Open Dissertation Mrosenberg 2019.Pdf
Total Page：16
File Type：pdf, Size：1020Kb
The Pennsylvania State University The Graduate School A SEARCH FOR VERY HIGH ENERGY PHOTONS FROM GAMMA-RAY BURSTS WITH THE HIGH ALTITUDE WATER CHERENKOV OBSERVATORY A Dissertation in Physics by Matthew M. Rosenberg © 2019 Matthew M. Rosenberg Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy December 2019 The dissertation of Matthew M. Rosenberg was reviewed and approved∗ by the following: Miguel Mostafá Professor of Physics and of Astronomy and Astrophysics Dissertation Advisor, Chair of Committee Kohta Murase Assistant Professor of Physics and of Astronomy and Astrophysics Stephane Coutu Professor of Physics and of Astronomy and Astrophysics Peter Mészáros Professor of Physics and Eberly Chair Professor of Astronomy and Astrophysics Richard Robinett Professor of Physics Associate Head for Undergraduate and Graduate Students ∗Signatures are on file in the Graduate School. ii Abstract Gamma-Ray Bursts (GRBs) are brief, intense flashes of gamma rays lasting from a fraction of a second to minutes. The prompt emission from these explosive events outshines all the stars in their entire host galaxy. Thought to be produced by the core collapse of massive stars and the merger of compact stellar remnants in distant galaxies, GRBs can liberate on the order of 1054 ergs of gravitational potential energy in just milliseconds. In addition to constituting an interesting phenomenon in their own right, these cosmic engines accelerate particles to energy scales unattainable in laboratories on Earth and thus provide a potentially interesting probe of fundamental physics as well as source candidates for ultra-high energy cosmic rays. We present recent efforts to extend the observation of GRBs beyond ∼100 GeV with the High Altitude Water Cherenkov (HAWC) observatory. Located in Puebla, Mexico at a latitude of 19◦ north and an altitude of 4100 meters above sea level, HAWC employs a 20,000 m2 array of 300 water Cherenkov detectors to observe the relativistic charged particles produced in the extensive air showers that develop upon the collision of high-energy gamma rays with Earth’s atmosphere. This technique provides sensitivity to ∼100 GeV – 100 TeV gamma rays, allows for nearly continuous operations, and achieves a wide instantaneous field of view of ∼2 sr that allows for daily monitoring of the northern sky. HAWC is thus ideally suited to capture any &100 GeV emission from transient events like GRBs. As GRB photons above a few TeV in energy are likely to be absorbed by the extra- galactic background light before reaching Earth, HAWC’s ∼100 GeV – 1 TeV data is of prime importance in the search for high-energy GRB emission. However, the small air-shower data necessary to achieve this lower threshold of ∼100 GeV has previously been poorly modeled in HAWC simulations and has therefore not been used in past HAWC GRB searches. We will show that these modeling discrepancies were caused by an inaccurate treatment of detector noise, outline a solution that allows HAWC to achieve its lowest possible energy threshold, and present a method to reduce the impact of detector noise on HAWC’s angular resolution in this newly recovered small air-shower data. Along with new GRB search algorithms, these improvements provide up to an order of magnitude improvement in HAWC’s sensitivity to gamma-ray bursts. We use these new techniques to scan archival HAWC data for gamma-ray emission coincident with GRBs detected by the Fermi and Swift satellites between December 2014 and April 2018. While no significant detections were found, a comparison of our upper limits on the &100 GeV flux from GRBs 170206A and 171120A with Fermi measurements suggests a cut-off or spectral steepening below that energy under a redshift assumption of z . 0.3. However, these limits are not sufficiently strict to compellingly constrain GRB models with predictions for TeV scale gamma-ray emission. iii Table of Contents List of Figures vii List of Tables xxv List of Equations xxvii Acknowledgments xxx Chapter 1 Introduction 1 1.1 Gamma-Ray Bursts . 2 1.1.1 Observational History . 3 1.1.1.1 The Vela Discovery . 3 1.1.1.2 The Compton Gamma-Ray Observatory . 3 1.1.1.3 Beppo-SAX and HETE-2 . 7 1.1.1.4 Swift . 8 1.1.1.5 Fermi . 10 1.1.1.6 HESS and MAGIC . 14 1.1.1.7 LIGO, Virgo, and the Multi-Messenger Era . 15 1.1.2 GRB Theory . 18 1.1.2.1 The GRB Paradigm . 18 1.1.2.2 EBL Attenuation . 22 1.2 The Role of HAWC in GRB Science . 24 Chapter 2 Detecting Gamma Rays 25 2.1 Extensive Air Showers . 25 2.1.1 Gamma-Ray Air Showers . 26 2.1.2 Cosmic-Ray Air Showers . 30 2.2 Cherenkov Radiation . 33 2.3 Gamma-Ray Detectors . 34 2.3.1 Direct Space-Based Detectors . 34 2.3.2 Imaging Atmospheric Cherenkov Telescopes . 35 2.3.3 Extensive Air-Shower Arrays . 37 iv Chapter 3 The High Altitude Water Cherenkov Observatory 39 3.1 Instrumentation, Electronics, and Online Processing . 41 3.2 Calibration . 45 3.2.1 Charge Calibration . 45 3.2.2 Timing Calibration . 47 3.3 Air-Shower Reconstruction . 49 3.3.1 Hit Selection and Charge Scaling . 49 3.3.2 Core Fit . 50 3.3.3 Angle Fit . 53 3.3.4 The Reconstruction Chain . 55 3.4 Event Size Bins . 56 3.5 Gamma/Hadron Shower Discrimination . 58 3.5.1 Compactness . 60 3.5.2 PINCness . 60 3.6 Sensitivity to Gamma Rays . 61 Chapter 4 HAWC’s Small Air-Shower Simulation 64 4.1 Monte Carlo Overview . 65 4.2 Discrepancies with Data . 65 4.3 Improved Modeling of Detector Noise in the Monte Carlo . 67 4.3.1 More Accurate Noise Models . 69 4.3.2 A Data Noise Overlay Algorithm . 72 Chapter 5 Improving HAWC’s Low-Energy Sensitivity 74 5.1 Low-Energy Reconstruction Challenges . 75 5.2 The Multi-Plane Fitter . 77 5.2.1 How the Algorithm Works . 78 5.2.2 Impact on Event Size . 78 5.2.3 Impact on Reconstruction Time . 79 5.3 A New Low-Energy Multi-Plane Fitter Analysis . 80 5.3.1 Setting the fHit Thresholds for Analysis Bins . 81 5.3.2 On-Array vs. Off-Array Events . 85 5.3.3 Combining High-Energy Bins . 89 5.3.4 Gamma/Hadron Separation Cuts for New Bins . 92 5.3.4.1 The Compactness and PINCness Variables Revisited . 92 5.3.4.2 Cut Optimization . 98 5.4 Performance of the Low-Energy Multi-Plane Fitter Analysis . 102 5.4.1 Results with One Year of Crab Data . 102 5.4.2 Agreement with MC Predictions of Crab Observations . 111 5.5 Improvements to Low-Energy Sensitivity . 115 5.5.1 Predicted Sensitivity Gain to Point Sources with a Low-Energy Cut-off 117 5.5.2 Sensitivity Gain in Low-fHit Crab Data . 118 v 5.6 MC Crab Predictions . 121 5.6.1 Significance and Excess Calculations . 121 5.6.2 Spectral Assumptions . 122 5.7 Other Gamma/Hadron Separation Variables Considered in the Multi-Plane Fitter Analysis . 125 5.7.1 Modeling of nHitSP-X Variables . 125 5.7.2 A Quality Cut on the Fraction of In-Time Hits . 127 5.7.3 A Muon Identification Variable . 129 5.8 Improving Low-Energy Sensitivity with the Existing Reconstruction . 134 5.9 An Alternate Noise Discrimination Technique . 137 Chapter 6 HAWC’s GRB Search Algorithms 143 6.1 The Published Single-Bin Excess Analysis . 143 6.2 A Multi-Bin Excess Analysis . 144 6.3 ZEBRA . 150 6.4 HAWC’s Sensitivity to GRBs . 158 6.4.1 Search Algorithm Comparisons . 159 6.4.2 The Most Sensitive Search Method . 162 Chapter 7 The 41 Month GRB Search 164 7.1 Burst Sample . 164 7.2 Time Windows . 165 7.3 Results . 166 7.3.1 Background Consistency . 166 7.3.2 Flux Limits . 167 7.3.3 Comparisons with Fermi Measurements . 169 7.4 Conclusions . 174 Appendix A List of Bursts in the 41 Month GRB Search 176 Appendix B Flux Limits for Bursts in the 41 Month GRB Search 184 Bibliography 192 vi List of Figures 1.1 Example BATSE light curves, in counts per second (cps) vs. time in seconds (s), for a sample of four GRBs [4]. ............................... 4 1.2 Distribution of T90, the time taken to observe 5% to 95% of all detected gamma rays, as measured by BATSE for GRBs in the BATSE 4B catalog [7]. .............. 5 1.3 Hardness ratio (HR) vs. T90 for GRBs seen by BATSE [8]. The hardness ratio is defined as a burst’s ∼100 - 300 keV fluence divided by its ∼50 - 100 keV fluence. Short GRBs, lasting less than 2s and plotted as squares with crosses, have harder spectra (are more skewed towards higher energies) than long GRBs, which last longer than 2s and are plotted as open circles. Also shown for these two samples of GRBs are dotted regression lines and their average HR and T90 values (as filled circles). The solid line simply connects these two points, while the dashed line is a regression line for the combined (long and short) GRB samples. HR and T90 are not correlated within either sample, and the overall correlation of the combined populations is simply an artifact of the different HR distributions of the two GRB classes. .................................. 6 1.4 A schematic diagram of the typical GRB X-ray afterglow light curve seen by Swift [17]. The prompt gamma-ray emission (phase 0) is followed by a power-law decay with an index of .