of a large number of scattering screens; however, the observational data from pulsars agrees well with the thin screen model which, to close approximation, can reproduce the exponential scattering tails observed for many pulsars (Sutton, 1971; Williamson, 1972). The observed scattering relation for pulsars has been approximated by Bhat et al. (2004) by

34 12 Chapter 1. Introduction Figure 1.5 A cartoon of the thin screen scattering model for radio pulses from a pulsar. A wave encountering a plasma screen half way between source and observer is distorted and deflected through the screen with propagation delays away from the direct line of sight. The result is a scatter-broadened image of the source which appears to have a radius d. Figure reproduced from Lorimer & Kramer (2004). log d = a + b (logdm) + c (logdm) 2 log (1.7) where d is the scattering timescale in ms, is the observing frequency in GHz, and DM is the dispersion measure. The coefficients a, b, c, as well as the scattering index were fit to the data for Galactic pulsars to obtain values of a = 6.46, b =0.154, c =1.07, and = 3.86 ± This relation is useful when the scattering timescale cannot be directly measured observationally for a pulsar with a known DM; however, in observational data there are several orders of magnitude of scatter around this relation, especially at higher DMs (Bhat et al., 2004) Interstellar scintillation Multi-path propagation through turbulent regions leads to patterns of constructive and destructive interference observed as brightness variability that makes the pulsar appear to scintillate, or twinkle (Armstrong et al., 1995). Scintillation is seen as the observer travels through the interference pattern created by the thin screen. This interference pattern (shown on the right hand side of Figure 1.5) arises because the paths of light through the medium have a range of phases such that the characteristic phase difference is (Rickett, 1977) 2 d. (1.8)

35 1.2. Pulsars 13 This interference pattern depends on the movement through space of both the pulsar and the scattering screen, as well as the velocity of the observer. The timescale t on which the intensity fluctuates depends on all three velocity components. Interference in the plasma becomes decorrelated if the phase differences between scattered waves are more than approximately 1 radian; i.e. when 2 d 1 (1.9) where is the decorrelation bandwidth, also called the scintillation bandwidth and is the typical bandwidth of correlated intensity fluctuations for a source. From Eq. 1.9, the scintillation bandwidth scales as 1/ d / 4. Scintillation occurs over a range of scales and typically two scintillation regimes are defined: diffractive and refractive. Diffractive scintillation is caused by turbulence on smaller length scales ( m) and results in intensity fluctuations on short timescales of the order seconds to minutes. Refractive scintillation is caused by turbulence on larger scales ( m) and manifests itself as longterm variations from hours to days. Diffractive scintillation is primarily seen in observations of pulsars and refractive scintillation is most often observed in the brightness fluctuations of distant quasars at GHz frequencies (Kaspi & Stinebring, 1992; Burke & Graham-Smith, 2014). In pulsar observations scintillation can present itself in two forms: strong and weak scintillation. Strong scintillation occurs when both refractive and diffractive effects combine in the scintillation seen from the pulsar at various spatial scales. Weak scintillation occurs when variations in phase are small at the distance of the observer and diffractive and refractive effects are minimal. Pulsar observations are typically made in the strong scintillation regime unless observing sources that are very nearby or making observations at high frequencies (Rickett, 1977) Faraday rotation A radio pulse that is linearly polarized in a single plane can also be described as the sum of two oppositely handed circularly polarized waves. If the plasma through which a radio pulse travels is magnetized parallel to the direction of propagation, the two circularly polarized waves will propagate at different speeds relative to one another. This differential phase rotation, proportional to the magnetic field strength, is called Faraday rotation. The ionized plasma of the interstellar medium is permeated by the Galactic magnetic field and these phase rotations are observed in the form of Faraday rotation of linearly polarized pulses from pulsars. The differential phase rotation between left- and right-

36 14 Chapter 1. Introduction handed polarized waves propagating through the medium is given by = e 3 m 2 ec 2 2 Z d 0 n e B k d` (1.10) where the integral is over the same distance as the DM from Eq. 1.2 and B k is the parallel component of the magnetic field along the line of sight. The differential phase rotation is periodic in phase on 2 ; however, the physical manifestation of this phenomenon, the rotation of the polarization position angle (PPA) relates to the plane in which the linear polarization oscillates and is therefore periodic on (Everett & Weisberg, 2001). Thus, where RM is the rotation measure RM = PPA = /2 =RM 2 (1.11) e 3 2 m 2 ec 4 Z d 0 n e B k d` (1.12) and has units of rad m 2. The RM for a given observation is measured experimentally through the frequency-dependent phase rotation of the linear polarization Stokes parameters Q and U through a fit with respect to the phase rotation at the center frequency of the band such that ( )= 0 +RM 2. Through measurement of the RM and DM of a pulse it is possible to obtain the average magnetic field weighted by the local electron density along the line of sight (Smith, 1968; Han et al., 2006) hb k i = R d 0 n eb k d` RM R d 0 n =1.23µG ed` rad m 2 DM 1 pc cm 3. (1.13) While the combined measurements of RM and DM of polarized, dispersed pulses can be a powerful tool for measuring the magnetic field in the interstellar plasma there are a few cases in which this method is a poor measure of hb k i. Firstly, when free electrons are concentrated in a dense region along the line of sight, such as in an H ii region, the effect of the magnetic field in that region will dominate and the average magnetic field strength will be overestimated. Secondly, when sign reversals of the magnetic field occur along the line of sight, such as the field reversals observed between spiral arms of the Galaxy (Han et al., 2006), the average magnetic field strength will be underestimated. In these two cases, the value obtained from the calculation in Eq will not accurately reflect the large scale magnetic field along a line of sight. Studies of the effects of dispersion, scattering, scintillation, and Faraday rotation, com-

37 1.2. Pulsars 15 bined with accurate information about the location of a pulsar within the Galaxy produce a picture of the shape, size, density, and magnetic fields of the Galaxy in different regions (Rand & Kulkarni, 1989; Rand & Lyne, 1994; Han et al., 2006). In addition, variations of observed flux and dispersion over short (seconds to days) and long (months to years) timescales encode the structure of the turbulence in the ISM and the local environment of the pulsar (Keith et al., 2013). Thus the pulses from pulsars are some of the most powerful tools available for studying the makeup and distribution of the material in the Galaxy Pulsar searches and rotating radio transients Numerous radio surveys designed to detect new pulsars have been undertaken since the very first pulsar discovery. Several bright pulsars were subsequently found through searches for individual pulses (Lyne & Rickett, 1968; Staelin & Reifenstein, 1968). However, as radio pulsar surveys began collecting more data, the primary method of pulsar searching shifted to periodicity searches using discrete Fourier transforms (Hulse & Taylor, 1974). These surveys were incredibly productive, with some effectively doubling the known population of pulsars with a single publication (Manchester et al., 1978). In just under 50 years the number of known radio pulsars has grown from 1 to over 2300 (Manchester et al., 2005) with even more new sources expected in upcoming surveys (Bates et al., 2014). As periodicity searches became the method de rigueur for finding large numbers of pulsars, single pulse searches were abandoned in the 1980s and 1990s. In 2006, however, McLaughlin & et al. (2006) published the results of a new single pulse search of the archival Parkes Multibeam Pulsar Survey (PMPS) data in which they detected eleven objects via single pulse emission. These objects, called Rotating Radio Transients (RRATs), are pulsars that emit detectable radio pulses for only a fraction of the time, with intervals between pulses of minutes to hours. Most RRATs are difficult to detect in periodicity searches, and are best identified through single pulse processing. RRATs represent only about 3% of the known pulsar population, but an estimate of their overall numbers in the Galaxy based on their observed variability implies an enormous source population, larger than the estimated population of regularly-emitting radio pulsars (Burke-Spolaor & Bailes, 2010; Keane et al., 2011). If RRATs are a separate population they generate large discrepancies between the population size and the rate of core-collapse supernovae in the Galaxy, which are thought to be the progenitors of neutron stars (Keane & Kramer, 2008). Such a conflict is partially resolved if RRATs are part of the normal pulsar population and represent a particular phase in their evolution. The position occupied by RRATs in the pulsar population is still poorly understood

38 16 Chapter 1. Introduction and estimates of period, period derivative, and age have been made for only around 60 objects. 2 A key objective for recent pulsar surveys has been the search for new RRATs through single pulse searches. The largest concerted effort in this area has been the High Time Resolution Universe survey (HTRU) undertaken with the Parkes radio telescope. The search techniques employed by this survey are described in Chapter Fast Radio Bursts The interest in single pulse searches was revitalized by the discovery of RRATs and, beginning with their discovery in 2006, single pulse searches were carried out on both archival data and new survey observations. As a result of these searches, a single bright pulse was discovered by Lorimer et al. (2007) in archival data from 2001 (Figure 1.6). This pulse, now called the Lorimer burst was detected with a peak flux density of 20 Jy and a DM of 375 pc cm 3 at a high Galactic latitude (b = 41.8 ). The Galactic DM contribution along this line of sight predicted by the NE2001 model is 25 pc cm 3,onlyabout5% of the total DM. The excess dispersion is postulated to arise in the intergalactic medium (IGM), placing the source far outside our Galaxy. For some time the Lorimer burst was the only one of its kind. Only recently, similar bursts have been discovered in contemporary (Thornton et al., 2013; Ravi et al., 2015) and archival (Keane et al., 2012; Burke-Spolaor & Bannister, 2014; Spitler et al., 2014; Masui et al., 2015) radio pulsar surveys, revealing a population of highly dispersed pulses now known as fast radio bursts (FRBs). The observational definition of an FRB is, at the time of writing, slightly tenuous. An FRB is generally defined as a bright (flux density, S & 0.5 Jy), narrow (width, W. 5 ms) single pulse with a DM greater than the modeled DM contribution of the Galaxy along a line of sight. For all but one of the 21 known FRBs the ratio DM FRB /DM Galaxy > 2.5. The one exception to this is FRB which was discovered very close to the Galactic plane by Keane et al. (2012) with a DM of 746 ± 1 pc cm 3 ; for this FRB the DM is only 40% greater than the expected contribution due to free electrons in the Galaxy. Recent investigation by Bannister & Madsen (2014) suggested an overdensity in the ionized material along this line of sight, which would make this burst Galactic, possibly due to an RRAT, a Galactic FRB progenitor, or another unknown source. Given the large uncertainties in the NE2001 model, a definition of an FRB based on a 2 A full list of RRAT sources can be found at 3 The naming convention for FRBs is based on the date of detection, so an FRB detected on 2015 March 29 would be FRB

39 1.3. Fast Radio Bursts 17 Figure 1.6 The frequency-time spectrum of the primary discovery beam for FRB (the Lorimer Burst) discovered in The single bright pulse has a dispersion measure of 375 pc cm 3 of which only 5% is accounted by the model of free electrons in the ISM. The detection in the discovery beam (beam 6) was bright enough to saturate the automatic gain controller used at the time, causing the total intensity to drop below the baseline after the pulse.

40 18 Chapter 1. Introduction threshold ratio between the observed DM and that of the model is not robust, especially given that the model is poorly constrained in the halo (Cordes & Lazio, 2002) and the majority of FRBs to date have been found at high Galactic latitudes (Keane & Petroff, 2015). However, adopting an error on NE2001 of 50% to account for the unknown parameters of the Galactic halo, all FRBs but FRB have DMs not easily accounted for purely by the cold plasma of the ISM Distances, energies, and brightness temperature If the majority of the excess DM is due to the IGM, which is 1000 times less dense than the ISM of the Milky Way (Ioka, 2003), then the progenitors of FRBs would be located at cosmological distance. The excess DM for these objects might arise in a number of different regions along the line of sight, such that DM FRB =DM Galaxy +DM anomaly +DM IGM +DM host +DM source (1.14) where the subscripts indicate the DM contributions from the Galactic ISM, anomalous regions in the ISM such as local overdensities, the IGM, a host galaxy, and any contribution local to the source. If the interstellar medium in the host galaxy has properties similar to our own ISM and FRBs are not produced in overdense regions, then the host ISM would contribute little to the total DM except the fraction of the host galaxies where the host has a high inclination angle (i >85 ). Barring this orientation, assuming FRB host galaxies are randomly oriented with respect to the observer, the majority of the excess DM would be due to the IGM between the progenitor and the observer. No exact measurement relating DM to redshift, z, is currently published and FRBs could be the first sources to make such a measurement possible if an independent distance measurement to the host can be made after an FRB detection (Macquart et al., 2015). However, models of the ionized IGM allow a rough estimate of FRB distances. The two models currently in use are those by Ioka (2003) and Inoue (2004), both of which propose a roughly linear relationship between DM and redshift out to z. 3 where helium reionization begins to strongly affect the electron density of the IGM (McQuinn et al., 2009). The conversion factor that will be used throughout this thesis is z apple (DM tot DM Galaxy ) 1200 pc cm 3 (1.15) where DM Galaxy is an estimate taken from the NE2001 model integrated out to the edge of the Galaxy. Eq becomes an equality only when DM host =DM source =0in Eq. 1.14

41 1.3. Fast Radio Bursts 19 and as such this relation provides only a very rough upper limit on the actual redshift of the source. Precise measurements of FRB redshifts could open the door to exciting new avenues of cosmological study only possible with these sources; these possibilities are discussed further in Chapter 8. For a radio pulse at some redshift the distance can be calculated by assuming a model for the expansion of the Universe. A flat Universe CDM is typically used (Wright, 2006) and two different distance parameters are obtained: the co-moving distance D comov and the luminosity distance D L. The co-moving distance takes the expansion of the Universe into account, provides a distance measure that does not change in time, and can be viewed as the physical distance to the source. The luminosity distance is essentially the distance derived from the observed flux using the inverse square law, or D 2 L = L/(4 S) (1.16) where L is the luminosity and S is the observed flux; the luminosity distance is the relevant quantity for calculating the energetics of an object at some redshift. The energy of an FRB E FRB at a redshift z is calculated by E FRB = F obs Jy ms 2 DL m Hz (1 + z) 1 Joules (1.17) where F obs = S obs W is the observed fluence, and is the observing bandwidth (Thornton et al., 2013; Keane & Petroff, 2015). Using distances derived from the redshifts estimated using Eq. 1.15, the known FRBs have estimated energies between Joules and are located at co-moving distances between 1 and 3 Gpc; however, these are upper limits given the large uncertainty on the true redshift (Keane & Petroff, 2015). An effective brightness temperature can also be calculated for each FRB given the flux, distance, width, and observing frequency, similar to Eq. 1.1; however, relevant equations require the luminosity distance and a corrective factor due to frequency dilation over the expanding Universe such that T B ' K Speak Jy 2 DL W 2 (1 + z) 4 (1.18) Gpc GHz ms 2 where is the Lorentz factor used to account for relativistic beaming effects ( =1is used here as the beaming process is unknown for the FRB emission mechanism). The population of FRBs discovered to date have estimated brightness temperatures T B K, which is orders of magnitude greater than any other transient population discussed in

42 20 Chapter 1. Introduction Section 1.1 with the exception of the nanoshot pulses observed from the Crab pulsar. Such high brightness temperatures require coherent emission well above the K cutoff for incoherent synchrotron emission FRB rates and progenitor theories The true progenitor (or progenitors) of FRBs remains unknown although a large number of theories exist to explain their origin. Currently, the number of theories for their sources is greater than the total number of known FRBs and none of them have been conclusively proven correct. Indeed, some of the current theories may be difficult to verify or refute on timescales of human civilization. Theories for the progenitors of FRBs must not only explain the large DMs and seemingly high brightness temperatures, but they must also be consistent with the very high FRB event rates inferred from current observations. The current best rate estimate in the published literature comes from the detection of 4 FRBs in 24% of the HTRU high latitude survey by Thornton et al. (2013). From this survey the rate can be calculated as R FRB (F 3Jyms) sky 1 day 1. (1.19) The inequality in the equation is due to a fluence incompleteness at broader pulse widths (Keane & Petroff, 2015). This incredibly high rate several thousand FRBs per day is approximately equal to the all-sky rate of core-collapse supernovae (Thornton et al., 2013), but places a difficult constraint on any progenitor theory. We provide an updated rate based on the full HTRU high latitude survey in Chapter 6. Here we discuss only a handful of the most promising theories based on their prevalence in the published literature and their testability. In the following paragraphs we will discuss theories for FRBs as magnetar hyperflares, blitzars, giant pulses from extragalactic pulsars, and pulsars in nearby galaxies. i. Magnetar hyperflares. In this model first put forward in Popov & Postnov (2010) a short radio pulse can be generated during a highly energetic flare from a neutron star with a high magnetic field strength, a magnetar. Observed X-ray flares from magnetars are thought to be caused by reconnection of magnetic field lines on the surface of the star, and can be extremely violent events (Hurley et al., 2005). As the shock from a flare propagates outward it may create a highly relativistic forward shock. Lyubarsky (2014) proposes that a coherent synchrotron maser may be produced at the shock front which would be responsible for the millisecond duration radio emission seen as an FRB.

43 1.3. Fast Radio Bursts 21 This model can elegantly explain both the high brightness temperature and the high rate seen for FRBs, as the rate for such flares over cosmological volume should be similar to that derived for FRBs (Thornton et al., 2013; Kulkarni et al., 2014). Many observable magnetars in our Galaxy lie in overdense regions such as within supernova remnants or near the Galactic Center (Eatough et al., 2013). If the FRB progenitors lay in similarly dense regions the contribution of DM source to the total DM would be significant, greatly reducing the true redshift and distance. ii. Blitzars. A blitzar is the theoretical emission from a neutron star as it collapses to form a black hole. Falcke & Rezzolla (2014) propose that a neutron star created above the theoretical mass limit, but able to maintain its state due to its high rotational velocity, eventually spins down over thousands to millions of years due to magnetic braking. At a certain point the star is no longer able to maintain itself against gravitational collapse and the neutron star forms a black hole at which point a strong shock will propagate outwards, disrupting the neutron star magnetosphere and producing bright radio emission. In this scenario the characteristic timescale for such an event would be of the order of the free-fall timescale of the collapsing material, estimated to be. 1 ms (Falcke & Rezzolla, 2014). The shock may manifest itself observationally as a sort of magnified pulsar emission, which would produce the required high brightness temperature and occur on the timescale of the collapse. Falcke & Rezzolla (2014) also argue that the rate is sufficiently high to explain the observed FRB rate as blitzars would need to occur as only a small subset ( 3%) of the core-collapse supernova population out to z apple 1 to be consistent with FRB observations. The cataclysmic nature of the blitzar progenitor implies a population of non-repeating sources. iii. Giant pulses from pulsars. Cordes & Wasserman (2015) have suggested that individual energetic pulses from extragalactic pulsars may be responsible for the observed FRB population. The brightest pulse from the Crab pulsar over its lifetime would be visible above current detection thresholds within a distance of 300 Mpc and similar abnormally bright pulses from a population of pulsars within this distance may be the source of FRBs. If each pulsar within a distance of 100 Mpc emits such pulses over their lifetime it would be enough to make this population consistent with the FRB rate. However, given that the giant pulses emitted from the Crab are not typical of the pulsar population as a whole, Cordes & Wasserman (2015) argue that a cosmological population is preferred in which pulsars out to z. 1 emit these giant pulses which might then be magnified through gravitational lensing of individual stars.

44 22 Chapter 1. Introduction If such pulses are similar to those from the Crab it is more likely that an individual energetic pulse will be made up of a number of individual shot pulses that remain unresolved in current observations, such as the nanoshots seen from the Crab that are modulated with a Gaussian envelope (Hankins & Eilek, 2007). While the energetics and rate arguments align well with the properties of FRBs, Cordes & Wasserman (2015) acknowledge that even though the population itself is made of repeating sources the probability of seeing a repeat pulse from such an object is extremely low on human timescales. iv. Pulsars in nearby galaxies. An extragalactic but non-cosmological origin for FRBs has recently been proposed in both Pen & Connor (2015) and Connor et al. (2015) suggesting that FRBs are bursts from local magnetars and young pulsars within 200 Mpc. In these models the FRB progenitor is an energetic and highly active neutron star that lies in a very dense region. Magnetars are observed to lie in overdense regions (Kulkarni et al., 2014) and young neutron stars are often still embedded within the supernova remnant left over from their birth. In both cases the removal of the z term in Eq makes it much easier to satisfy energetics requirements. In the case of a young energetic pulsar in a supernova remnant, if the number of young pulsars is proportional to the core-collapse supernova rate and each pulsar emits a giant pulse every 100 days, then the FRB rate is satisfied within the local volume out to about 200 Mpc (Connor et al., 2015). Given that magnetar giant flares are much less frequent than once every 100 days (Turolla et al., 2015), and that the population of magnetars is smaller than that of young pulsars, this model is difficult to reconcile with the large overall FRB rate; however, due to their proximity, much smaller flares could be detected than from magnetars at cosmological distances. In each of the cases listed above one common thread emerges neutron star emission or interaction with the circumstellar medium as the progenitor for FRBs. The large amount of energy released by neutron stars, combined with their ability to generate coherent emission from a small emission region, and their residence in extreme environments make them likely candidates for the type of short, extreme emission necessary to produce the observed pulses from FRBs. Many models of the FRB population assume for simplicity that each burst is a standard candle, i.e. every FRB has the same intrinsic luminosity (Lorimer et al., 2013; Hassall et al., 2013; Macquart & Johnston, 2015). The interest in whether or not FRBs are standard candles is considerable, as this would have profound implications for determining

45 1.3. Fast Radio Bursts 23 FRB distances without the need to identify a host galaxy. Additionally, a standard candle emission mechanism would make strong constraints on possible emission physics and progenitor theories. Currently, however, the population of known FRBs is not sufficient to make these measurements Pulse propagation As FRB pulses travel through the ionized plasma in the host, IGM, and ISM they should experience the same effects of dispersion, scattering, Faraday rotation, and possibly scintillation, described in Sections through Dispersive effects in the IGM and the ISM are essentially the same as both are within the cold plasma regime. The only difference between the traditional DM measured for pulsars and the dispersion measured for FRBs is that, due to the expansion of the Universe, the frequency at which the FRB is observed is redshifted from the emitted frequency. At higher frequencies the dispersive effects are less severe and thus the measured DM for FRBs is slightly weighted towards the electrons in the local Universe, as those in the host galaxy and medium local to the progenitor have less effect. The redshift effect for dispersion holds true for Faraday rotation as well. The linearly polarized light from the source will experience less Faraday rotation at the higher emitted frequency than it will when traveling through the interstellar medium of our own Galaxy. This has been quantified by Hammond et al. (2012) as Z zs n e (z)b k (z) dl RM(z s )= (1 + z) 2 dz dz rad m 2 (1.20) for polarized, extragalactic radio sources, where z s is the redshift of the source and the functions n e (z) and B k (z) are the electron density and the magnetic field strength as a function of redshift along the line of sight. Even with an understanding of the weighting of the Faraday rotation along the line of sight, disentangling the effects of these different regimes, especially without an accurate distance to the source, is not currently possible. As with pulsars, maximal scattering of an FRB pulse should occur at a screen halfway between the source and the observer, however for FRBs this places the screen in the middle of the IGM, where turbulence is expected only on very small scales which are unlikely to produce scattering at an observable level for millisecond pulses (Luan & Goldreich, 2014). However, scattering is clearly seen for several FRB pulses (Lorimer et al., 2007; Thornton et al., 2013; Ravi et al., 2015; Chapter 6). The source of the scattering of FRB pulses is still a topic of debate with some arguing that scattering in the IGM is impossible and

46 24 Chapter 1. Introduction must occur in the host (Luan & Goldreich, 2014) while others argue that a host-based scattering origin is not possible and the IGM is a much more likely source of the scattering screen (Macquart & Koay, 2013). McQuinn (2014) has argued that the scattering seen for a subset of FRBs may be due to passing through the extended halo of an intervening galaxy which would act as an ideal scattering screen. This is a promising hypothesis given that it would explain the inconsistent presence of scattering in the FRB population. Ultimately FRBs may be powerful tools for studying extreme physics at cosmological distances, and may also be ideal probes of the ionized material in distant galaxies and in the IGM, both of which have been previously inaccessible. The total population of FRBs known to the author is only 21 sources. Far greater numbers are required to answer some of the questions presented here related to their progenitors, distances, luminosities, and emission mechanisms Perytons Our understanding of the origin of FRBs has been challenged by a second poorly understood class of objects called perytons identified in pulsar survey data (Burke-Spolaor et al., 2011a). Peryton signals mimic the sweep in frequency seen in dispersed astrophysical signals but occur simultaneously in all 13 beams of the multibeam receiver with a similar signal-to-noise ratio (S/N) in each beam. They also have peculiar frequency structure, with all perytons showing bright patches in specific regions of the observing band (Figure 1.7). They have never been successfully associated with any astrophysical source (Kocz et al., 2012). The spacing between beams of the receiver makes it such that an astrophysical pulse will usually occur in one beam, and at most around four beams if the source is so bright as to be visible in sidelobes of neighboring beams. Only one published FRB, the Lorimer burst, was detected in multiple beams, appearing in four adjacent beams of the receiver. However, the Lorimer burst was so exceptionally bright that it saturated the automatic gain controller in the primary beam (Lorimer et al., 2007). Nevertheless, the resemblance between perytons and localised astrophysical sources in their frequency-time spectrum is unsettling (see Figure 1.7 and compare with the FRB in Figure 1.6). However, perytons appear with non-uniform brightness across the observing band and are much broader than FRB pulses ( 30 ms for perytons and <5 ms for FRBs). Until recently it was unknown what source of local radio frequency interference (RFI) might be capable of producing this frequency-dependent time delay. All known perytons were discovered in archival survey data from Parkes taken between the years 1998 and 2003 and all occurred in the middle of the day, which suggests an origin in human activity

47 1.4. Thesis outline 25 Figure 1.7 The frequency-time spectrum of a peryton detected at the Parkes radio telescope. The frequency-time behavior of the pulse mimics the dispersion seen for astrophysical signals; however, the peryton spectrum is less broadband and more clumpy than the spectrum of a typical astrophysical pulse. (Bagchi et al., 2012). Despite differences between FRBs and perytons with respect to many key properties, the peryton problem has led some to question the astrophysical nature of FRBs, implying that they could both be manifestations of the same local signal (Kulkarni et al., 2014). We address the peryton issue and identify their source in Chapter 5 concluding that FRBs and perytons are very unlikely to have the same progenitor and that the astrophysical origin of FRBs remains likely. 1.4 Thesis outline This thesis focuses on the transient radio emission seen from pulsars and fast radio bursts using the single dish Parkes radio telescope. As shown above, short radio pulses provide the ability to study not only energetic and compact objects, but also the ISM (and even the IGM) in a way not possible otherwise. In Chapter 2 we present the technical systems used to detect radio transients at Parkes and how these systems have evolved over time. We introduce one of the most successful transient detection systems to date the Berkeley Parkes Swinburne Recorder (BPSR) and summarize the current real-time transient detection efforts underway. Chapter 3 details a long-term study of 168 young pulsars. The DMs of these pulsars were monitored over more than 6 years to look for dispersion measure variations and

48 26 Chapter 1. Introduction to probe the medium-scale turbulence in the interstellar medium. Of this sample four pulsars were found to have significant DM variations over this time period, likely due to a combination of ISM turbulence and turbulent material local to the source. We use these sources to explore the turbulent scales of the interstellar medium. In Chapter 4 we describe a search of the High Time Resolution Universe (HTRU) survey for fast radio bursts at intermediate and low Galactic latitudes. This search yielded no new FRBs, an unexpected result given the large amount of time on sky compared to previous surveys. This work reveals an absence of fast radio bursts at low Galactic latitudes, largely inconsistent with a homogeneous sky distribution and the current estimates of the FRB rate. This work also shows that Galactic obscuration cannot account for the nondetection of these sources and concludes that a larger population is needed to understand the latitude-dependence of FRB detectability. Chapter 5 reveals the source of the peryton population. Perytons are generated by premature opening of microwave oven doors during a heating cycle and are detected at Parkes when the telescope is at an appropriate angle relative to the oven. We determine that the microwave oven source of perytons cannot explain the observed properties of the FRB population and conclude that they have different origins. Chapter 6 details a renewed search of the HTRU high latitude survey and 5 additional bursts found in the remaining survey pointings and updated rate estimates for the FRB population. A follow-up campaign was conducted for 8 of the FRBs from the survey. In order to rule out sources that repeat on short timescales, detailed follow-up observations are needed. We detected no repeat emission from any FRB in the sample. We place limits on periodically repeating sources with periods less than a day, and completely rule out periodic repeaters with periods apple 8.6 hours. Chapter 7 reports on a fast radio burst FRB discovered in real-time at the Parkes telescope. FRB was the first source detected with full-polarization and was found to be 21 ± 7% circularly polarized, primarily on the leading edge of the pulse, with no detectable linear polarization above the & 10% level. Multi-wavelength follow-up observations were also made for this burst. No variable counterpart was detected in the observations; however, this resulted in the first X-ray, optical, and radio limits on any FRB afterglows. Finally, in Chapter 8 the results detailed in this thesis are reviewed. The future of transient radio astronomy is discussed, with emphasis on the bright prospects of nextgeneration telescopes such as the Square Kilometre Array.

49 2 Technological advances in transient radio astronomy In this chapter we present the technical challenges to observing radio transients. Since the discovery of pulsars, specialized data acquisition hardware and software have been developed to maximize pulsar science. Here we describe some of the most useful advances in radio astronomy instrumentation for pulsar and radio transient observing modes, including the development of the real-time transient detection system in operation at the Parkes radio telescope. 2.1 Data acquisition Single dish radio observations are typically made with orthogonally polarized receptors at the primary focus which couple the electromagnetic signal to two voltage signals. Bright pulses from pulsars and fast radio bursts increase the variance of the voltage output by each receptor. The power of pulses that have been subjected to dispersion is spread, or smeared out in time, making them difficult to detect without some correction for the frequency-dependent time of arrival (see Section 1.2.1). To correct for the effects of dispersion it is necessary to divide the signal into many frequency channels by passing it through a spectrometer. The current spectrometer of choice for pulsar observations is the polyphase filterbank (PFB), which separates the signal into a predetermined number of frequency channels across the bandwidth (Ferris & Saunders, 2004). The PFB is typically implemented using field programmable gate arrays (FPGAs) where the operations are encoded in firmware and highly parallelized (Manchester et al., 2013). Current systems at telescopes such as Parkes record 8-bit data and a PFB with frequency channel width b is able to sample with time resolution 1/b for complex samples 27

50 28 Chapter 2. Technological Introduction (Nyquist, 1928). For a system with 1,024 frequency channels over 400 MHz of bandwidth this corresponds to 1,024 complex 8-bit samples for each polarization every 2.56 µs, a data rate of 1,600 Megabytes (MB) per second. Such a data rate is unsustainable for a large survey given current digital storage facilities. As such, the recorded data are often detected then integrated over multiple time bins to decrease the time resolution. The number of samples over which the data are integrated determines the resulting time resolution of the instrument. In most cases, after integration, the data are also reduced from 8-bit to 2-bit after summing the two polarizations and re-normalizing the data. Decimation in time and bits serves to reduce the data rate to a manageable level ( 1 10 MB/s). However, it is worth noting that this data reduction strategy, performed before recording the data to disk, results in all polarization information being lost as the two independent signals from which polarization properties can be derived are summed, and only total intensity is recorded. While not ideal, this compromise allows the storage of high time resolution data over four times the amount of time on sky than would be possible otherwise. For the processing pipeline described here, the data are written to disk with the programmed time resolution consisting of a time series for each of the individual frequency channels. This is known as the filterbank data format. Filterbank data are extremely versatile as they can be searched for both single pulses and periodic sources. All of this is possible in software using packages like the sigrpoc 1, presto 2, peasoup 3,andheimdall 4 distributions. Searches for new pulsars and single pulses are carried out over a range of DMs (and periods for pulsars) as described in Section 2.2. Alternatively, if the period and DM of a pulsar are well determined, then the pulsar can be timed the arrival time of the pulsar pulses can be compared with a model that predicts the phase of the pulsar s periodic signal. For these observations the data can be added over many pulses at the period of the pulsar to obtain an average or integrated pulse profile. The time of arrival (TOA) of the integrated pulse profile in a single observation can be compared to the predicted arrival time extrapolated from previous timing observations. Deviations of the pulsar TOAs from the model are minimized to improve measurements of the pulsar parameters such as period, period derivative, and any orbital parameters for a pulsar in a binary system. The precise timing of pulsars can be useful for a variety of experiments, from gravitational wave detection using an array of precisely timed pulsars (Hellings & Downs, 1983; Foster & Backer, 1990; Manchester et al., 2013), to comparing the

51 2.1. Data acquisition 29 Figure 2.1 The configuration of the 13-beam Parkes 21-cm multibeam receiver. Individual beams have a full-width half maximum (FWHM) of 14.4 arcminutes. The distance between two beam centers in the x-direction as shown here is equal to the FWHM and the separation in the y-direction is p 3 FWHM, or 25 arcminutes. The center beam is designated by beam 1, the inner ring consists of beams 2 7, and the outer ring consists of beams The numbers labeled on this figure are used as the names of the beams throughout this thesis. emission properties of young pulsars in radio and gamma-rays (Weltevrede et al., 2010b) The Parkes radio telescope Parkes survey data at 1.4 GHz are primarily acquired using the 21-cm multibeam receiver, which has been in operation at the telescope since 1997 (Staveley-Smith et al., 1996) and consists of a central beam surrounded by two concentric hexagonal rings (Figure 2.1). Each beam has a full-width half-maximum (FWHM) on the sky of approximately 14.4 arcminutes at 1 GHz. The gains and widths of the beams are slightly different for the inner and outer rings of the receiver and are listed in Table 2.1. In a single observation, or pointing, individual filterbank files are recorded for each beam and saved separately to disk. For recent surveys at Parkes this has been done using the Berkeley Parkes Swinburne Recorder (BPSR) instrument, which has an FPGA-based polyphase filterbank that passes 64-µs down-sampled data to 13 CPUs which perform the decimation in bits. The data are then recorded to disk, after which they are sent to the Swinburne gstar supercomputer facility via optical fibre for storage and a search can be performed off-line for any single pulses in the data. The advantage of this combined

52 30 Chapter 2. Technological Introduction Table 2.1 Specifications for the 13 beams of the Parkes 21-cm multibeam receiver. Each beam has 2 orthogonal linear polarizations, and a system temperature of 23 K (Keith et al., 2010). The gain and beam width vary for the inner and outer rings and the central beam and are taken to be the values at the centre observing frequency of 1382 MHz. Specifications from Manchester et al. (2001). Beam Center Inner Ring Outer Ring Beam gain (G, KJy 1 ) Beam width (arcmin) hardware/software approach is the flexibility of the system as well as the ability to maintain the full-polarization 8-bit data in CPU memory for a certain amount of time, which is useful in the case of real-time searches (see Section 2.2.2). In the following sections we focus on the methods for finding single pulses in filterbank data including the algorithms used in these searches and the application of these techniques in recent surveys to search for fast radio bursts. 2.2 Detecting single pulses A signal in filterbank data over a bandwidth W will have a maximum signal-to-noise ratio with a peak flux density S peak and width S/N = S peak S sys p np W, (2.1) in a given telescope system where S sys is the system equivalent flux density, and n p is the number of polarizations summed to create the signal. The system equivalent flux density can be related to the configuration of the system by S sys = T sys G, (2.2) where T sys is the system temperature, is a correction factor to account for small losses in the digitization process and G is the telescope gain, which mainly depends on the effective aperture of the telescope. These are a function of telescope parameters and receiver configuration. Using Equation 2.2 in Equation 2.1 gives S/N = S peakg T sys p np W. (2.3) This equation represents the best-case detection S/N for a square pulse once the data have been de-dispersed to the exact DM of the pulse, summed in signal over the entire

53 2.2. Detecting single pulses 31 bandwidth, and integrated for a time t = W (i.e. a boxcar of width W has been used to smooth and decimate the time series). However, the detected width will be greater than the intrinsic width of the pulse due to the recording systems and the effects of the interstellar medium (as presented in Section 1.2). These effects sum in quadrature to yield the detected pulse width, W = q t 2 samp + W 2 int + t2 DM + t2 DMerr + 2 d, (2.4) where t samp is the sampling time of the data, W int is the intrinsic width of the pulse, is the dispersion-induced time delay caused by intra-channel smearing of the pulse such that t DM = 8300 DM b/ 3 for a frequency channel of width b at a frequency (both in MHz), t DMerr is broadening of the pulse due to an error in DM of size DM such that t DMerr = 8300 DM / 3 over a bandwidth where the fractional bandwidth is small, and d is the scattering timescale (Section 1.2.2; Cordes & McLaughlin, 2003). The goal of a survey is to search for pulses of any width contained in the data, which necessitates searching over a wide range of possible DMs and pulse widths for peaks in S/N as a function of time. Given the large parameter space to search, a fixed number of DM trials and boxcar filters over a range of possible pulse widths are used to detect peaks in S/N(t). Several search codes exist to do this, such as dedisperse_all 5, destroy 6, sigproc, presto, andheimdall. All these codes operate in essentially the same way in that they use a list of trial DMs between some DM min and DM max. For each DM trial the data are de-dispersed, integrated in frequency, and searched for pulses over a range of widths. In the search codes mentioned above, the data are searched for pulses with widths W =2 n time samples for n =0, 1, 2,...,12 by convolving the time series with a boxcar filter, essentially a square pulse. In the case of the 64-µs sampling discussed in Section 2.1 these trials correspond to pulse widths W = 0.064, 0.128, 0.256,...,262 ms. The methods for searching for pulses with widths larger than a single sample are slightly different for the different search codes mentioned above. In some cases, such as for dedisperse_all, the data are down-sampled by a factor of 2 for each trial by averaging every two samples (reducing the number of time samples by 2 n for the n-th iteration) and then searched for peaks. If a pulse spans two adjacent decimated time samples then it will be detected with a less than optimal S/N (Figure 2.2). This down-sampling can decrease the S/N by up to 1/ p 2 and has been called the root 2 problem (Keane & Petroff, 2015). The t DM

54 32 Chapter 2. Technological Introduction Figure 2.2 The recovered signal-to-noise ratio (S/N) of a pulse as a function of phase along the time series. In this case the pulse was injected with S/N = 16 and a width of 2 ms. Both heimdall and destroy, with their sliding boxcars, recover the maximum S/N p throughout. dedisperse_all and seek both experience a decrease in S/N by up to 1/ 2 when the boxcar and pulse are out of phase. seek peaks twice due to a 2-bit smoothing step performed prior to downsampling. From Keane & Petroff (2015) root 2 problem can be avoided if, instead of down-sampling, the data are convolved with a sliding boxcar of width W and the original temporal resolution is retained. Both destroy and heimdall make use of a sliding boxcar search and consistently recover the maximum signal-to-noise ratio. Using values from a typical single pulse search at 1.4 GHz 1,749 DM trials optimally spaced between DMmin = 0 pc cm 3 and DMmax = 5,000 pc cm 3 to account for the expected amount of pulse broadening between two adjacent trials (Levin, 2012), and 13 width trials from 20 to 212 samples a single observation requires 22,737 separate searches. The large number of required operations is computationally expensive. By far the most time-consuming process in the search algorithm is the de-dispersion process, which takes approximately an order of magnitude more compute time than any other process including the matched filter searches and event detection (Barsdell, 2012). The de-dispersion speed constraint has been a serious impediment to faster search code in recent years making it difficult to achieve near real-time processing speeds (Magro et al., 2011; Barsdell et al., 2012). A recent solution to the de-dispersion speed problem was developed by Barsdell et al. (2012) who implemented the de-dispersion algorithm for computation on a graphics pro-

55 2.2. Detecting single pulses 33 cessing unit (GPU). Unlike a CPU which is designed to perform sequential operations on data, the GPU architecture is highly optimized to perform the same operation simultaneously on multiple data using large numbers of parallel processors. Historically GPUs were developed for gaming which requires high-speed rendering of images; however, astronomers now apply this parallelized approach to astronomical problems such as N-body code acceleration (Nitadori & Aarseth, 2012) and gravitational microlensing simulations (Vernardos & Fluke, 2013). The use of GPUs in the de-dispersion stage of single pulse data analysis has resulted in a processing speed nine times faster than what was previously possible on a CPU (Barsdell, 2012). The heimdall code written by Ben Barsdell and Andrew Jameson makes use of GPUs for data processing and is currently the fastest single pulse search software available. Due to its speed and optimized S/N search advantages over other software, heimdall is the primary code used for searches of Parkes filterbank data. Below we discuss how this software has been implemented to search for single pulses in generic Parkes survey data as well as how it has been modified and optimized for real-time searches The heimdall pipeline The heimdall search code takes in a subset, or gulp, ofdatathatspanashorttime interval and processes it in its entirety over the DM width parameter space in search of single pulses. The entire observation is processed gulp by gulp with overlaps between gulps to compensate for possible dispersed pulses at gulp edges. The results are output to a candidates file as an ASCII list of detected peaks with information on each candidate such as S/N, width, DM, and time into the observation. A single pulse will be detected at a range of DMs close to the true value and these events must be merged into one before returning the DM that gives the maximum S/N. Thus thousands of events can be identified prior to merging, which will go on to produce only a handful of independent candidates. After the individual beam data have been fully processed the candidate lists are combined to create a full candidate list for the observation along with information for each candidate such as the number of beams in which it was detected. Candidates detected simultaneously in multiple beams can be eliminated to reduce radio frequency interference (RFI) in the near-field. Candidate pulses can be visualized in a number of ways. The most direct way of validating a candidate is to look at a time-frequency plot of intensity for the source, as shown in Figure 1.3, to judge the bandwidth of the candidate and whether it truly appears to be a dispersed, broadband pulse. However, a single pointing can return hundreds of

56 34 Chapter 2. Technological Introduction false candidates and the quickest way to eliminate these is to look at an overview plot for the pointing (Figure 2.3). Both methods used together are useful for finding promising candidates in survey pointings. The pipeline for reduction of filterbank survey data is outlined in Figure 2.4 and roughly consists of processing individual beams of a pointing, merging the results from all beams and rejecting coincident detections that appear in multiple beams. Various cuts can then be applied to the data to search for candidates of interest for further study. Candidates with low DM (DM apple 2), and candidates that appear in fewer than 3 adjacent DM trials are rejected immediately as these are typically caused by zero-dm RFI or noise in the data. The candidates remaining after these initial cuts then form the basis of our searches for rotating radio transients (RRATs) and FRBs within the survey. The single pulse searches described in this thesis are characterized by the following search parameters: 2pccm 3 apple DM < 5000 pc cm samples apple W apple 2 12 samples N beams;adj apple 4 (2.5) where the first two lines represent the DM and width ranges over which we search and N beams;adj is the number of adjacent beams in which the signal is present. A signal can appear in up to 4 adjacent beams, beyond which it is deemed to be RFI. If the signal is coincident in multiple beams that are not adjacent it may pass this criterion and later be classified as RFI in the coincidence check. These are the basic criteria used to create the candidates files for all single pulses in a single survey pointing. Further refinements or cuts can be made on these candidates to select a sub-sample of interest, as described in Chapter Real-time searches Real-time searches for single pulses are performed on-site at Parkes as the data are being taken. Instead of being sent to Swinburne, each beam of a pointing is processed on a separate GPU within the HI Pulsar signal processor (HIPSR) server system that hosts the BPSR backend. The processing time for a gulp of data varies depending on the gulp size. However, the performance of heimdall is optimized to make efficient use of GPU memory using a gulp size of 16.8 seconds which can be fully processed, on average, in under 10 seconds; these speeds make real-time searches possible for the first time. To maintain

57 2.2. Detecting single pulses 35 Figure 2.3 A sample overview plot of candidates generated in a heimdall search of a single Parkes pointing. The top left plot gives a histogram of candidates over the DM range searched, one for each of the 13 beams. The top right scatter plot gives the DM of each candidate and its S/N. In the bottom panel showing time and candidate DMs, the color and size of the filled circles represent the pulse width and S/N, respectively, with the primary detection beam labeled in the circle. All other symbols represent spurious candidates cut based on low DM (cyan, bottom of plot), or appearance in too few DM trials and coincidence in multiple beams (orange). A single bright pulse in beam 3 of width 16 ms and DM 940 pc cm 3 is visible at t 200 sinthedm-timeplot,andin the top right corner of the DM-S/N plot; this is FRB published by Thornton et al. (2013).

58 36 Chapter 2. Technological Introduction Figure 2.4 The processing pipeline for filterbank data from Parkes using the heimdall single pulse search software. Operations performed on the FPGAs are shown in red, CPU operations are shown in blue, and GPU operations are shown in green. For offline processing the complete filterbank files for a pointing are transferred to the Swinburne gstar supercomputing facility and processed on the high performance computing nodes. For realtime processing the gulps of data are taken from the ring buffer and searched on HIPSR. Each beam of filterbank data is processed separately with heimdall and the candidates are cross-checked and concatenated into a single file. A variety of search thresholds can be applied to the full candidates list depending on the sources of interest.

59 2.2. Detecting single pulses 37 consistent processing speed, certain quick cuts must be made to ensure that no backlog of incoming data occurs when large numbers of false candidates are generated by the presence of strong RFI in the data. Therefore, an additional cut is made in the real-time heimdall that is not implemented in the off-line processing described in Section 2.2.1: if the number of ungrouped candidates identified in the gulp exceeds 100,000 the processing of the gulp stops and the processing moves on to the next gulp. The results of a single gulp from all 13 beams are run through the coincidence pipeline where strong cuts are made with the explicit goal to search for FRBs. These cuts are much more restrictive than what is applied off-line, but the aim of the search is to identify pulses which have strong FRB-like characteristics in the data as quickly as possible. Namely, pulses that have DM 1.5 DM Galaxy S/N 10 N beams apple 4 W apple ms N events (t obs 2s! t obs +2s)apple 5 (2.6) where DM Galaxy is the DM contribution predicted by the NE2001 model (Cordes & Lazio, 2002), the width cut specifically focuses on events of short duration, and the final line of Equation 2.6 stipulates that there cannot be more than five other candidates in the pointing within a 4-second window centered around the candidate of interest. All archival FRBs found to date pass the thresholds set in this equation, although less stringent cuts are made in the off-line processing to ensure no potential atypical FRBs are ignored (see Chapter 4 for details) and to allow RRATs through the first detection stage. The power of the real-time search system is that these operations are all performed while the 8-bit data and the full polarization information are still available. This is made possible by the use of a ring buffer incorporated into the BPSR system which holds 120 seconds of 8-bit data from all 13 beams while the real-time processing is underway. As long as the system keeps up with the incoming data any FRB in the pointing should be found before the 8-bit data are deleted from the buffer, making it possible to preserve the full polarization information for a FRB. Within the real-time heimdall pipeline, when a candidate matching all the criteria in Equation 2.6 is detected, the 8-bit data for the candidate are saved in the time window

60 38 Chapter 2. Technological Introduction t 0 t apple t apple t t (2.7) where t is the time into the observation, t 0 is the time of the candidate event at the highest frequency in the observing band, and t is total dispersive delay between the highest and lowest frequencies in the observing band (given in Equation 1.2), essentially preserving the candidate and a buffer of data of length t on either side of the event. The pipeline was initially tested in early 2014 by eliminating the DM cutoff condition from Equation 2.6 and observing bright pulses from RRATs, which successfully triggered the real-time data acquisition under the anticipated conditions. The system was put into use as part of normal operations mode for BPSR in March The first real-time FRB discovery made by this system is presented in this thesis (see Chapter 7) and the system has primarily been used in transient surveys such as the High Time Resolution Universe survey (HTRU, real-time visualization only; Keith et al., 2010) and the ongoing Survey for Pulsars and Extragalactic Radio Bursts (SUPERB; Keane et al, in prep.). 2.3 The High Time Resolution Universe survey The High Time Resolution Universe survey (hereafter, HTRU) began in 2008 as an ambitious effort to survey the entire radio sky with sub-ms time resolution to search for pulsars, RRATs, and other radio transients. The survey is conducted jointly by the Parkes radio telescope in the South (Keith et al., 2010), and the Efflesberg radio telescope in the North (Barr et al., 2013) both observing at a center frequency of 1.4 GHz. The HTRU survey consists of three regions or sub-surveys; these three elements of the HTRU South survey are presented in Table 2.2. Note that although the PFB has 1,024 frequency channels the usable N channels = 870. This is due to the presence of persistent strong RFI from transmitting satellites at the highest frequencies in the band, which reduce the available bandwidth that is useful in searches from 400 MHz to approximately 340 MHz. The Southern survey ended in February 2014 with 100% of the planned low and intermediate latitude pointings and 98% of the high latitude survey completed over 6.5 years, from 2008 to The pointing durations for each component are designed for different science goals in the different latitude regimes. The long pointings at low Galactic latitudes were designed to detect new pulsars too weak for detection in previous surveys. At intermediate latitudes the survey aim was to cover a large area of sky quickly to search for pulsars slightly out of the plane that may be useful for timing projects as well as to search for any new RRATs. The high latitude portion of the survey, which covers by far

61 2.3. The High Time Resolution Universe survey 39 Table 2.2 The parameters of the three components of the HTRU South survey conducted at the Parkes telescope. The survey bounds are listed in terms of Galactic longitude and latitude (`, b) and declination ( ). Table adapted from Keith et al. (2010). Survey High Intermediate Low < <` 80 <` Survey Bounds `<30 `<30 b < 15 b < 3.5 Pointing duration (s) N beams, completed samp (µs) usable (MHz) channel (khz) N channels Pointing length (samples) Data/beam (GB) Data/total (TB) the largest area of sky, was designed primarily to look for transient phenomena such as FRBs. Few new pulsars were expected in the high latitude survey. The intermediate latitude component was completed first with all pointings taken between 2008 and the end of The low latitude survey completion was the second priority and the last months of the survey were entirely focused on the remaining high latitude pointings. Initial discoveries from the HTRU South survey have been incredibly fruitful. Highlights include the discovery and study of several new pulsars (Bates et al., 2011, 2012; Levin et al., 2013), the discovery of numerous millisecond pulsars (Keith et al., 2012; Burgay et al., 2013; Ng et al., 2014), studies of single pulse properties of pulsars (Burke-Spolaor et al., 2012), the discovery of new RRATs (Burke-Spolaor et al., 2011b), the discovery of a radio-loud magnetar (Levin et al., 2012), and the discovery of a millisecond pulsar with an ultra-compact planetary companion (Bailes et al., 2011). The citations above report on the processing and analysis of only a subset of the HTRU South data and further discoveries are expected. One of the most intriguing results from the high latitude survey was the discovery of four new fast radio bursts (Thornton et al., 2013) firmly establishing the FRB population and giving rise to a new wave of interest in the progenitors and sources of FRBs. These four sources were discovered in a single pulse search of only 24% of the full high latitude survey performed in late 2012, before the survey was complete. The numbers hinted at an enormous all-sky FRB rate ( 10 4 sky 1 day 1 ) making the detection of more bursts in the full survey extremely likely. Ultimately this prompted development of the real-

62 40 Chapter 2. Technological Introduction time system currently in use at Parkes. Even before the real-time triggering mode was implemented, the data were visualized with heimdall overview plots such as the one in Figure 2.3 as observations were underway, effectively allowing for visual inspection in realtime beginning in May Three new FRBs were discovered in this observing mode in June and July 2013 in near-real-time; however, no polarization data were available at the time (Chapter 6). The HTRU North survey is not yet complete, and additional FRB discoveries are expected in coming years as part of the ongoing survey in the Northern Hemisphere. Analysis of the data from the HTRU South survey is still underway and work remains to be done on all components of the search: RRAT and pulsar searches in the high latitude survey; RRAT searches and improved acceleration searches in the intermediate latitude survey; and completion of ongoing RRAT, pulsar, and FRB searches of the full low latitude survey. Future searches are expected to yield additional interesting pulsars, RRATs, and FRBs. Searches of the intermediate latitude survey for FRBs and perytons and the high latitude survey for FRBs are presented in Chapters 4, 5, and 6, respectively.

63 3 Dispersion measure variations in a sample of 168 pulsars In this chapter we present a study of a large population of young pulsars over a 6 year time period to search for variations in pulsar dispersion measure. Multi-year variations in DM can be used to probe intermediate scales of turbulence in the interstellar medium, a region inaccessible via other measurements. We find 5- variations over the span of the observations for only 4 pulsars in the sample, most of which is attributable to dense material local to the pulsar. These observations can be used to place limits on DM variations expected for pulsars and other radio sources at high DM. 3.1 Introduction The emission from pulsars experiences a time delay as it passes through the interstellar medium (ISM) due to the dispersive effects of its plasma component. The group delay of this signal t g ( ) depends on the observation frequency and the electron density along the line of sight as t g ( ) = h R i d 0 n ed` K 2 (3.1) where K is the dispersion constant with a value K MHz 2 pc cm 3 s 1, is the observing frequency in GHz, n e is electron density and d is the distance of the pulsar from the observer. The expression in brackets is refered to as the dispersion measure (DM) and describes the amount of ionised interstellar material between the observer and the pulsar (Chapter 1). Dispersive effects are proportional to 2 and can be determined experimentally by 41

64 42 Chapter 3. Dispersion measure variations of young pulsars measuring delays in pulse arrival times for a pulsar across the bandwidth of an observation at a single frequency or fitting over a range of frequencies (Keith et al., 2013 and references therein). When a pulsar is first discovered, the spin period and DM are directly obtained as part of the search process. In most cases, a pulsar s DM is treated as a constant but several long-term studies of DM have revealed temporal variations on timescales of months to years (Hamilton et al., 1985; Phillips & Wolszczan, 1991; You et al., 2007; Keith et al., 2013). Variations in dispersion have been used to study turbulent structure in the free electron density of the ISM. The spectral energy density scale of interstellar turbulence is thought to show power law statistics for interstellar material between large (10 18 m) and small (10 6 m) spatial scales such that P 3N (q) C 2 Nq (3.2) represents the power spectrum of the electron density P 3N with a spectral index and a structure coefficient CN 2. It is estimated in Armstrong et al. (1995) that this spectrum is consistent with a Kolmogorov power law described by = 11/3. However, inhomogeneities in the form of highly anisotropic filaments are believed to exist in the ISM (Brisken et al., 2010) and may be responsible for so-called extreme scattering events (Fiedler et al., 1987; Romani et al., 1987). Turbulent interstellar material is probed on various scales by different types of observations, from rotation measure variations at the largest scales to weak diffractive interstellar scattering at the smallest. Fluctuations in pulsar DMs provide the capability to probe the ISM in the middle of this spatial range between and m, where other techniques are incapable of detecting variations. Thus, DM variation measurements bridge a crucial gap in the ISM turbulence spectrum. Significant DM variations have previously been observed in studies of different classes of objects. Varying DM along the line of sight to the Vela pulsar was first noted in Hamilton et al. (1985); DM was observed to decrease over the length of their study. They attributed these changes to a dense, magnetised filament within the Vela supernova remnant (SNR) passing out of the line of sight over the 15 years of data (Hamilton et al., 1985). Similarly, DM to the Crab pulsar has been observed to increase by 0.02 pc cm 3 yr 1 over 68 epochs between 1982 and 1988, attributed to variations within the turbulent environment of the local Crab SNR (Lyne et al., 1988). A study of seven pulsars over two years in Phillips & Wolszczan (1991) detected variations caused by interstellar turbulence with a spectral index

65 3.1. Introduction 43 of = 11/3, and DM variations have also been observed in high-precision observations of millisecond pulsars (e.g. You et al., 2007). These variations are generally consistent with levels of turbulence in the ionised ISM, though there is growing evidence that the exponent of the power-law noise process is steeper than expected from Kolmogorov turbulence for some lines of sight (Keith et al., 2013). Changes in DM over time provide a direct method of probing turbulence in the interstellar medium (Rickett, 1977). These changes relate to the DM structure function D DM as ddm dt = (D DM) 1/2 (3.3) where ddm/dt is the absolute rate of change of the DM over time in pc cm 3 yr 1 and is the span of the observations in years (Backer et al., 1993). The structure function, in turn, is related to the diffractive timescale, d, of the pulsar by You et al. (2007) D DM = K 2 2 (s). (3.4) K has the same value as in Equation 3.1, (s) is the time span of the observations in seconds, and = 2, where = 11/3 is taken to be the power-law exponent of a Kolmogorov spectrum (Armstrong et al., 1995). seconds at the observing frequency. d Here d is the diffractive timescale in In this chapter we examine the DMs of more than 160 young, highly energtic pulsars monitored regularly over six years at the Parkes radio telescope as part of a radio counterpart study to one conducted with the Fermi gamma-ray telescope (Smith et al., 2008). The pulsars in our sample are distributed at a range of distances within the Galactic plane with DMs between 2 pc cm 3 and almost 1000 pc cm 3. The majority are at low Galactic latitudes and probe a diverse range of sight lines through the Galactic ISM. Our sample is additionally promising for DM variation studies as young pulsars are also more likely to be associated with supernova remnants remaining from their birth, providing the possibility of yet more ionised, turbulent local structure. Many previous studies mentioned here focus on millisecond pulsars, most with DM < 100 pc cm 3. Canonical pulsars are detected up to much higher DMs and provide a complementary sample to the MSPs, allowing us to study turbulence over larger lines of sight. In Section 3.2 we describe our observations; in Section 3.3 we describe our data analysis procedures and our statistic for measuring DM variations in our pulsars. In Section 3.4

66 44 Chapter 3. Dispersion measure variations of young pulsars we outline our findings, with special attention paid to four pulsars of interest: PSRs J , J , J , and J , and we set upper limits for all others in Section 3.5; we conclude in Section Observations Since early 2007, regular observations of a large sample of pulsars have been carried out with the 64-metre Parkes radio telescope in support of the Fermi gamma-ray mission. A total of 156 pulsars were drawn from the list of highly energetic pulsars in Smith et al. (2008) supplemented by a small number of other interesting southern sources. The initial description of the observational setup and early timing results from the Parkes dataset are described in Weltevrede et al. (2010b). For this work we used data taken using the Parkes telescope between February 2007 and October Observations were carried out on an approximately monthly basis with all 168 pulsars observed over a 24 hour period at a centre frequency near 1.4 GHz. At 6 month intervals, additional observations were obtained simultaneously at 3.1 and 0.7 GHz on the following day. During a single observation each pulsar was observed long enough to obtain a signal to noise ratio greater than 5, typically only a few minutes. Observations at 1.4 GHz with 256 MHz of bandwidth were taken using the centre beam of the Parkes multibeam receiver (Staveley-Smith et al., 1996). Observations at 3.1 and 0.7 GHz were done simultaneously using the 10/50 cm receiver installed at Parkes (Granet et al., 2005) and had 1,024 MHz and 64 MHz of bandwidth, respectively (Weltevrede et al., 2010b). The voltage signals from the orthogonal, linearly-polarised receptors were digitised and converted to a filterbank consisting of 1,024 frequency channels then folded using 1,024 phase bins across the pulse period of the pulsar. Incoming data were folded at the period of the pulsar in 30-second sub-integrations and then written to disk. Regular calibration was performed by sending an artificial calibration signal into the feed at a 45 angle from both linear probes to determine both their relative gain and the phase offset. The final calibrated data were saved to disk and used to create an average pulse profile over the full span of the observation. 3.3 Analysis Initial data reduction was performed after each observation using the psrchive data analysis package (Hotan et al., 2004). An integrated pulse profile for each pulsar observation

67 3.3. Analysis 45 was produced after excising time and frequency channels with significant radio frequency interference. The remaining channels were calibrated to produce a final pulse profile at each observing frequency which was compared with a standard profile for the pulsar, created by summing profiles from all previous observations (Weltevrede & Johnston, 2008). The time of arrival (TOA) for the integrated profile was converted to the solar system barycentre using the DE405 model (Standish, 1998) and compared with that of the timing model prediction using the tempo2 software package (Hobbs et al., 2006). The time difference between the observed TOA and the timing model gave a residual for each observation. Once several epochs of residuals were available, it became possible to remove common parameters such as effects from the pulsar spin frequency and spin frequency derivative through fits within tempo2. These fits removed linear and quadratic terms from the residuals, respectively. At this stage it was possible to fit for the DM contribution in the refined residuals. Previous studies of DM from pulsar timing residuals have identified problems of obtaining reliable values and accurately correcting for DM effects in the timing solution. You et al. (2007) performed a linear fit by directly comparing the arrival times at two different frequencies. Since all epochs in their sample consisted of observations at 3 distinct centre frequencies they determined the best two with which to perform calculations on a case-bycase basis. This method was updated in Keith et al. (2013) by using all three observing frequencies simultaneously to determine the DM for each epoch. Keith et al. also incorporated a smoothing function into the tempo2 fitting algorithm that was previously applied after fitting. We created two DM datasets using the algorithm described in Keith et al. (2013). Each pulsar has been observed at approximately 80 epochs at 1.4 GHz but at only 10 epochs at 0.7 and 3.1 GHz. Thus two separate time series were created, one for DM measured across the 20 cm band only, and one measured across all three frequencies, where available. In some cases the number of useful multi-frequency DM measurements is smaller than the number of epochs at which observations were taken because scattering effects preclude detection at 0.7 GHz. To calculate DM variations over the span of the dataset, we performed a weighted least-squares fit to measure the slope in DM over time. The result of this fitting procedure was a best-fit slope, ddm/dt, taken to be the variation in DM. Separate fits were done for 20 cm and multi-frequency DM measurements resulting in two separate ddm/dt values for each pulsar. Multi-frequency fits of ddm/dt for pulsars with only one or two usable multi-frequency epochs were not considered as the linear fit had no associated error.

68 46 Chapter 3. Dispersion measure variations of young pulsars Table 3.1 Pulsars with DM variations over 6 years above 3 levels. Pulsars with detections above 5 levels are listed in bold. Slopes for the multi-frequency (mf) and 20 cm observations with errors in the last digit are in units of pc cm 3 yr 1. Name DM ddm/dt mf ddm/dt 20cm J (1) (9) J (4) 0.030(1) J (2) 0.022(1) J (2) 0.18(1) J (5) 0.27(3) J (4) 0.52(5) J (3) 0.4(1) J (9) 0.19(6) J (2) 0.016(3) J (2) 0.17(4) J (4) 0.13(3) We note that the weighted linear fit is not a perfect tool for the study of small-scale variations, and we may expect variations on timescales shorter than the many-year span of our dataset that do not fit this trend. Overarching linear changes in DM would be expected to arise in cases where a single large structure moves across the line of sight over the span of observations. Additionally, the steep power law of Equation 3.2 implies that the most power will be at the largest timescale, thus the largest DM variations. A linear fit may also encompass spatial density gradients but provides a good first order detection statistic. 3.4 Results - Detections DM variations were detected in eleven pulsars from our sample over the 6 years of observation. All are embedded in the Galactic plane with dispersion measures ranging from 67.9 to 599 pc cm 3. Only four pulsars in our sample, PSRs J , J , J , and J , had variations deemed highly significant. These pulsars wer identified based on the fact that they all had values of ddm/dt with agreement in sign between 20 cm and multi-frequency fits with an error in each fit apple 35%. Variations were labeled as highly significant detections if errors were apple 20% in both fits. Fits for all other pulsars in our sample failed to meet one or more of these criteria and the weighted linear fit was used to produce an upper limit on detectable variations. Marginal detections, pulsars with detections between 3 and 5, are largely consistent with variations predicted from an ISM dominated by Kolmogorov turbulence.

69 3.4. Results - Detections 47 Figure 3.1 The DM of PSR J over 2000 days for 18 epochs of multi-frequency measurements (circles) and 97 epochs of measurements across the band centred at 20 cm (squares) with weighted linear fits represented by the dashed and dot-dashed lines, respectively. The general trend is of increasing DM over the dataset with a notable reversal between MJDs and Table 3.1 lists the pulsars with significant measurements of DM variations. significant pulsars will be discussed individually below. Highly PSR J PSR J (B ), located in the Vela supernova remnant, lies within the Gum Nebula (Large et al., 1968). It is one of the brightest pulsars in the sky, with a flux density at 1400 MHz of 1100 mjy (Backer & Fisher, 1974) and characteristic age c of 11 kyr. It is located at a distance from the Sun of approximately 300 pc (Dodson et al., 2003) at Galactic longitude and latitude (`, b) = (263.5, 2.79 ). The pulsar has a very large DM for its distance and using CN 2 as a measure of turbulence (Cordes, 1986), its value is the highest measured of any pulsar (Johnston et al., 1998). The scintillation velocity at high observing frequencies has been measured by Johnston et al. (1998). Corresponding to a value of d 10 s at 1.4 GHz. We therefore expect DM variations of order 0.01 pc cm 3 yr 1 based on Equation 3.3. Previous studies of changing DM along the line of sight to Vela (Hamilton et al., 1985) showed DM to be decreasing over 5 epochs between the years 1970 and 1985 at a rate of pc cm 3 yr 1, a factor of 4 greater than expected from turbulence. Hamilton et al. (1985) interpreted their measured

70 48 Chapter 3. Dispersion measure variations of young pulsars decrease in DM as the movement of a magnetised filament out of the line of sight within the SNR, meaning that changes in DM were due to the local environment of the pulsar rather than the turbulence in the greater ISM. As shown in Figure 3.1, single frequency DM measurements over the entire six years of our dataset show DM increasing at a rate of (9) pc cm 3 yr 1.Similarly,dDM/dt = 0.005(1) pc cm 3 yr 1 using multi-frequency fits. These variations are significantly smaller than those measured by Hamilton et al. (1985) but are more or less consistent with expected values given the measured scintillation parameters. The dramatic change in ddm/dt is highlighted in Figure 3.2 where we show the Hamilton et al. data over plotted with data from this study and analogue filterbank system archives at Parkes. In order to reduce the noise due to measurement uncertainty we plot weighted averages in 100-day bins. We caution that there may be a systematic offset between the DMs derived in the Hamilton et al. data and those derived from our work due to known intrinsic frequency evolution of the Vela profile (Keith et al., 2011). We interpret the dramatic change in ddm/dt to be evidence that the filament responsible for change seen by Hamilton et al. moved completely out of our line of sight some time near MJD We believe that the currently observable DM variations can be explained solely by the turbulent ISM. Although the overall trend in ddm/dt in the recent data is positive, variations are visible on shorter timescales within the span of our observations, most notably where DM appears to decrease between MJD and This is consistent with turbulence in the ISM. Contributions from the surrounding Gum Nebula are most likely minimal, however, as there are no detectable variations in other pulsars from the Gum in our sample PSRsJ , J , J , and J PSR J The pulsar PSR J (B ) has a spin period of 106 ms, and a DM derived distance of 6.7 kpc placing it well within the Galactic plane, at (`, b) = (270.27, 1.02 ) (D Amico et al., 1988). Gaensler et al. (1998) discovered a bow-shock in the immediate surroundings of the pulsar suggesting that it is travelling through the turbulent medium of an associated pulsar wind nebula (PWN) with velocity 60 km s 1 at a position angle of 315 (north through east). Their derived velocity is consistent with the scintillation measurements of Johnston et al. (1998), who measured the diffractive timescale to be 4770 s at 1.5 GHz. This yields expected DM variations of pc cm 3 yr 1. No long term studies of DM along the line of sight to PSR J exist in the

71 3.4. Results - Detections DM (cm -3 pc) Figure 3.2 DM measurements of PSR J since 1969 (MJD 40500). Square markers indicate single values taken from Hamilton et al. (1985). Other markers are weighted averages of the DM measured in 100 day bins of Parkes observations. Values before MJD are taken from archival Parkes data recorded using an analogue filterbank system. The lines indicate extrapolation of the trends from the Hamilton et al. dataset and from this work. literature, however previously published DM estimates for this pulsar do exist as far back as its discovery in 1988, when its DM was measured to be 192 ± 12 pc cm 3 (D Amico et al., 1988). At the beginning of the Fermi dataset in 2007 DM was measured to be approximately pc cm 3, but had dropped by 0.12 pc cm 3 by the final epoch from Unfortunately the large uncertainty in the 1988 data and lack of data in the intervening years prevent us from drawing any conclusions as to the long term evolution of the DM. The variation in DM along the line of sight to PSR J is one of the largest measured of any pulsar in our sample, with a best-fit linear slope of ddm/dt = 0.030(1) pc cm 3 yr 1 for the 20 cm DM measurements and ddm/dt = 0.038(4) pc cm 3 yr 1 over 12 multi-frequency epochs shown in Figure 3.3. Similar to PSR J , fluctuations on shorter timescales are present in the 20 cm data, and are visible even in the more sparsely sampled multi-frequency dataset. The DM variations along the line of sight are more than two orders of magnitude greater than expected from models. The high variations, then, seem likely to be caused by the immediate surroundings of the pulsar. PSR J has an unusual PWN and appears to be moving slowly through a highly dense (n e > 2 cm 3 ), and likely turbulent, medium (Gaensler et al., 1998). Thus for a region on the order of a parsec in size, the MJD

72 50 Chapter 3. Dispersion measure variations of young pulsars Figure 3.3 The DM of PSR J over 12 multi-frequency epochs (circles) and 77 epochs measured across only the 20 cm band (squares) with weighted linear fits represented by the dashed and dot-dashed lines, respectively. PWN contribution to total DM would be small but the nebula s highly turbulent nature would be capable of much larger fractional contributions to ddm/dt as the pulsar moved through it. DM variations can then be attributed to a small percentage variation from within the local PWN PSR J PSR J (B ) is a young pulsar with a period of 189 ms and a characteristic age c = yr (Manchester et al., 1978). It lies in the Galactic plane close to the centre of the Galaxy with Galactic coordinates ` = and b = 3.11 at a DM-derived distance of approximately 5.2 kpc (Cordes & Lazio, 2002). Previous studies of PSR J were unable to make significant measurements of pulsar velocity or DM variations (Hobbs et al., 2004; Zou et al., 2005), thus neither significant velocity nor diffractive timescale measurements exist for this pulsar in the literature. Assuming a velocity of 300 km s 1 we expect a diffractive timescale of order d =6s, which in turn corresponds to DM variations of magnitude 0.02 pc cm 3 yr 1 using the Cordes & Lazio (2002) model. The general trend in our data is a decrease in DM over the six years of observations seen in Figure 3.4, although the best-fit rate of this variation differs between the 20 cm and the multi-frequency data with ddm/dt 20cm = 0.022(1) pc cm 3 yr 1 and ddm/dt mf = 0.011(2) pc cm 3 yr 1, respectively. These gradients differ by a factor of 2, with lower

73 3.4. Results - Detections 51 Figure 3.4 DM measurements for PSR J over 11 epochs of multi-frequency data (circles) and 75 epochs measured across the 20 cm band alone (squares) with weighted linear fits represented by the dashed and dot-dashed lines, respectively. error in the fit at 20 cm. The good fit to the data may arise because the trend over 2000 days is not a strictly linear one; additional fluctuations are visible on shorter timescales possibly due to turbulent structure on small scales passing through the line of sight. In the case of PSR J the DM variations we observe are consistent with values predicted for a turbulent ISM in this direction for our assumed velocity and DM-determined distance. This pulsar is not well-studied like PSRs J and J , but there is no evidence for the presence of an associated SNR or PWN in the local neighbourhood. Therefore we attribute the variations in the DM towards this pulsar to the turbulent ISM alone PSR J PSR J (B ) has a period of 85 ms and an approximate characteristic age of 150 kyr (Clifton & Lyne, 1986). At the time of its discovery it was identified as an isolated pulsar close to the supernova remnant W41. It has been argued that the pulsar s high velocity away from SNR W41 indicates a past connection and that PSR J originated within the shell-like SNR (Hobbs et al., 2005). More recently, X-ray studies of the region using the XMM-Newton satellite discovered an X-ray pulsar wind nebula surrounding this pulsar in the form of a bow shock nebula (Esposito et al., 2011). PSR J is located towards the Galactic centre (`, b) =(23.39, 0.06 )ata DM-derived distance of 5.6 kpc (Cordes & Lazio, 2002). This pulsar has been observed

74 52 Chapter 3. Dispersion measure variations of young pulsars Figure 3.5 The DM of PSR J over the 2000 days of observations as measured over 11 epochs of multi-frequency data (circles) and 67 epochs measured across the 20 cm band alone (squares) with weighted linear fits represented by the dashed and dot-dashed lines, respectively. The general trend is that of decreasing DM with a sign reversal between MJD and to move with a transverse velocity of approximately 740 km s 1, more than twice the rms velocity of non-millisecond pulsars (Nicastro & Johnston, 1995; Hobbs et al., 2005). The high transverse velocity and distance correspond to a scattering timescale at 1400 MHz of 5 s and expected DM variations of 0.02 pc cm 3 yr 1. From our observations we find a general trend of decreasing DM along the line of sight to J with ddm/dt mf = 0.13(2) and ddm/dt 20cm = 0.18(1) in units of pc cm 3 yr 1, seen in Figure 3.5, for multi-frequency and 20 cm DMs, respectively. These variations are larger than those of any other pulsar in our sample by an order of magnitude. However, these fits include a change in sign of ddm/dt between MJD and MJD seen in both sets of DM measurements, most likely attributable to general turbulence; a piecewise fit to these data would yield an even larger value for ddm/dt over the regions of decreasing DM. PSR J also has the largest DM of any pulsar in which variations were detected. These extreme DM variations may seem more reasonable in light of the recent discovery of the pulsar s X-ray PWN. The turbulent ISM along the line of sight to PSR J would be expected to contribute only about 10% of the observed variations and it is possible that observed behaviour is due entirely to the energetic bow shock nebula through which the pulsar is moving, including the brief passage of a dense filament through the line of sight corresponding to the temporary increase in DM midway through the dataset.

75 3.5. Results - Upper limits ddm/dt (cm -3 pc yr -1 ) DM (cm -3 pc) Figure 3.6 Upper limits on ddm/dt for pulsars in which no significant DM variations were detected. Overlayed lines display predicted variations detectable at a range of DMs for a pulsar at ` = 330, b =0 with a velocity of 164 km s 1 (dashed), 338 km s 1 (dotted), and 511 km s 1 (dot-dashed), the median and 1 sigma velocities from the pulsar velocity distribution in Hobbs et al. (2005). 3.5 Results - Upper limits Upper limits on ddm/dt for each of the pulsars in the Fermi project with no significant DM variations are listed in Table 3.2 along with the DM that best fits our data. All but 36 of our measured DM values have smaller uncertainties than previous best estimates. In Figure 3.6 we plot our upper limits as a function of DM. We compared the 25 pulsars common to our observations and the Hobbs et al. (2004) study and found our upper limits were consistent with but less constraining than theirs. Although our limits on ddm/dt may also contain contributions from spatial density gradients our data are not sufficiently sensitive to disentangle this contribution from that of variations due to turbulence. Because we are only setting upper limits on total variations, we do not attempt to explicitly differentiate between the two. Ideally we want to compare our upper limits with theoretical predictions for ddm/dt based on Kolmogorov turbulence. To do this we would need to measure the diffractive timescale d and then apply Equations 3.3 and 3.4. Unfortunately, the high DMs of most of our sample preclude direct measurements of d as, in the majority of cases, they will be significantly smaller than our integration time. For any given line of sight we can however, estimate d using

76 54 Chapter 3. Dispersion measure variations of young pulsars the Cordes & Lazio (2002) model of the Galaxy, which estimates scintillation along the line of sight consistent with a Kolmogorov spectrum of turbulence. For illustrative purposes in Figure 3.6 we choose a representative line of sight at (`, b) =(330, 0 )andusethe Cordes & Lazio (2002) model to step through DM and derive the scintillation bandwidth,. Conversion of to d is obtained through (D ) 1/2 d = A V, (3.5) v where D is the distance to the pulsar in kpc, is the diffractive scintillation bandwidth in MHz at the observing frequency in GHz, v is the velocity of the pulsar in km s 1, and we adopt a value of A V = from previous studies (Nicastro et al., 2001). Figure 3.6 shows the curves obtained for three different velocities, v= 164, 338, and511 km s 1, the median and one sigma 2D velocities obtained using the distribution in Hobbs et al. (2005). We note that a number of upper limits lie below the theoretical value expected from the median two dimensional velocity of 338 km s 1 (Hobbs et al., 2005). This result is in contrast to the results for the millisecond pulsars for which ddm/dt is higher than expected. By using the probability distribution function for pulsar velocities given by Hobbs et al. (2005) we estimate that we should have had 12 pulsars in our sample with measurable values of ddm/dt, in good agreement with the 11 measured. However, this velocity distribution may not be entirely accurate because it models a pulsar s motion in 2-dimensional space. Detectable DM variations in some pulsars may be more realistically caused by irregularities along a single spatial axis in the interstellar turbulence (Brisken et al., 2010). If this is the case we only need concern ourselves with a one dimensional velocity as the pulsar moves through the ISM. The probability of detecting pulsars in our sample can be recalculated using a one dimensional Gaussian distribution. We find a much lower detection estimate of 6 pulsars, including our real detections. While this alternate model of ISM turbulence may be the cause of variations along some of our lines of sight, we expect this effect only at low DM as the effects of multiple irregularities would cancel out over large distances. We also note that our results appear to be at odds with Bhat et al. (2004) who conclude that NE2001 underpredicts scattering, particularly at high DM. However, Bhat et al. (2004) compare pulse-broadening times estimated from the Cordes & Lazio (2002) model and their own CLEAN-based deconvolution algorithm, which are directly sensitive to an inner scale. Measurements of DM variations are not sensitive to the ISM inner scale which may explain the difference between the findings of these studies.

77 3.5. Results - Upper limits 55 Table 3.2 All pulsars observed for the Fermi project are listed alongside DM fits from our data with error in the last digit, and an upper limit on ddm/dt in pc cm 3 yr 1. DM values with smaller uncertainties than previous publications are marked with an asterisk (*). Name DM ddm/dt lim PSR DM ddm/dt limit J (13) 0.18 J * 97.1(1) 0.08 J * 21.7(1) 0.05 J * 679(1) 0.7 J * 18.58(2) 0.2 J * (5) 0.07 J (5) J * 284.5(1) 0.1 J * 96.91(4) 0.02 J (1) 0.5 J * (7) 0.05 J * (3) J (1) 0.1 J * 537.8(4) 0.5 J * 13.94(9) 0.1 J * 961.0(3) J * 91.7(2) 0.1 J * 514.4(4) 0.4 J * (3) J * 670.6(4) 0.4 J * (1) 0.02 J * (6) 0.1 J * (2) 0.03 J * 260.5(2) 0.3 J (4) 0.3 J * (2) 0.02 J * 236.4(1) 0.02 J * (2) J (1) 0.08 J * 8.639(7) J * 199.3(2) 0.2 J * 142.1(1) 0.2 J (4) 0.06 J * (1) 0.02 J * (3) 0.04 J (3) 0.46 J * (5) 0.01 J * 194.0(4) 0.3 J * 98.49(8) J * 480.6(4) 0.2 J * 278.1(2) 0.1 J * 152.2(1) 0.1 J * (7) 0.08 J * 832(1) 0.7 J * (9) 0.1 J * 49.6(1) 0.1 J * 1040(1) 0.8 J * (3) 0.05 J * 441.5(4) 0.6 J * 604.6(1) 0.3 J (2) J * (3) 0.02 J * (2) 0.02 J * 426.1(1) 0.2 J * (4) J * 345.9(3) 0.3 J * 491.9(6) 0.5 J * (7) 0.07 J * 636.5(1) 0.07 J (4) 0.04 J * 29.69(1) 0.01 J * 491.6(7) 0.7 J * (1) 0.01 J * (4) J * (5) 0.1 J (1) 0.05 J * 704.8(2) 0.4 J * 195.2(6) 0.4 J (1) 0.1 J * (1) J * 520.4(4) 0.3 J * (9) 0.01 J * 243.2(1) 0.2 J * 582.4(1) 0.09 J * 790(1) 0.9 J * 574.2(5) 0.8 J * (4) J (5) 0.3 J * 433.0(6) 0.4 J (1) 0.09 J * 374(1) 1.00 J * 419.1(3) 0.5 J * (1) 0.02 J * 436.4(3) 0.2 J * 471.0(1) 0.5 J * 423.1(1) 0.2

78 56 Chapter 3. Dispersion measure variations of young pulsars Name DM ddm/dt limit PSR DM ddm/dt limit J * (6) 0.5 J (5) 0.03 J * 478.6(6) 0.3 J * 747(1) 1 J (3) 0.4 J * 724.6(2) 0.3 J * 392.3(3) 0.4 J * 768.5(6) 0.7 J * 331(1) 0.7 J (2) 0.1 J * 320.2(3) 0.2 J * (4) 0.05 J * 229.3(3) 0.2 J * 249(2) 0.8 J * 538.4(5) 0.2 J * 605.0(1) 0.1 J * 377.6(3) 0.2 J * (1) 0.01 J (2) 0.01 J (2) 0.02 J * (1) 0.05 J * 294.0(9) 0.8 J * 75.68(3) 0.02 J * 467.9(4) 0.5 J * 314.0(6) 0.4 J * 276.2(1) 0.3 J * (6) 0.04 J (2) 0.04 J * 99.49(3) 0.01 J * 319.5(6) 0.5 J * 254.4(1) 0.07 J * 459.3(3) 0.4 J * 718(4) 2 J * 617.2(4) 0.4 J * (4) 0.06 J * 276.6(4) 0.5 J * (4) J * 452.6(3) 0.6 J * (8) 0.05 J * 344.5(3) 0.7 J * 758(3) 1 J (3) 0.02 J * 488.1(4) 0.3 J * 284.5(3) 0.5 J (6) 1 J * 343.4(2) 0.1 J * (2) 0.03 J * 797.7(6) 0.7 J * 170.5(1) 0.1 J * 228.4(2) 0.2 J * (1) J * 826(2) 3 J (7) J * (4) 0.05 J * 329(1) 7 J * 230.8(2) 0.1 J (2) 0.02 J * (2) 0.01 J * 386(1) 0.5 J (1) 0.07 J (1) 0.7 J * 437.5(1) 0.03 J * (5) 0.07 J (2) 2

79 3.6. Conclusions 57 We find the two dimensional scattering modelled in NE2001 to agree well with the findings of our study, even in the high DM regime where that model becomes discrepant with others such as Bhat et al. (2004). 3.6 Conclusions We have analysed over five years of timing data for more than 160 young pulsars to search for any characteristic DM variations along several lines of sight. Only four pulsars in our sample PSRs J , J , J , and J showed highly significant changes in DM over the span of the study with seven other pulsars identified as marginal detections. One pulsar, PSR J , displayed detectable DM variations at levels predicted by an interstellar medium dominated by Kolomogorov turbulence with no contribution from dense filaments local to the pulsar. DM variations for the Vela pulsar, PSR J , were also consistent with a purely turbulent ISM, a dramatic change from measurements of large variations made 15 years ago attributed to the local SNR, indicating that perhaps the responsible filament is no longer moving through our line of sight. The other two detections, with variations well above those predicted by theory, are known to lie within turbulent local environments of supernova remnants or pulsar wind nebulae which make large contributions to observable turbulence along these particular lines of sight. No DM variations were observed along the lines of sight to most pulsars in our sample, but we were able to set upper limits on detectable variations. We compared these limits with DM variations predicted from models of Kolmogorov turbulence and found our limits to be within an order of magnitude of theoretical predictions. Comparisons with accepted two dimensional velocity distributions using NE2001 scattering models suggested our experiment should have detected DM variations to approximately 12 pulsars. Confining our models to one dimension to simulate scattering effects due to irregularities in the interstellar turbulence reduces this estimate to 6 pulsars. We find our results to be in good agreement with 2D scattering from the NE2001 model. The DM variations are a red process with a steep spectral exponent, therefore longer time baselines dramatically increase our sensitivity to DM variations. With more time the observation of young, high-dm pulsars will provide us with an excellent complement to the results obtained from millisecond pulsars at low DMs.

80

81 4 An Absence of Fast Radio Bursts at Intermediate Galactic Latitudes In this chapter we detail a search for fast radio bursts in the HTRU intermediate latitude survey which yielded no detections. A significant population of FRBs was expected in this survey given the large total time on sky and the high FRB rate implied by Thornton et al. (2013). Modeled Galactic effects such as scattering and pulse broadening cannot fully explain the discrepancy between the high and intermediate latitude surveys. Ultimately, a larger total population is needed to understand the latitude distribution of these sources. 4.1 Introduction Fast radio bursts (FRBs) are single, bright, highly dispersed radio pulses of millisecond duration. These bursts have fluences of Jy ms, and dispersion measures (DMs) well in excess of the expected Galactic contribution along the line of sight. Given the high flux density and high DM-derived distances, they could arise from high luminosity events at z. 1. The first burst of extragalactic origin (Lorimer et al., 2007) was discovered using the Parkes multibeam receiver (Staveley-Smith et al., 1996) in a pulsar survey of the Magellanic Clouds at Galactic latitude b = 41. Subsequently, the astrophysical origin of the Lorimer burst was called into question by the discovery of apparently dispersed sources in archival surveys called perytons (Burke-Spolaor et al., 2011a; Bagchi et al., 2012). Perytons exhibit dispersive properties that are similar, though not identical, to those of an astrophysical source; however, they are detected in all 13 beams of the Parkes 21-cm multibeam receiver, which is impossible for a distant point source. They have peculiar frequency structure, with all perytons showing bright nodules in specific regions of the 59

82 60 Chapter 4. An Absence of Fast Radio Bursts at Intermediate Latitudes observing band. One of the scenarios considered in recent work by Kulkarni et al. (2014) is a terrestrial origin for FRBs, where they are interpreted as being similar to peryton events, but occuring at greater distances (> 40km) from the telescope, mimicking a source at infinity. In this model the Lorimer burst, which was detected in four adjacent beams of the multibeam receiver, occupies a place between traditional FRB events and traditional peryton events and is believed to have occured at some distance from the detector close to the Fresnel scale for Parkes, 20 km. Loeb et al. (2014) have proposed that FRBs originate in the envelope of main-sequence flare stars within our Galaxy, after finding a flare star within the full width at half maximum of the detection beam of one FRB from the Thornton et al. (2013) sample. Recently, however, several authors have highlighted why such a model is physically untenable (Luan & Goldreich, 2014; Dennison, 2014). Several extragalactic progenitors (most at cosmological distances) have also been proposed. A list is presented in Section Each of these mechanisms is theorized to be capable of producing coherent radio emission of millisecond duration. At present, archival and on-going radio pulsar surveys are the most immediate and obvious places to begin searching for more FRBs. Thornton et al. (2013) estimate an FRB rate of R FRB sky 1 day 1 for bursts with fluences F 3Jy ms, based on 615 hours of observations. The HTRU intermediate latitude survey used an identical setup to Thornton et al. (2013) with 1,157 hours on-sky. Here we report on a search for FRBs in the HTRU intermediate latitude survey in a DM range from pc cm 3 which returned no new, highly-dispersed pulses. An introduction to the HTRU survey, the analysis tools, and results of the single pulse search are presented in Section 4.2. We present an in-depth discussion of our non-detection in Section Analysis and Results The High Time Resolution Universe (HTRU) Survey was designed as a comprehensive survey of the radio sky with 64-µs time resolution at 1.4 GHz to detect pulsars and other transient radio phenomena. Observations for HTRU are divided into three observing regimes at low, intermediate, and high Galactic latitudes. This study focuses on the intermediate latitude component of the survey: 540-s pointings in the range 120 <`<30 and b < 15 with the 13-beam Parkes 21-cm multibeam receiver, which has a 0.5 deg 2 field of view.

83 4.2. Analysis and Results 61 The survey data were searched for single pulses using techniques similar to those described in Burke-Spolaor et al. (2011b). The dedispersion and width filter matching were optimized for processing on a graphics processing unit (GPU) with the new software package heimdall. heimdall produces a list of candidates for each beam. All 13 beams in a single pointing are then run through a coincidence detector. Candidates that occur in more than 4 beams, fewer than 3 adjacent DM trials, have a S/N < 6 or DM < 1.5 pc cm 3 are rejected. With these cuts we are not sensitive to peryton-like events that occur in all 13 beams of the receiver. We will address the topic of perytons in the HTRU survey in Chapter 5. The candidates that remain after these cuts are concatenanted into a single candidate list for the entire pointing. Each pointing candidate file was searched for FRBs by looking for candidates matching the following criteria S/N > 10 W apple µs = 16.3 ms DM/DM Galaxy > 0.9 (4.1) where the width W corresponds to 2 n, where n is the trial 2 (0, 1, 2,...8). The DM threshold was intentionally set to include high-dm candidates from sources within the Galaxy to ensure sensitivity near the theoretical DM Galaxy boundary along these lines of sight. DM Galaxy used in this analysis is obtained from NE2001, a model of the Galactic electron density (Cordes & Lazio, 2002). All pointings were searched out to a DM max of 5000 pc cm 3. Extragalactic sources will have a value of DM/DM Galaxy & 1 and pulsars will have DM/DM Galaxy. 1, if the estimated DM Galaxy from NE2001 is correct. For pointings in the intermediate latitude survey the ratio of DM max to DM Galaxy ranges from 1.1 close to the Galactic centre to > 50 at higher latitudes; we were therefore sensitive to extragalactic sources along every line of sight observed during the survey. The spatial volume probed by this search is at least the same as that in the Thornton et al. (2013) analysis if not greater, depending on the maximum redshift to which FRBs are detectable. A total of 52 candidates were identified in the 1,157 hours of the intermediate latitude survey after applying these criteria. Of these, 29 were found to be zero-dm RFI, and 23 events were caused by narrow-band RFI. No new, highly-dispersed pulses were detected. Our pipeline was also run on a fraction of the HTRU high latitude beams to search for FRBs. All four previously published FRBs were recovered in this analysis. Had these

84 62 Chapter 4. An Absence of Fast Radio Bursts at Intermediate Latitudes events occured in the intermediate latitude dataset, they would have been detected. 4.3 Discussion Although the HTRU intermediate latitude survey observed for almost twice as long as the survey reported by Thornton et al. (2013), no bursts were detected. The likelihood of finding N FRBs in our survey based on M FRBs detected at high latitudes, marginalized over the unknown FRB rate, is given by P (N M) = Z 1 0 P (N )P ( M)d (4.2) where is the expected number of detections, and has a value of 1.88, the ratio of on-sky time of this survey compared to the Thornton survey. Here P (N ), thedistributionof the number of events given an expected number of detections, is Poissonian. Using Bayes Theorem and a flat prior for, the distribution for P ( M) is also Poissonian. Equation 4.2 thus reduces to: P (N M) = N (1+M+N) (M + N)! (1 + ). (4.3) M! N! A full derivation of this equation and why it is used is included in Appendix B. Based on a detection of 4 FRBs in 615 hours of high latitude data the probability of detecting 0 FRBs in the intermediate latitude survey is 0.5%, thus excluding the hypothesis that FRBs are uniformly distributed on the sky with 99.5% confidence. The low probability of this result poses a critical question regarding the spatial distribution of these events. No systematic bias was introduced by the pointing position of the telescope, as both survey components covered similar distribution of telescope azimuth and elevation. The primary differences between the two HTRU survey components are Galactic effects introduced along sightlines at lower Galactic latitudes. Here we discuss four potential contributors to a decreased sensitivity to FRBs at b < 15 dispersion in the interstellar medium (ISM), interstellar scattering, sky temperature, and scintillation effects Dispersion in the ISM A broadband radio pulse traveling through the ISM experiences a dispersive delay proportional to the squared wavelength of the radiation and the magnitude of the delay is a measure of the electron column density along the line of sight, DM. All radio pulsars in the Galaxy have a measured DM that can be related to distance from Earth using Galactic

85 4.3. Discussion 63 electron density models such as NE2001, used in most pulsar DM/distance estimates. The NE2001 model has been calibrated against nearby pulsars for which distances are known. Using NE2001 as a model of the ionized Galaxy, we can estimate the maximum DM contribution DM Galaxy from the Milky Way along any line of sight. At high Galactic latitudes sightlines probe the diffuse halo of the Galaxy and DM Galaxy is typically less than 50 pc cm 3. Within the region of the intermediate latitude survey, however, Galactic dispersion contributes an average of 380 pc cm 3 and has been measured to contribute as much as 1778 pc cm 3 near the Galactic center (Eatough et al., 2013). After subtracting DM Galaxy as predicted by NE2001, the high-latitude FRBs have excess DMs between 521 and 1072, which can be attributed to the IGM and any putative host galaxy. For an FRB pulse with a DM 0 =DM host +DM IGM entering the Galaxy along a sightline through the intermediate latitude region the total DM observed would, on average, be of order pc 1500 cm 3 for an FRB with DM 0 similar to the maximum in the known sample. We would recover this pulse as it is still below the maximum DM trial in our search (5000 pc cm 3 ) in the absence of other pulse smearing effects Scattering in the ISM Three possible scattering regimes can be considered for FRBs at cosmological distances, scattering due to the host galaxy, the IGM, and the ISM of the Milky Way. Previous studies concerned with the detectability of FRBs have assumed two extreme cases for the IGM: strong, ISM-like scattering, and no scattering (Hassall et al., 2013; Trott et al., 2013; Lorimer et al., 2013). If IGM scattering was as strong as that of the ISM, FRB pulses would be detected with much lower peak flux densities and broader pulses, leading to the conclusion that IGM scattering is likely weak or even un-observable (Macquart & Koay, 2013). Only one FRB in the HTRU sample, FRB110220, showed measurable scattering. Here we consider only the effects of Galactic scattering due to multipath propagation in the ISM, as IGM and host contributions appear to be minimal, and should have similar values for all FRBs irrespective of position. We scale the effects of Galactic scattering in the intermediate latitude survey region using the NE2001 model and the relationship between DM and scattering timescale from Bhat et al. (2004) (Equation 1.7). This relation calculates the expected total of pulse broadening effects along any line of sight for an input DM. We use the DM Galaxy obtained from NE2001 for our analysis in Section as input to estimate a scattering timescale d. For the majority of survey pointings (>85%), we determine our measurements are still

86 64 Chapter 4. An Absence of Fast Radio Bursts at Intermediate Latitudes sensitive to FRB signals even in the presence of strong scattering in the ISM Sky Temperature A third consideration at low Galactic latitudes is the decrease in sensitivity due to sky temperature (T sky ). At radio frequencies observations can be sensitivity limited if the standard deviation of noise fluctuations approaches the total power of the observed source (Lorimer & Kramer, 2004). In the analysis that follows we use the 1.4 GHz T sky map from de Oliveira-Costa et al. (2008) to estimate the sky temperature for the survey region. Excluding pointings within a few degrees of the Galactic centre, T sky lies between 3 K and 30 K over the intermediate latitude survey. For b > 2, T sky is never more than 10 K, still well below our system temperature (T sys = 23 K, Keith et al., 2010). The pointings for which T sky is equal to or greater than T sys are already sensitivity limited due to scattering and/or the total DM contribution along the line of sight as determined in Sections and Comparing the mean value of T sky for the intermediate latitude pointings with the mean value at high latitudes we find a difference of only 1 K between intermediate latitude survey pointings at b > 5 (4 K) and high latitude survey pointings (3 K). Sky temperature increases significantly only in the Galactic Plane where the mean temperature is closer to 10 K. In addition, T atmosphere and T spillover are negligible at Parkes at this frequency. Sky temperature is therefore not a significant factor in our comparison between the two survey components, and does not play a role in limiting our sensitivity, other than in regions where the survey is already limited by other Galactic factors Scintillation The dearth of low latitude FRB events compared with high latitudes might also be explained by scintillation at high Galactic latitudes where FRB pulses may be amplified by single wideband scintles. For the four known FRBs, the scintillation bandwidths predicted using NE2001 for each line of sight are 4.8, 2.5, 5.8, and 6.1 MHz for FRB110220, FRB , FRB110703, and FRB120127, respectively. All are around two orders of magnitude too small to produce significant amplification. However, these values are extrapolations from the Bhat et al. (2004) model fit, which has a high variance at the extremes, and may not be exact. 1 The published name for this FRB in Thornton et al. (2013) (FRB110627) is incorrect based on the UTC naming convention.

87 4.3. Discussion 65 Amplifications of pulsar fluxes by orders of magnitude have been observed in the 47 Tucanae and SMC pulsars (Camilo et al., 2000). If some FRBs are similarly amplified it may be that a fraction of those observed would not have been detected unless favourable scintillation conditions existed at the time of their arrival. In the Galactic Plane we know that pulsar flux densities are relatively stable (Stinebring et al., 2000) and not amplified by diffractive scintillation to the same degree. So diffractive scintillation may help explain the larger number of FRBs we detect at high latitudes Sensitivity Map The factors introduced in the previous sections can ultimately be combined to produce a map to determine the fraction of survey pointings in which the combination of these effects dramatically limits sensitivity. We created a simple mask to simulate the expected Galactic effect on a pulse traveling through the ISM. The effects of the temporal smearing of a pulse across the band due to dispersion, pulse broadening due to scattering, and sky temperature will combine to decrease the signal-to-noise detected for an FRB pulse from an intrinsic value S/N to an effective S/N 0 as q 0 = d 2 + t2 DM q W 0 = 02 +Wint 2 p S/N 0 Wint /W =S/N 0 (1 + T sky /23K) (4.4) for a receiver with T sys of 23 K. Here d is the pulse broadening time, and t DM is the pulse smearing time due to dispersion, which combine to give an effective scattering timescale 0, and W int and W 0 are the intrinsic and effective widths, respectively. This set of equations allows us to estimate the detectability of an FRB pulse within the parameters of our survey. From the values in Equations 4.4 we can create a map of the intermediate latitude survey and see where a simulated FRB pulse with properties similar to the FRBs in Thornton et al. (2013) falls below our signal-to-noise threshold of S/N = 10. In Figure 4.1 we simulate an FRB detection with S/N = 13, and a pulse width before traveling through the Galaxy, W int = 2 ms. The pulse falls below the detection threshold in 20% of all intermediate latitude pointings, primarily in high-dm regions where the dispersion smearing time and pulse broadening time are large. As expected the regions where we are least sensitive to FRBs are in the vicinity of the Galactic center, in the Galactic Plane, and through the Gum Nebula (at (`, b) ( 100, 10 )).

88 66 Chapter 4. An Absence of Fast Radio Bursts at Intermediate Latitudes Figure 4.1 The effective signal-to-noise, S/N 0, of an FRB observed along all sightlines of the intermediate latitude survey. An FRB event is simulated with S/N = 13, and width = 2-ms before entering the Galaxy and the effects of dispersive smearing, interstellar scattering, and T sky are taken into account to estimate the effective signal-to-noise with which the pulse would be detected with the Parkes multibeam receiver. The total time on sky of pointings not sensitive to FRBs by this metric is 231 hours of observing. This reduces the value of in Equation 4.3 from 1.88 to 1.51 and increases the probability to 1.0% Summary Even when taking into account Galactic effects, the probabilty of non-detection at intermediate latitudes given the current rate estimate is extremely low. We note that the Bhat et al. (2004) model describes the scattering that occurs in our Galaxy; however, owing to the lever arm effect (Hassall et al., 2013), the contribution of Galactic scattering to extragalactic sources may be significantly reduced. In the no scattering case, the percentage of pointings no longer sensitive FRB pulses decreases to 14% (Figure 4.2) making our results and original predictions still more discrepant. Currently, the rate calculation is based on a handful of sources in only a fraction of the HTRU high latitude data. Further analysis is expected to reveal a substantial population of FRBs that will allow for a more precise rate calculation. An increased sample of FRBs is essential to resolving whether or not there is a true lack of FRBs detected through, or in the direction of, the Galactic plane. The search for additional FRBs at high latitudes is detailed in Chapter 6.

89 4.4. Conclusions 67 Figure 4.2 The effective signal-to-noise, S/N 0 of the simulated FRB from Figure 4.1 with no ISM scattering effects applied. Pulse smearing due to dispersion in the ISM is still accounted for. In this case the simulated FRB would drop below our detection threshold in only 14% of survey pointings 4.4 Conclusions We conducted a single pulse search of 1,157 hours of the High Time Resolution Universe intermediate latitude survey of the Southern radio sky at 1.4 GHz with 64-µs time resolution. We searched the data using the new GPU-based single pulse processing tool heimdall over a range of incoherent DM trials from 0 to 5000 pc cm 3 for a range of pulse widths. We searched for pulses with FRB-like measurable pulse properties with a ratio DM/DM Galaxy > 0.9. We did not detect any FRBs in the intermediate latitude survey. We verified the search pipeline on the high latitude FRBs in a blind search and all were recovered. Based on the detections in 615 hours of observations by Thornton et al. (2013) the probability of a non-detection in the HTRU intermediate latitude survey was 0.50%; this low probability lead us to investigate possible causes of the discrepancy. The combined contribution along sightlines through the Galactic disk of dispersion smearing, interstellar scattering, and sky temperature account for a 20% decrease in FRB-sensitive pointings for the survey, however this is still not enough to explain the null result and only increases the probability of a non-detection to 1.0%, thus excluding the hypothesis that FRBs are uniformly distributed on the sky with 99% confidence. We conclude that the low probability of agreement between results at high and intermediate latitudes reveals a disagreement between the rates calculated from these two surveys. A further analysis of the HTRU high latitude data will provide a more stringent limit on all-sky FRB rates.

90 68 Chapter 4. An Absence of Fast Radio Bursts at Intermediate Latitudes We note that any Galactic model of FRB events must explain not only the dispersion and scattering seen in FRB pulses, but also the latitude distribution found in this work.

91 5 Identifying the source of perytons at the Parkes radio telescope In this chapter we present recent searches of archival and contemporary Parkes data for perytons. New perytons, discovered within days of their occurrence combined with new data from on-site radio frequency interference monitoring led to the identification of the source. We were able to generate perytons through unconventional use of the microwave ovens at the Parkes site. We also discuss the implications of the man-made progenitor of perytons on the source of FRBs. 5.1 Introduction Peryton is the moniker given to a group of radio signals which have been reported at the Parkes and Bleien Radio Observatories at observing frequencies 1.4GHz (Burke- Spolaor et al., 2011a; Kocz et al., 2012; Bagchi et al., 2012; Saint-Hilaire et al., 2014). The signals are seen over a wide field-of-view suggesting that they are in the near-field rather than boresight astronomical sources (Kulkarni et al., 2014). They are transient, lasting 250 ms across the band, and the 25 perytons reported in the literature occurred only during office hours and predominantly on weekdays. These characteristics suggest that the perytons are a form of human-generated radio frequency interference (RFI). In fact one of the perytons defining characteristics their wide-field detectability is routinely used to screen out local interference detections in pulsar searches (Keane et al., 2010; Kocz et al., 2012). Perytons most striking feature, which sets them apart from standard interference signals, is that they are swept in frequency. The frequency dependent detection of the signal is sufficiently similar to the quadratic form of a bona fide astrophysical signal which has 69

92 70 Chapter 5. Identifying the source of perytons traversed the interstellar medium, that the origin of the first fast radio burst, FRB (Lorimer et al., 2007), was called into question by Burke-Spolaor et al. (2011a). This was mainly based upon the apparent clustering of peryton dispersion measures (DMs) around 400 pc cm 3, which is within 10% of FRB s DM. Ongoing searches are actively searching for FRBs and perytons and are capable of rapidly identifying detections. In this paper, we report on three new peryton discoveries from a single week in 2015 January made with the Parkes radio telescope. In addition to the rapid identification within the Parkes observing band, the RFI environment over a wider frequency range was monitored with dedicated equipment at both the Parkes Observatory and the Australia Telescope Compact Array (located 400 km north of Parkes). For one event, the Giant Metrewave Radio Telescope (GMRT), in India, was being used to observe the same field as Parkes. Below, in Section 5.2, we describe the observing setup and details of the on-site RFI monitors. In Section 5.3 we present the results of the analysis of our observations, and our successful recreation of peryton signals. Section 5.4 discusses, in more depth, the identified sources of the signals and we compare the perytons to the known FRB population in Section 5.5. We present our conclusions in Section Observations As part of the SUrvey for Pulsars and Extragalactic Radio Bursts (SUPERB 1 ; Keane et al., in prep.), at Parkes, real-time pulsar and transient searches are performed. The live transient searching system developed for SUPERB, which uses the heimdall single pulse search software package, is now routinely used by several projects. The survey data are taken using the Berkeley Parkes Swinburne Recorder (BPSR) with the observing setup described in Chapter 2. For each pointing 13 such data streams are recorded, one for each beam of the multibeam receiver (Staveley-Smith et al., 1996). The survey has been running since 2014 April to search for pulsars and FRBs. In 2014 December, an RFI monitoring system was installed on the Parkes site identical to ones which had been in operation at the Australia Telescope Compact Array (ATCA) since 2014 November. The RFI monitor itself is a Rhode & Schwarz EB500 Monitoring Receiver capable of detecting signals across a wide range of frequencies from 402 MHz to 3 GHz. The frequency and time resolution of the monitoring system are limited to 2 MHz and 10 s, respectively. The antenna is mounted on a rotator, which sweeps out 360 in azimuth every 12 min, then returns to an azimuth of 0 for another 8 min before repeating the cycle. 1

93 5.2. Observations 71 A spectrum is produced every 10 s, which is obtained by stepping in 20 MHz steps across the full band. So each 10 s spectrum has only 0.1 s of data at any given frequency. The installation of the monitor gives an unprecedented view of the RFI environment at the telescope at any given time and this setup is ideal for identifying very strong signals of RFI which may corrupt observations with the main dish at Parkes. In 2015 January March, h (13.3 d) of 13-beam BPSR data were recorded for the SUPERB survey alone to search for pulsars and FRBs. Total time in the BPSR observing mode in these months was h over a range of observing projects aimed at detecting and studying fast transients. Ultimately h of these observations were searched for perytons in the months of 2015 January March in this work. Three events were discovered, all occurring in the week starting 2015 January 19, on the 19th (Monday), 22nd (Thursday), and 23rd (Friday) in a rotating radio transient search, the PULSE@Parkes outreach project (Hobbs et al., 2009) and SUPERB, respectively. For the event on January 23, simultaneous coverage with the GMRT was also available, which was shadowing Parkes as part of the SUPERB project s effort to localize FRBs. The peryton search for SUPERB and other BPSR data is performed after the Parkes data have been transferred to the gstar supercomputer facility at Swinburne University of Technology. The peryton search is performed by summing the frequency time data of all 13-beams from BPSR and searching these summed data using heimdall for single pulses with a signal-to-noise ratio (S/N) 10 and DM 10 pc cm 3. This method ensures that dispersed pulses occurring in a majority of beams are efficiently detected even if they may be too weak to be detected in single-beam searches. For the perytons identified in 2015 January, once the date and UTC time were established the Parkes and ATCA RFI monitor data were checked around the times of the perytons for the presence of signals that might be correlated with the appearance of a peryton at 1.4 GHz. The same search technique was applied to search for perytons in the High Time Resolution Universe (HTRU) intermediateand high-latitude surveys of Keith et al. (2010). The HTRU intermediate-latitude survey was conducted between 2008 and 2010 and the high latitude component was conducted between 2009 and The HTRU survey concluded in 2014 February and as such no RFI monitor data are available for events detected in these data nor for any peryton detected before those reported here.

94 72 Chapter 5. Identifying the source of perytons Table 5.1 Properties of the perytons from 2015 January Date Time DM DM S/N Width Telescope Telescope (dd-mm-yy) (UTC) (pc cm 3 ) error (beam 1) (ms) azimuth elevation (deg) (deg) :39: :28: :48: Results Three perytons The properties of the three perytons discovered in 2015 January are noted in Table 5.1, and Figure 5.1 shows their time frequency structure. These events are typical perytons in that they are bright and detectable in all beams of the multibeam receiver. They are also apparently dispersed or chirped in frequency, but not strictly obeying the quadratic cold plasma dispersion law; signals from pulsars and FRBs are observed to obey this law precisely (Hassall et al., 2012; Thornton et al., 2013). They have a typical peryton spectrum, being broad-band, but brighter at higher frequencies. Conversely, an off-axis detection of an astronomical source (i.e. one effectively at infinity) would be suppressed at the highest frequencies, but the near-field beam pattern is radically different (see e.g. figure 10 in Kulkarni et al. 2014). The existence of a standard template for peryton spectra and similar DMs also suggests that the source, or sources, are at roughly constant distances and possibly consistently reproducible. These three perytons are the focus of our analysis as they were the first with simultaneous coverage with additional instruments: the RFI monitors operating at both the Parkes and ATCA sites. For all three events, the Parkes RFI monitor detected emission in the frequency range GHz consistent (to less than one time sample) with the time of the 1.4 GHz peryton event. This strongly suggests that the 1.4 GHz millisecondduration burst is somehow associated with the episodes of 2.4 GHz emission, which last for some tens of seconds. The broad RFI spectra from the monitor at the times around the perytons are shown in Figure 5.2 with the bright emission shown as well as the time of the peryton. Simultaneous emission in the same frequency range was seen in the ATCA data at the time of the first peryton, but no such emission was seen for any other peryton detection, making it likely that this one event was a coincidence (see Figure 5.3). For the

95 5.3. Results 73 Figure 5.1 The time frequency structure of the three January perytons (bottom of each panel) and the pulse shape after dedispersion to the optimal DM in Table 5.1 and summed in frequency across the band (top of each panel). In the case of events on and , the summed 13-beam data are shown. For only beam 1 is plotted as the outer beam data were not recorded to disc.

96 74 Chapter 5. Identifying the source of perytons third peryton, simultaneous coverage with GMRT at 325 MHz observing in 2 s snapshots also produced no detection. The detection on only the Parkes site confines the source(s) of the peryton signals to a local origin. The GHz range of the spectrum is allocated to fixed, mobile and broadcasting uses by the Australian Communications and Media Authority, and includes use by industrial, scientific and medical applications, which encompasses microwave ovens, wireless internet, and other electrical items. This suggests that the perytons may be associated with equipment operating at GHz, but that some intermittent event or malfunctioning, for example, from the equipment s power supply, is resulting in sporadic emission at 1.4 GHz Prevalence of GHz signals at Parkes As can be seen in Figure 2 there is at least one case where a single peryton is detected but there are multiple or ongoing detections at GHz around the time of the peryton. This already indicates that while peryton detections at 1.4 GHz coincide with episodes of emission at higher frequency, the higher frequency emission can occur without generating a peryton. More detailed inspection of the archival RFI monitor data at Parkes gives an indication of the prevalence of these episodes at higher frequencies. In the months investigated several hundred spikes of emission were detected in the frequency range GHz. These events cluster in time of day and are much more common during daytime (between the hours of 9am and 5pm local time). A time-of-day histogram of these spikes over the period of 2015 January 18 to March 12 is plotted in Figure 5.4. This is entirely consistent with the use of microwave ovens and other electrical equipment. Tests at Parkes confirmed that microwave ovens produced detectable levels of 2.4 GHz emission in the RFI monitoring equipment independent of the azimuth of the rotator. Standard practice at ATNF observatories is not to allow the use of microwave ovens on site when observing in the 2.4 GHz band is taking place Archival perytons Using the search technique described in Section 5.2, 15 perytons were found in the HTRU intermediate latitude survey and an additional 6 perytons were found in a search of 90% of the high latitude survey (the same survey region searched for FRBs in Chapter 6). While the RFI monitor had not yet been set up on site and the RFI environment is impossible to recover, we can use these perytons to study the ensemble properties. Combining the perytons from 2015 January, HTRU, Burke-Spolaor et al. (2011a), Kocz et al. (2012), and

97 5.3. Results 75 Figure 5.2 RFI monitor spectra from Parkes for the perytons in the week starting 2015 January 19. The time of peryton has been indicated around the GHz range by black arrows.

98 76 Chapter 5. Identifying the source of perytons Figure 5.3 RFI monitor data from Parkes and the ATCA between 2.30 and 2.50 GHz around the times of the three January perytons and one peryton from the Woolshed microwave oven tests ( ). Figure 5.4 Number of narrow-emission spikes detected with the RFI monitor with S/N > 10 in a 60 MHz window around GHz between 18 January and 12 March, 2015.

99 5.3. Results 77 Bagchi et al. (2012) the total number of perytons is 46. The properties of these sources, especially how they relate to the population properties of FRBs is discussed in more detail in Section Generating perytons With the recognition that peryton signals are likely to be associated with equipment emitting at GHz, an effort was made to try to identify such equipment on site, and attempt to create a peryton. As microwave ovens are known to emit in this frequency range and could potentially produce short-lived emission the site microwave ovens were the focus of our initial tests for reproducing peryton signals. There are three microwave ovens on site in close proximity to the telescope that experience frequent use located in the tower below the telescope, in the visitors centre and in the staff kitchen in the building traditionally referred to as the Woolshed. There are two additional microwave ovens at the observer s quarters approximately 1 km from the main site. The first tests occurred on 2015 February 27 during scheduled maintenance while the telescope was stowed at zenith. The BPSR system was turned on for all 13 beams and the three microwave ovens on-site were run on high and low power for durations of s. In each test the load in the microwave oven was a ceramic mug full of water. In the first set of tests, a single peryton was detected during tests of the tower microwave oven with a DM of 345 pc cm 3. The detection of radiation from the tower microwave oven would be very surprising as the tower is shielded on the windows and in the walls and the dish surface blocks the line of sight to the receiver in the cabin at the prime focus. However it was later determined that the Woolshed microwave oven was also in use at the time, unrelated to these tests, and might potentially have been the source of the peryton. The second set of tests were conducted on 2015 March 12, this time pointing the telescope at azimuth and elevation combinations where we often see perytons. From the 21 perytons discovered in the HTRU survey and the known pointing locations a broad estimate of the peryton rate as a function of azimuth and elevation can be calculated. For the HTRU perytons, the rate is highest at an azimuth and elevation of ( 130,65)and when pointing near zenith. An initial test was conducted with the microwave ovens while pointing the telescope at these locations and no perytons were seen. The decisive test occurred on 2015 March 17 when the tests were repeated with the same microwave oven setup but instead of waiting for the microwave oven cycle to finish the microwave oven was stopped by opening the door. This test produced three bright perytons from the staff kitchen microwave oven, all at the exact times of opening the microwave oven

100 78 Chapter 5. Identifying the source of perytons Figure 5.5 One of the bright perytons generated during the test on 2015 March 17 with DM = pc cm 3. The plot elements are the same as those in Figure 5.1. RFI monitor data at the time of this peryton are shown in Figure 5.3. door, with DMs of 410.3, 410.3, and pc cm 3 (the first of these generated perytons is used in Figures 5.3 and 5.5). With knowledge that this mode of operation of a microwave oven could produce perytons, we examined the range of azimuths and elevations at which there was direct line of sight from the microwave oven to the multibeam receiver (i.e., the underside of the focus cabin). As is apparent in Figure 5.6, almost all the perytons with DMs > 300 occurred when there was visibility of the focus cabin from the Woolshed microwave oven. This left the smaller sample of perytons with lower DMs, which were, however, consistent with an origin at the visitors centre or the Quarters. (This sample also included all five events which had been detected on the weekend, when there were generally no staff on-site and the Woolshed was not in use.) Similar tests were performed with a previously installed microwave oven in the visitors centre and six perytons were seen at the times corresponding to opening the door; however, these perytons had DMs of 206.7, 204.9, 217.0, 259.2, 189.8, and pc cm 3. This process does not generate a peryton every time, however; in fact perytons appear to be generated with an 50% success rate. A bimodal distribution of peryton DMs can be accounted for from at least two microwave ovens on-site being used and stopped in this manner. The detectability of perytons with a given DM from a microwave oven stopped this way depends on the direction in which the telescope is pointing. The receiver is sensitive to perytons when the microwave oven producing the bursts has a direct line of sight to the focus cabin and receiver of the