Constraining high-energy Emission with Fermi

Constraining the High-Energy Emission from Gamma-ray Bursts with Fermi

The Fermi Large Area Telescope Team M. Ackermann11affiliation: Deutsches Elektronen Synchrotron DESY, D-15738 Zeuthen, Germany , M. Ajello22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , L. Baldini33affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy , G. Barbiellini44affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, I-34127 Trieste, Italy 55affiliation: Dipartimento di Fisica, Università di Trieste, I-34127 Trieste, Italy , M. G. Baring66affiliation: Rice University, Department of Physics and Astronomy, MS-108, P. O. Box 1892, Houston, TX 77251, USA , K. Bechtol22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , R. Bellazzini33affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy , R. D. Blandford22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , E. D. Bloom22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , E. Bonamente88affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia, Italy 99affiliation: Dipartimento di Fisica, Università degli Studi di Perugia, I-06123 Perugia, Italy , A. W. Borgland22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , E. Bottacini22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , A. Bouvier1010affiliation: Santa Cruz Institute for Particle Physics, Department of Physics and Department of Astronomy and Astrophysics, University of California at Santa Cruz, Santa Cruz, CA 95064, USA , M. Brigida1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , R. Buehler22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , S. Buson1414affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Padova, I-35131 Padova, Italy 1515affiliation: Dipartimento di Fisica “G. Galilei”, Università di Padova, I-35131 Padova, Italy , G. A. Caliandro1616affiliation: Institut de Ciències de l’Espai (IEEE-CSIC), Campus UAB, 08193 Barcelona, Spain , R. A. Cameron22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , C. Cecchi88affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia, Italy 99affiliation: Dipartimento di Fisica, Università degli Studi di Perugia, I-06123 Perugia, Italy , E. Charles22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , A. Chekhtman1717affiliation: Artep Inc., 2922 Excelsior Springs Court, Ellicott City, MD 21042, resident at Naval Research Laboratory, Washington, DC 20375, USA , J. Chiang22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA 1818affiliation: email: jchiang@slac.stanford.edu , S. Ciprini1919affiliation: ASI Science Data Center, I-00044 Frascati (Roma), Italy 99affiliation: Dipartimento di Fisica, Università degli Studi di Perugia, I-06123 Perugia, Italy , R. Claus22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , J. Cohen-Tanugi2020affiliation: Laboratoire Univers et Particules de Montpellier, Université Montpellier 2, CNRS/IN2P3, Montpellier, France , V. Connaughton1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA 2121affiliation: email: connauv@uah.edu , S. Cutini2222affiliation: Agenzia Spaziale Italiana (ASI) Science Data Center, I-00044 Frascati (Roma), Italy , F. D’Ammando2323affiliation: IASF Palermo, 90146 Palermo, Italy 2424affiliation: INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica, I-00133 Roma, Italy , F. de Palma1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , C. D. Dermer2525affiliation: Space Science Division, Naval Research Laboratory, Washington, DC 20375-5352, USA , E. do Couto e Silva22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , P. S. Drell22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , A. Drlica-Wagner22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , C. Favuzzi1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , Y. Fukazawa2727affiliation: Department of Physical Sciences, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8526, Japan , P. Fusco1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , F. Gargano1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , D. Gasparrini2222affiliation: Agenzia Spaziale Italiana (ASI) Science Data Center, I-00044 Frascati (Roma), Italy , N. Gehrels2828affiliation: NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA , S. Germani88affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia, Italy 99affiliation: Dipartimento di Fisica, Università degli Studi di Perugia, I-06123 Perugia, Italy , N. Giglietto1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , F. Giordano1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , M. Giroletti2929affiliation: INAF Istituto di Radioastronomia, 40129 Bologna, Italy , T. Glanzman22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , J. Granot3030affiliation: Centre for Astrophysics Research, Science and Technology Research Institute, University of Hertfordshire, Hatfield AL10 9AB, UK , I. A. Grenier3131affiliation: Laboratoire AIM, CEA-IRFU/CNRS/Université Paris Diderot, Service d’Astrophysique, CEA Saclay, 91191 Gif sur Yvette, France , J. E. Grove2525affiliation: Space Science Division, Naval Research Laboratory, Washington, DC 20375-5352, USA , S. Guiriec1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , D. Hadasch1616affiliation: Institut de Ciències de l’Espai (IEEE-CSIC), Campus UAB, 08193 Barcelona, Spain , Y. Hanabata2727affiliation: Department of Physical Sciences, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8526, Japan , A. K. Harding2828affiliation: NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA , E. Hays2828affiliation: NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA , D. Horan3333affiliation: Laboratoire Leprince-Ringuet, École polytechnique, CNRS/IN2P3, Palaiseau, France , G. Jóhannesson3434affiliation: Science Institute, University of Iceland, IS-107 Reykjavik, Iceland , J. Kataoka3535affiliation: Research Institute for Science and Engineering, Waseda University, 3-4-1, Okubo, Shinjuku, Tokyo 169-8555, Japan , J. Knödlseder3636affiliation: CNRS, IRAP, F-31028 Toulouse cedex 4, France 3737affiliation: GAHEC, Université de Toulouse, UPS-OMP, IRAP, Toulouse, France , D. Kocevski22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA 3838affiliation: email: kocevski@stanford.edu , M. Kuss33affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy , J. Lande22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , F. Longo44affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, I-34127 Trieste, Italy 55affiliation: Dipartimento di Fisica, Università di Trieste, I-34127 Trieste, Italy , F. Loparco1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , M. N. Lovellette2525affiliation: Space Science Division, Naval Research Laboratory, Washington, DC 20375-5352, USA , P. Lubrano88affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia, Italy 99affiliation: Dipartimento di Fisica, Università degli Studi di Perugia, I-06123 Perugia, Italy , M. N. Mazziotta1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , S. McGlynn3939affiliation: Exzellenzcluster Universe, Technische Universität München, D-85748 Garching, Germany , P. F. Michelson22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , W. Mitthumsiri22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , M. E. Monzani22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , E. Moretti4040affiliation: Department of Physics, Royal Institute of Technology (KTH), AlbaNova, SE-106 91 Stockholm, Sweden 4141affiliation: The Oskar Klein Centre for Cosmoparticle Physics, AlbaNova, SE-106 91 Stockholm, Sweden 4242affiliation: email: moretti@particle.kth.se , A. Morselli4343affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Roma “Tor Vergata”, I-00133 Roma, Italy , I. V. Moskalenko22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , S. Murgia22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , M. Naumann-Godo3131affiliation: Laboratoire AIM, CEA-IRFU/CNRS/Université Paris Diderot, Service d’Astrophysique, CEA Saclay, 91191 Gif sur Yvette, France , J. P. Norris4444affiliation: Department of Physics, Boise State University, Boise, ID 83725, USA , E. Nuss2020affiliation: Laboratoire Univers et Particules de Montpellier, Université Montpellier 2, CNRS/IN2P3, Montpellier, France , T. Nymark4040affiliation: Department of Physics, Royal Institute of Technology (KTH), AlbaNova, SE-106 91 Stockholm, Sweden 4141affiliation: The Oskar Klein Centre for Cosmoparticle Physics, AlbaNova, SE-106 91 Stockholm, Sweden , T. Ohsugi4545affiliation: Hiroshima Astrophysical Science Center, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8526, Japan , A. Okumura22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA 4646affiliation: Institute of Space and Astronautical Science, JAXA, 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252-5210, Japan , N. Omodei22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , E. Orlando22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA 3232affiliation: Max-Planck Institut für extraterrestrische Physik, 85748 Garching, Germany , J. H. Panetta22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , D. Parent4747affiliation: Center for Earth Observing and Space Research, College of Science, George Mason University, Fairfax, VA 22030, resident at Naval Research Laboratory, Washington, DC 20375, USA , V. Pelassa1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , M. Pesce-Rollins33affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy , F. Piron2020affiliation: Laboratoire Univers et Particules de Montpellier, Université Montpellier 2, CNRS/IN2P3, Montpellier, France , G. Pivato1515affiliation: Dipartimento di Fisica “G. Galilei”, Università di Padova, I-35131 Padova, Italy , J. L. Racusin2828affiliation: NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA , S. Rainò1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , R. Rando1414affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Padova, I-35131 Padova, Italy 1515affiliation: Dipartimento di Fisica “G. Galilei”, Università di Padova, I-35131 Padova, Italy , S. Razzaque4747affiliation: Center for Earth Observing and Space Research, College of Science, George Mason University, Fairfax, VA 22030, resident at Naval Research Laboratory, Washington, DC 20375, USA , A. Reimer77affiliation: Institut für Astro- und Teilchenphysik and Institut für Theoretische Physik, Leopold-Franzens-Universität Innsbruck, A-6020 Innsbruck, Austria 22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , O. Reimer77affiliation: Institut für Astro- und Teilchenphysik and Institut für Theoretische Physik, Leopold-Franzens-Universität Innsbruck, A-6020 Innsbruck, Austria 22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , S. Ritz1010affiliation: Santa Cruz Institute for Particle Physics, Department of Physics and Department of Astronomy and Astrophysics, University of California at Santa Cruz, Santa Cruz, CA 95064, USA , F. Ryde4040affiliation: Department of Physics, Royal Institute of Technology (KTH), AlbaNova, SE-106 91 Stockholm, Sweden 4141affiliation: The Oskar Klein Centre for Cosmoparticle Physics, AlbaNova, SE-106 91 Stockholm, Sweden , C. Sgrò33affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy , E. J. Siskind4848affiliation: NYCB Real-Time Computing Inc., Lattingtown, NY 11560-1025, USA , E. Sonbas2828affiliation: NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA 4949affiliation: Adıyaman University, 02040 Adıyaman, Turkey 5050affiliation: Universities Space Research Association (USRA), Columbia, MD 21044, USA , G. Spandre33affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy , P. Spinelli1111affiliation: Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy 1212affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy , M. Stamatikos2828affiliation: NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA 5151affiliation: Department of Physics, Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA , Lukasz Stawarz4646affiliation: Institute of Space and Astronautical Science, JAXA, 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252-5210, Japan 5252affiliation: Astronomical Observatory, Jagiellonian University, 30-244 Kraków, Poland , D. J. Suson5353affiliation: Department of Chemistry and Physics, Purdue University Calumet, Hammond, IN 46323-2094, USA , H. Takahashi4545affiliation: Hiroshima Astrophysical Science Center, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8526, Japan , T. Tanaka22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , J. G. Thayer22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , J. B. Thayer22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , L. Tibaldo1414affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Padova, I-35131 Padova, Italy 1515affiliation: Dipartimento di Fisica “G. Galilei”, Università di Padova, I-35131 Padova, Italy , M. Tinivella33affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy , G. Tosti88affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia, Italy 99affiliation: Dipartimento di Fisica, Università degli Studi di Perugia, I-06123 Perugia, Italy , T. Uehara2727affiliation: Department of Physical Sciences, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8526, Japan , J. Vandenbroucke22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA , V. Vasileiou2020affiliation: Laboratoire Univers et Particules de Montpellier, Université Montpellier 2, CNRS/IN2P3, Montpellier, France , G. Vianello22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA 5454affiliation: Consorzio Interuniversitario per la Fisica Spaziale (CIFS), I-10133 Torino, Italy , V. Vitale4343affiliation: Istituto Nazionale di Fisica Nucleare, Sezione di Roma “Tor Vergata”, I-00133 Roma, Italy 5555affiliation: Dipartimento di Fisica, Università di Roma “Tor Vergata”, I-00133 Roma, Italy , A. P. Waite22affiliation: W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA
The Fermi Gamma-ray Burst Monitor Team V. Connaughton1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , M. S. Briggs1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA 5656affiliation: email: michael.briggs@nasa.gov , S. Guirec2828affiliation: NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA , A. Goldstein1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , J. M. Burgess1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , P. N. Bhat1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , E. Bissaldi77affiliation: Institut für Astro- und Teilchenphysik and Institut für Theoretische Physik, Leopold-Franzens-Universität Innsbruck, A-6020 Innsbruck, Austria , A. Camero-Arranz (50,58) J. Fishman1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , G. Fitzpatrick2626affiliation: University College Dublin, Belfield, Dublin 4, Ireland , S. Foley2626affiliation: University College Dublin, Belfield, Dublin 4, Ireland 3232affiliation: Max-Planck Institut für extraterrestrische Physik, 85748 Garching, Germany , D. Gruber3232affiliation: Max-Planck Institut für extraterrestrische Physik, 85748 Garching, Germany , P. Jenke5858affiliation: NASA Marshall Space Flight Center, Huntsville, AL 35812, USA , R. M. Kippen5757affiliation: Los Alamos National Laboratory, Los Alamos, NM 87545, USA , C. Kouveliotou5858affiliation: NASA Marshall Space Flight Center, Huntsville, AL 35812, USA , S. McBreen2626affiliation: University College Dublin, Belfield, Dublin 4, Ireland 3232affiliation: Max-Planck Institut für extraterrestrische Physik, 85748 Garching, Germany , C. Meegan5050affiliation: Universities Space Research Association (USRA), Columbia, MD 21044, USA , W. S. Paciesas1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , R. Preece1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA , A. Rau3232affiliation: Max-Planck Institut für extraterrestrische Physik, 85748 Garching, Germany , D. Tierney2626affiliation: University College Dublin, Belfield, Dublin 4, Ireland , A. J. van der Horst5858affiliation: NASA Marshall Space Flight Center, Huntsville, AL 35812, USA 5959affiliation: NASA Postdoctoral Program Fellow, USA , A. von Kienlin3232affiliation: Max-Planck Institut für extraterrestrische Physik, 85748 Garching, Germany , C. Wilson-Hodge5858affiliation: NASA Marshall Space Flight Center, Huntsville, AL 35812, USA , S. Xiong1313affiliation: Center for Space Plasma and Aeronomic Research (CSPAR), University of Alabama in Huntsville, Huntsville, AL 35899, USA
Abstract

We examine 288 GRBs detected by the Fermi Gamma-ray Space Telescope’s Gamma-ray Burst Monitor (GBM) that fell within the field-of-view of Fermi’s Large Area Telescope (LAT) during the first 2.5 years of observations, which showed no evidence for emission above 100 MeV. We report the photon flux upper limits in the 0.110 GeV range during the prompt emission phase as well as for fixed 30 s and 100 s integrations starting from the trigger time for each burst. We compare these limits with the fluxes that would be expected from extrapolations of spectral fits presented in the first GBM spectral catalog and infer that roughly half of the GBM-detected bursts either require spectral breaks between the GBM and LAT energy bands or have intrinsically steeper spectra above the peak of the spectra (). In order to distinguish between these two scenarios, we perform joint GBM and LAT spectral fits to the 30 brightest GBM-detected bursts and find that a majority of these bursts are indeed softer above than would be inferred from fitting the GBM data alone. Approximately 20% of this spectroscopic subsample show statistically significant evidence for a cut-off in their high-energy spectra, which if assumed to be due to attenuation, places limits on the maximum Lorentz factor associated with the relativistic outflow producing this emission. All of these latter bursts have maximum Lorentz factor estimates that are well below the minimum Lorentz factors calculated for LAT-detected GRBs, revealing a wide distribution in the bulk Lorentz factor of GRB outflows and indicating that LAT-detected bursts may represent the high end of this distribution.

Gamma-rays: Bursts: Prompt
6060affiliationtext: email: valerie@nasa.gov

1 Introduction

Observations by the Fermi Gamma-ray Space Telescope have dramatically increased our knowledge of the broad-band spectra of gamma-ray bursts (GRBs). The Gamma-ray Burst Monitor (GBM) on board Fermi has detected over 700 GRBs in roughly 3 years of triggered operations. Of these bursts, 29 have been detected at energies  100 MeV by Fermi’s Large Area Telescope (LAT); and five of these bursts: GRB 080916C, GRB 090510, GRB 090328, GRB 090902B, and GRB 090926A, have been detected at energies  GeV. The high-energy emission from the majority of these bursts show evidence for being consistent with the high-energy component of the smoothly joined broken power-law, commonly referred to as the Band spectrum (Band et al., 1993), that has been observed in the GBM energy range. Three of these bursts: GRB 090510 (Ackermann et al., 2010a), GRB 090902B (Abdo et al., 2009a), and GRB 090926A (Ackermann et al., 2011a), though, exhibit an additional hard spectral component that is distinct from the continuum emission observed at sub-MeV energies.

Similar high-energy emission above 100 MeV was detected by the Energetic Gamma-Ray Experiment Telescope (EGRET) onboard the Compton Gamma-Ray Observatory and by the AGILE spacecraft (Del Monte et al., 2011). The prompt high-energy emission detected by EGRET from GRB 930131 (Sommer et al., 1994; Kouveliotou et al., 1994) and GRB 940217 (Hurley et al., 1994), was consistent with an extrapolation of the GRB spectrum as measured by the Burst And Transient Source Experiment (BATSE) in the 25 keV2 MeV energy range. EGRET observations of GRB 941017 (González et al., 2003), on the other hand, showed evidence for an additional hard spectral component that extended up to 200 MeV, the first such detection in a GRB spectrum.

Unlike these previous detections by EGRET, many of the LAT detected bursts have measured redshifts, made possible through X-ray localizations by the Swift spacecraft (Gehrels et al., 2004) and ground-based follow-up observations of their long-lived afterglow emission. The high-energy detections, combined with the redshift to these GRBs, have shed new light into the underlying physics of this emission. At a redshift of (McBreen et al., 2010), the detection of GeV photons from GRB 090510 indicates a minimum bulk Lorentz factor of in order for the observed gamma rays to have avoided attenuation due to electron-positron pair production (Ackermann et al., 2010b). Furthermore, a spectral cut-off at GeV is quite evident in the high-energy component of GRB 090926A, which if interpreted as opacity due to attenuation within the emitting region, allows for a direct estimate of the bulk Lorentz factor of 700 for the outflow producing the emission (Ackermann et al., 2011b).

Perhaps equally important for unraveling the nature of the prompt emission is the lack of a significant detection above 100 MeV for the majority of the GRBs detected by the GBM. The LAT instrument has detected roughly 8 of the GBM-triggered GRBs that have occurred within the LAT field-of-view (FOV). This detection rate places limits on the ubiquity of the extra high-energy components detected by LAT, EGRET, and AGILE. Such a component would be a natural consequence of synchrotron emission from relativistic electrons in an internal shock scenario, but, for example, might be suppressed in Poynting flux dominated models (eg, see Fan & Piran (2008)). Therefore, a systematic analysis of the non-detections of high-energy components in GBM-detected GRBs may significantly help to discriminate between various prompt emission mechanisms. Furthermore, the lack of a detection by the LAT of GBM-detected GRBs with particularly hard spectra points to intrinsic spectral cut-offs and/or curvature at high energies, giving us further insight into the physical properties of the emitting region.

In this paper, we examine the GBM-detected bursts that fell within the LAT field-of-view at the time of trigger during the first 2.5 years of observations which showed no evidence for emission above 100 MeV. We report the photon flux upper limits in the 0.110 GeV band during the prompt emission phase and for 30 s and 100 s integrations starting from the trigger time for each burst. We then compare these upper limits with the fluxes that would be expected from extrapolations of spectral fits presented in the first GBM spectral catalog (Goldstein et al, in press) in order to determine how well measurements of the  MeV properties of GRBs can predict detections at  MeV energies.

We find that roughly half of the GBM detected bursts either require spectral breaks or have intrinsically steeper spectra in order to explain their non-detections by the LAT. We distinguish between these two scenarios by performing joint GBM and LAT spectral fits to a subset of the 30 brightest bursts, as seen by the GBM that were simultaneously in the LAT field of view. We find that while a majority of these bursts have spectra that are softer above the peak of the spectra () than would be inferred from fitting the GBM data alone, a subset of bright bursts have a svstatistically significant high-energy spectral cut-off similar to the spectral break reported for GRB 090926A (Ackermann et al., 2011b). Finally, we use our joint GBM and LAT spectral fits in conjunction with the LAT non-detections at 100 MeV to place limits on the maximum Lorentz factor for these GRBs which show evidence for intrinsic spectral breaks

The paper is structured as follows: In section 2, we review the characteristics of the GBM and LAT instruments, and in section 3, we define the GRB samples considered in this work. In section 4, we describe the analysis we perform to quantify the significance of the LAT non-detections; we present the results in section 5, and discuss the implications they have on our understanding of the properties associated with the prompt gamma-ray emission in section 6.

2 The LAT and GBM Instruments

The Fermi Gamma-ray Space Telescope carries the Gamma-ray Burst Monitor (Meegan et al., 2009a) and the Large Area Telescope (Atwood et al., 2009). The GBM has 14 scintillation detectors that together view the entire unocculted sky. Triggering and localization are performed using 12 sodium iodide (NaI) and 2 bismuth germanate (BGO) detectors with different orientations placed around the spacecraft. The two BGO scintillators are placed on opposite sides of the spacecraft so that at least one detector is in view for any direction on the sky. GBM spectroscopy uses both the NaI and BGO detectors, sensitive between 8 keV and 1 MeV, and 150 keV and 40 MeV, respectively, so that their combination provides an unprecedented 4 decades of energy coverage with which to perform spectroscopic studies of GRBs.

The LAT is a pair conversion telescope comprising a array of silicon strip trackers and cesium iodide (CsI) calorimeters covered by a segmented anti-coincidence detector (ACD) to reject charged-particle background events. The LAT covers the energy range from 20 MeV to more than 300 GeV with a field-of-view of steradians. The dead time per event of the LAT is nominally 26.50 s for most events, although about 10 of the event read outs include more calibration data, which engender longer dead times. This dead time is 4 orders of magnitude shorter than that of EGRET. This is crucial for observations of high-intensity transient events such as GRBs. The LAT triggers on many more background events than celestial gamma rays. Onboard background rejection is supplemented on the ground using event class selections that accommodate the broad range of sources of interest.

3 Sample Definition

We compiled a sample of all GRBs detected by the GBM between the beginning of normal science operations of the Fermi mission on 2008 August 4th up to 2011 January 1st, yielding a total of 620 GRBs. Of these, 288 bursts fell within 65 of the LAT z-axis (or boresight) at the time of GBM trigger, which we define as the LAT FOV. Bursts detected at angles greater than at the time of the GBM trigger were not considered for this analysis, due to the greatly reduced sensitivity of the instrument for such large off-axis angles. A plot of the distribution of the LAT boresight angles at trigger time, , for all 620 bursts is shown in Figure 1. Roughly half (46) of the GBM-detected GRBs fell within the LAT FOV at , as expected given the relative sky coverage of the two instruments. These bursts make up the sample for which the photon flux upper limits described in the next section have been calculated. A complete list of the 288 bursts in the sample, their positions, their durations, and their LAT boresight angles is given in Table 1.

We defined a subsample of 92 bursts which had a rate trigger greater than 75 counts  s in at least one of the two BGO detectors. This criteria is similar to the one adopted by Bissaldi et al. (2011) in their analysis of the brightest GBM detected bursts in the first year of observations. Hereafter, we refer to these 92 bursts as the “bright BGO subsample”; it comprises likely candidates for which it would be possible to find evidence of spectral curvature above the upper boundary of the nominal BGO energy window of  MeV. Finally, we define our so-called “spectroscopic subsample” as the 30 bursts (of the bright BGO subsample) that have sufficient counts at higher energies to allow for the index of a Band function fit to be determined with standard errors . This spectroscopic subsample was used in joint fits with the LAT data to test models containing spectral breaks or cut-offs.

4 Analysis

4.1 LAT Upper Limits

We derive upper limits for the 288 GRBs that were detected by the GBM and fell in the LAT FOV from the LAT data using two methods. The first consists of the standard unbinned likelihood analysis using the software developed and provided by the LAT team, while the second method simply considers the total observed counts within an energy-dependent acceptance cone centered on the GBM burst location. The likelihood analysis will give more constraining upper limits, but since it uses the instrumental point-spread-function (PSF) information to model the spatial distribution of the observed photons, in cases where the burst location is inaccurate and burst photons are present, it can give less reliable constraints. The latter method will be less constraining in general, but it will also be less sensitive to errors in the burst location, as the analysis considers photons collected over a fixed aperture and does not otherwise use the burst or photon positions on the sky. We use both methods to obtain photon flux upper limits over a 0.110 GeV energy range.

For the unbinned likelihood analysis, we used the standard software package provided by the LAT team, (ScienceTools version v9r15p6)111http://fermi.gsfc.nasa.gov/ssc/. We selected “transient” class events in a acceptance cone centered on the burst location, and we fit the data using the pyLikelihood module and the P6_V3_TRANSIENT response functions (Atwood et al., 2009). Each burst is modeled as a point source at the best available location, derived either from an instrument with good localization capabilities (eg Swift or LAT) or by the GBM alone. Of the 288 GRBs considered here, , In the likelihood fitting, the expected distribution of counts is modeled using the energy-dependent LAT PSF and a power-law source spectrum. The photon index of the power-law is fixed to either the value found from the fit of the GBM data for that burst or, if the GBM data are not sufficiently constraining (ie ), to , the mean value found for the population of BATSE-detected bursts (Preece et al., 2000a; Kaneko et al., 2006). An isotropic background component is included in the model, and the spectral properties of this component are derived using an empirical background model (Abdo et al., 2009c) that is a function of the position of the source in the sky and the position and orientation of the spacecraft in orbit. This background model accounts for contributions from both residual charged particle backgrounds and the time-averaged celestial gamma-ray emission.

Since we are considering cases where the burst flux in the LAT band will be weak or zero, the maximum likelihood estimate of the source flux may actually be negative owing to downward statistical fluctuations in the background counts. Because the unbinned likelihood function is based on Poisson probabilities, a prior assumption is imposed that requires the source flux to be non-negative. This is necessary to avoid negative probability densities that may arise for measured counts that are found very close to the GRB point-source location because of the sharpness of the PSF. On average, this means that for half of the cases in the null hypothesis (i.e., zero burst flux), the “best-fit” value of the source flux is zero but does not correspond to a local maximum of the unconstrained likelihood function (Mattox et al., 1996).

Given the prior of the non-negative source flux, we treat the resulting likelihood function as the posterior distribution of the flux parameter. In this case, an upper limit may be obtained by finding the flux value at which the integral of the normalized likelihood corresponds to the chosen confidence level (Amsler et al., 2008). For a fully Bayesian treatment, one would integrate over the full posterior distribution, i.e., marginalize over the other free parameters in the model. However, in practice, we have found it sufficient to treat the profile likelihood function as a one-dimensional probability distribution function (pdf) in the flux parameter. Again, in the limit of Gaussian statistics and a strong source, this method is equivalent to the use of the asymptotic standard error for defining confidence intervals. Hereafter, we will refer to this treatment as the “unbinned likelihood” method.

In the second set of upper limit calculations, we implement the method described by Helene (1983) and the interval calculation implemented in Kraft et al. (1991). Here, the upper limit is computed in terms of the number of counts and is based on the observed and estimated background counts within a prescribed extraction region. For the LAT data, the extraction region is an energy-dependent acceptance cone centered on the burst position. Since the burst locations from the GBM data have typical systematic uncertainties 3.2 (Connaughton et al. 2011), the size of the acceptance cone at a given energy is taken to be the sum in quadrature of the LAT 95% PSF containment angle and the total (statistical + systematic) uncertainty in the burst location. The counts upper limits are evaluated over a number of energy bands, converted to fluxes using the energy-dependent LAT exposure at the burst location, and then summed to obtain the final flux limit. Since this method relies on comparing counts without fitting any spectral shape parameters, we will refer to this as the “counting” method.

The time intervals over which the upper limits are calculated are important for their interpretation. For both upper limit methods, we consider three time intervals: two fixed intervals of 30 and 100 seconds post-trigger, and a “T100” interval that is determined through the use of the Bayesian Blocks algorithm (Jackson et al., 2005) to estimate the duration of burst activity in the NaI detector that has the largest signal above background. For the T100 interval, an estimate of the time-varying background count rate is obtained by fitting a 3rd degree polynomial to the binned data in time intervals outside of the prompt burst phase. Nominally, we take to  s and  s to , where is the GBM trigger time and  s, although we increased the separation of these intervals in some cases to accommodate longer bursts. The counts per bin is then subtracted by the resulting background model throughout the to interval, and the binned reconstruction mode of the Bayesian Blocks algorithm is applied. The T100 interval is then defined by the first and last change points in the Bayesian Blocks reconstruction.

The two fixed time intervals have been introduced so as to not bias our results through assumptions regarding the durations of the high energy components. The brighter LAT-detected GRBs have exhibited both delayed and extended high-energy emission on time scales that exceed the durations traditionally defined by observations in the keVMeV energy range (Abdo et al. 2011). Hence, we search for and place limits on emission over intervals that may in some cases exceed the burst duration. We will discuss the implications of the limits found for the various time intervals in section 5.1.

4.2 GBM Spectroscopy

For the 92 bursts in the bright BGO subsample, we performed spectral fits to the NaI and BGO data and estimated the flux expected to be seen by the LAT between - GeV using the GBM fitted Band function (Band et al., 1993) parameters. The selection of background and source intervals for all bursts were performed manually through the use of the RMFIT (version 3.3) spectral analysis software package222http://fermi.gsfc.nasa.gov/ssc/data/analysis/user/. Because the number of counts in the highest BGO energy bins is often in the Poisson regime, we use the Castor modification (Castor, 1995) to the Cash statistic (Cash, 1976), commonly referred to as C-Stat 333http://heasarc.nasa.gov/xanadu/xspec/manual/manual.html, since the standard statistic is not reliable for low counts. The variable GBM background for each burst is determined for all detectors individually by fitting an energy-dependent, second order polynomial to the data several hundred seconds before and after the prompt GRB emission. The standard 128 energy bin CSPEC data (Meegan et al., 2009b) from the triggered NaI and BGO detectors were then fit from 8 keV to 1 MeV and from 200 keV to 40 MeV, respectively, for each burst.

As we noted above, only 30 bursts in the bright BGO subsample have sufficient signal-to-noise to constrain the high-energy power-law index of the Band function to within . Although we considered a variety of models in our spectral analysis, we found that the Band function was sufficient to describe the spectral shape for all of these bursts.

5 Results

5.1 LAT Upper Limits

Of the 288 GRBs in our sample, we were able to obtain upper limits, at 95% confidence level (CL), for 270 bursts using the unbinned likelihood method and 95% CL upper limits for 250 bursts using the counting method for the T100 intervals derived from the GBM data. The GRBs for which upper limits could not be calculated were bursts that occurred either during spacecraft passages through the South Atlantic Anomaly (SAA) or at angles with respect to the Earth’s zenith that were , thereby resulting in diffuse emission at the burst locations that was dominated by -rays from the Earth’s limb produced by interactions of cosmic rays with the earth’s atmosphere. These cases where the burst occurred at a high angle with respect to the zenith primarily affects the counting method, because it requires a reliable estimate of the background during the burst, and our method to estimate the background does not account for Earth limb emission. The likelihood method can fit for an Earth limb as a diffuse component, but it may give weaker limits since the background level is not as tightly constrained in this case compared to when the empirical background estimate can be used to model all of the non-burst emission. The photon flux upper limits found for the likelihood method for all three time intervals are presented in the last three columns of Table 1.

The distributions of the 95% CL photon flux upper limits obtained via the likelihood and counting methods for the 30 s, 100 s, and T100 time intervals are shown in upper-left, upper-right, and lower-left panels of Figure 2, respectively. As expected, the likelihood limits are systematically deeper than those found using the counting method over the same time interval. For either method, the upper limits for the 100 s integrations are roughly half an order-of-magnitude deeper than for the 30 s integrations. In the photon-limited case, this is expected since the flux limit at a specified confidence level should be inversely proportional to the exposure. The doubly peaked upper limits distribution that appears in the upper-left panel of Figure 2 for the T100 duration reflects the bimodal duration distribution for the short and long GRB populations. The median of the T100 upper limit distribution for the likelihood method is photons cm s with a standard deviation of ; whereas the counting method distribution has a median of photons cm s and . The median of the 30 s upper limits distribution for the likelihood method is photons cm s with a standard deviation of ; whereas the counting method distribution has a median of photons cm s and . The median of the 100 s upper limits distribution for the likelihood method are photons cm s and and photons cm s and for the counting method.

A comparison of the likelihood and counting methods for all three time intervals for is shown in the lower-right panel of Figure 2. The scatter in the upper limits distribution for both methods is largely due to the range of angles at which the GRBs occurred with respect to the LAT boresight, resulting in different effective areas and hence different exposures for each burst. The LAT exposure as a function of the off-axis angle drops steeply with increasing inclination, resulting in a shallowing of the LAT upper limits as a function of increasing off-axis angle, which can be seen in Figure 3. Overall, the two methods give consistent results for the bursts in our sample, and therefore we will hereafter focus primarily on the limits obtained with the likelihood method in our discussion of the implication of these results.

Despite the dependence of the upper limit values on off-axis angle, the distribution of LAT photon flux upper limits is relatively narrow for angles , allowing us to define an effective LAT sensitivity assuming a typical GRB spectrum (i.e., ). We can therefore set sensitivity thresholds for the corresponding median photon flux upper limit for each integration time of  photons cmsand  photons cms.

Finally, in Figure 4 we plot the location of each burst on the sky in Galactic coordinates, color-coded to represent the likelihood-determined photon flux upper limits. There is no evidence of a spatial dependence of the GBM detection rate nor of the magnitude of the LAT upper limit, as a function of Galactic latitude .

5.2 GBM Spectral Fits and Upper Limit Comparisons

We compare the LAT upper limits calculated over the burst duration to the expected 0.110 GeV photon fluxes found through extrapolations of spectral fits presented in the first GBM spectral catalog (Goldstein et al in press). We focus this analysis on bursts for which a Band spectral model was a preferred fit compared to models with fewer degrees of freedom, since alternative models such as Comptonized spectra suffer sharp drops in expected flux at high-energy and are not expected to result in LAT detections without the presence of additional spectral components. Of the 487 GRBs presented in that catalog, a Band model fit was preferred over simpler models for 161 bursts, 75 of which appeared in the LAT field of view. For this comparison, the LAT upper limits were recalculated for a duration that matched the interval used in the GBM spectral catalog (see Goldstein et al. 2011 for a detailed discussion of their interval selection). We next performed a simulation in which we varied the expected LAT photon flux fitted values using the associated errors for each burst in order to determine the median number of bursts over all realizations that would fall above the LAT upper limit. In a total of realizations, we find that 50 of the GRBs in the GBM spectral catalog, which prefer a Band model fit, have expected 0.110 GeV photon fluxes that exceeds the LAT upper limit.

We investigate the differences between the GBM-based extrapolations and the LAT upper-limits further by performing detailed spectral fits to our spectroscopic subsample. The spectral parameters obtained from the fits to the GBM data only for the 30 GRBs in this spectroscopic subsample are listed in Table 2. The median values of the low and high energy power-law indices and the peak of the spectra are , , and keV, with standard deviations of , , and  keV, respectively. The distributions of spectral parameters for these bursts are consistent with similar distributions found for BATSE-detected GRBs (Preece et al., 2000a; Kaneko et al., 2006). The time durations used in the spectral fits and the time-averaged photon flux values in the 0.0220 MeV energy range for these GRBs are given in Table 3. In the third column, we list the expected flux in the 0.110 GeV energy range assuming a power-law extrapolation of the Band function fit to the GBM data; and in the fourth column, we give the measured LAT photon flux upper limit found for the same time interval. The errors on the expected LAT photon fluxes were determined using the covariance matrices obtained from the GBM spectral fits.

A comparison of the LAT photon flux upper limits versus the expected 0.110 GeV photon fluxes for each burst in our spectroscopic subsample is shown as blue data points in Figure 5. The downward arrows on the expected flux values indicate values that are consistent with zero within the 1- errors shown. The dashed line represents the line of equality between the expected LAT photon flux and the LAT photon flux upper limits when calculated for the durations presented in Table 5. In a total of realizations, we find that 53 of GRBs in our spectroscopic subsample have expected 0.110 GeV photon fluxes that exceed their associated 95% CL LAT upper limit. As with the flux comparison, roughly 50 in our sample also have expected fluence values that exceed the 95% CL LAT fluence upper limit. Figure 6 shows that the degree to which the expected flux in the LAT energy range from these bursts exceed our estimated LAT upper limits correlates strongly with the measured high energy spectral index, with particularly hard bursts exceeding the estimated LAT sensitivity by as much as a factor of 100. Again, the spectral fits to the bright bursts detected by the BGO clearly shows that a simple extrapolation from the GBM band to the LAT band systematically over-predicts the observed flux.

5.3 Joint GBM and LAT Spectral Fits

Including the LAT data in the spectral fits drastically alters the best-fit Band model parameters and the resulting expected photon flux in the LAT energy range. The best-fit parameters of the joint spectral fits for the spectroscopic subsample can be found in Table 4. The high-energy spectral indices are typically steeper (softer) than found from fits to the GBM data alone.

The difference in the values for the joint fits with respect to the fits to the GBM data alone can be found in Column 8 of Table 4. The resulting distributions are shown in Figure 7. The GBM-only distribution (red histogram) peaks at , matching the distribution found for the population of BATSE-detected bursts presented in Preece et al. (2000a). In contrast, the distribution found from the joint fits (blue histogram) indicates spectra that are considerably softer, with a median value of . While the GBM-only distribution includes 5 GRBs with , no bursts had values this hard from the joint fits. The low energy power-law index and the peak of the spectra, distribution remain relatively unchanged. In Figure 5, we compare the LAT photon flux upper limits calculated over the burst duration presented in Table 4 versus the expected 0.110 GeV photon fluxes for each burst, now using a power-law extrapolation of the Band function that was fit to both the GBM and LAT data. The softer values obtained through the joint fits yield expected LAT photon flux values that are more consistent with the LAT non-detections, with only 23 of the bursts in our spectroscopic subsample with expected flux values that exceed the 95% CL LAT flux upper limit given realizations of the data about their errors. We find that a similar ratio of bursts have expected fluence values that exceed their associated 95% CL LAT fluence upper limit.

5.4 Spectral Breaks or Softer Spectral Indices?

Although the discrepancy between the predicted 0.110 GeV fluxes from the GBM-only fits and the LAT upper limits can be explained by the softer values in the joint fits, intrinsic spectral breaks at energies  MeV can also reconcile the conflicting GBM and LAT results. Determining whether softer values or spectral breaks are present has at least two important implications: If the spectral breaks or cut-offs arise from intrinsic pair production () in the source, then the break or cut-off energy would provide a direct estimate of the bulk Lorentz factor of the emitting region within the outflow On the other hand, an intrinsically softer distribution of values would mean that theoretical inferences based on the distributions found by fitting BATSE or GBM data alone may need to be revised. Evidence for either spectral breaks or softer values could also provide support for multi-component models that have been used to describe novel spectral features detected by the GBM and LAT (eg, Guiriec et al., 2011a).

For the joint fitting of the GBM and LAT data, deciding between the two possibilities for any single burst can be cast as a standard model selection problem. Under the null hypothesis, we model the GRB spectrum using a simple Band function, as we have done in section 5.3. As an alternative hypothesis, we could extend the Band model to account for the presence of a spectral break. This may be done via an additional break energy above the Band , effectively using a doubly broken power-law in the fit; or it could be accomplished by adding an exponential cut-off to the Band model with cut-off energy . In either case, the null and alternative hypotheses are “nested” such that the former is a special case of the latter for some values of the extra model parameters that are introduced. Assuming there are additional free parameters under the alternative model, then whether the alternative model is statistically preferred would be given by the C-Stat value assuming it follows a distribution for degrees-of-freedom.

For the purposes of this analysis, we have adopted an alternative model consisting of a Band function plus a step function fixed at 50 MeV. Although unphysical, a simple step function introduces a single additional degree-of-freedom and can adequately represent the need for a break in the high-energy spectra. This additional degree-of-freedom represents the normalization of the Band function’s high-energy component above 50 MeV, which is left to vary, leading to the normalization of the power-law above 50 MeV being adjusted such that it is always consistent with the LAT upper limits. For this analysis, the index of the power-law above the break is fixed to match the Band function’s high-energy power-law index, which is allowed to vary as a free parameter. Since this introduces a single extra degree-of-freedom, a value of C-Stat would represent a ¿ improvement in the fit. We adopt this criterion as the threshold for a statistical preference for a break in the high-energy spectrum of an individual GRB.

An example of such a fit can be seen in Figure 8, where the three panels show (clockwise) a Band model fit to GBM data alone, a Band model fit to both the GBM and LAT data, and a Band model plus a step function fit to the GBM and LAT data. The difference between the first two panels demonstrates the degree to which the high-energy spectral index can steepen to accommodate the LAT data, despite being outside of the range allowed by the statistical uncertainty in the determination made through the GBM fit alone. The third panel shows the effect of introducing a step function between the two instruments, in which the requirement for a softer value is alleviated. For the fit shown in Figure 8, the value determined through the Band model plus a step function fit is consistent with the value found by fitting a Band model to the GBM data alone.

The C-Stat values obtained for the Band and Band+step function fits are listed in Column 9 of Table 4. For most of the bursts, a simple steepening of the high energy power-law index was sufficient to explain the lack of a LAT detection. However, in 6 cases C-Stat exceeded a value of 9, indicating a statistical preference for a break in the high energy spectrum. Figure 9 shows the ratio of the expected LAT flux (based on GBM-only fits) to the LAT 95% CL upper limit plotted versus the C-Stat values for the spectroscopic subsample. A weak correlation between the flux ratio and C-Stat is apparent. In addition, Figure 10 shows an anti-correlation between the resulting C-Stat values for this sample plotted versus the uncertainty in the high-energy spectral index found from fits to the GBM data alone. The bursts for which a spectral break is statistically preferred both have the most severe discrepancies between the GBM-only extrapolations and the LAT upper limits and also have the smallest uncertainties in their GBM-only values.

5.5 Constraints on the Bulk Lorentz Factor

If we assume that the high-energy spectra in the 6 GRBs that prefer spectral cut-offs are a result of attenuation, as opposed to a spectral turnover that is intrinsic to the GRB spectrum, then we can use the joint GBM and LAT spectral fits in conjunction with the LAT non-detections at 100 MeV to place limits on the maximum Lorentz factor. In this context, the high-energy -rays produced within the GRB jet may undergo pair production and can be absorbed in situ. The interaction rate of this process and corresponding optical depth, , depend on the target photon density and can be significant when both the high-energy and target photons are produced in the same physical region. Highly relativistic bulk motion of such an emission region can reduce the implied optical depth greatly by allowing for a larger emitting region radius and a smaller target photon density for a given observed flux and variability time scale. Observation of -ray emission up to an energy thus can be used to put a lower limit on the bulk Lorentz factor of the emitting region (Lithwick & Sari, 2001; Razzaque et al., 2004; Granot et al., 2008; Ackermann et al., 2010b). This method is valid for , which follows from the threshold condition for pair production, when both the incident and target photons are at the maximum observed energy.

If a high-energy -ray photon with energy and the observed broadband photon emission originate from the same physical region, and if we assume the photons are quasi-isotropic in the comoving frame, then the pair production optical depth can be written as

(1)

Here is the observed photon spectrum, is the target photon energy, is the target photon energy in the comoving frame of the emitting plasma, is the luminosity distance, is the -ray flux variability time scale, and is the Thomson cross-section. The function is defined by Gould & Schréder (1967) and Brown et al. (1973). The value of follows from the condition . This single-zone model, in which the spatial and temporal dependancies of have been averaged out, has been the technique used to measure the reported values of for the LAT detections of GRBs 080916C, 090510, and 09092B in Abdo et al. (2009d), Ackermann et al. (2010b), and Abdo et al. (2009b), respectively.

A direct estimate of the bulk Lorentz factor , as opposed to a minimum value, of the GRB jet can be made based on evidence of a cut-off in the spectral fits that are attributed to attenuation, such as has been reported for GRB 090926A in Abdo et al. (2010).

In the case of the 6 GRBs that we are considering here for which no direct evidence for a spectral cut-off is otherwise detected, we use our upper limits to calculate a maximum bulk Lorentz factor from the condition . To do so, we use the Band function fit to the GBM and LAT data and set MeV. We also assume a variability time scale of  s, which we believe represents a conservative estimate of given the ubiquity of millisecond variability in BATSE detected GRBs (Walker et al., 2000) as well as the short timescales observed in other LAT detected GRBs (Ackermann et al., 2010b).

We note that if the cutoff energy due to intrinsic pair opacity is small enough, , then the Thomson optical depth of the pairs that are produced in the emitting region is (Lithwick & Sari, 2001; Abdo et al., 2009a). This should affect both the observed spectrum, thermalizing it for a large enough optical depth, and light curve, eliminating short timescale variability. For MeV, this condition is nearly violated at , therefore a much lower cutoff energy would be hard to reconcile with an intrinsic pair opacity origin for GRBs at low redshift.

The resulting and values for previously reported LAT detections and from the upper limits presented here are shown in Figure 13. Since the Lorentz factor calculation depends on the redshift, which is unknown for the majority of GBM detected bursts, we have plotted the values as a function of the redshift (red lines). One GRB in our spectroscopic subsample, GRB 091127, has a measured redshift which allows us to constrain the burst’s value. Using a redshift of (Cucchiara et al., 2009) and MeV, we calculate a relatively small bulk Lorentz factor of . Using the measurements of for these GRBs provides a relatively narrow distribution of that range from at to at . These values stand in stark contrast to the LAT detected GRBs for which was measured, all of which have .

The detection of spectral curvature by the LAT in the spectrum of GRB 090926 provides a case that appears to bridge the LAT detected and non-detected samples. The estimate of of 200700 presented in Abdo et al. (2010) reflects the systematic differences between Lorentz factors obtained through the use of time-dependent models by Granot et al. (2008) which yield systematic differences in and the inferred when compared to the simple single-zone model used above. Granot et al. (2008), and more recently Hascoët et al. (2011), have shown that such time-dependent models, which include the temporal evolution of during the emission period, can yield inferred estimates that are reduced by a factor of 2-3 compared to estimates made using single-zone models. In the context of these time-dependent model, the and presented in Figure 13 would all be systematically overestimated by a factor of 2-3, but the dichotomy between the LAT detected and LAT non-detected GRBs would persist since all estimates would be effected by the same correction.

Note that the grey dashed line in Figure 13 demarcates the self-consistency line where the condition that is violated, implying an incorrect determination of , for the bursts with no detected emission above MeV. None of the bursts in our spectroscopic subsample violate this condition at any redshift for the choice of MeV.

6 Discussion

The upper limits presented above place stringent constraints on the high energy emission from GRBs detected by the GBM. Of the 620 bursts detected by the GBM from 2008 August 4th to 2011 January 1st, 46% were within the LAT FOV. There is evidence for high energy emission MeV in the LAT energy range for 23 GRBs, representing 8% of the entire GBM sample observed by the LAT. This is significantly less than the pre-launch estimate of 1 detection per month that produces at least 100 counts above 100 MeV (Band et al., 2009).

The results of our joint GBM and LAT spectral fits show that both softer high-energy power-law spectra and spectral breaks likely account for the lower-than-expected number of LAT-detected GRBs. For the 24 bursts in our spectroscopic subsample where a spectral break is not statistically justified, the values from the joint fits are systematically softer than the values found from fitting the GBM data alone. This may indicate that the high-energy spectral index for the Band model may in fact be softer than that deduced from measurements made by previous missions, such as BATSE, which had a much narrower energy range compared to the combined coverage of the GBM and LAT. The GBM+LAT distribution shown in Figure 7 appears to exclude the harder spectra found from fits made with just the lower energy BATSE or GBM data. In fact, we find no cases of spectra with , which would otherwise result in a divergent energy flux at high energies.

The detection of softer values also provides support for continuum models with multiple components, which have been used to describe novel spectral features detected by the GBM and LAT. Recent work on bright GRBs by Guiriec et al. (2011a) suggests that although the Band function represents many GRB spectra very well in a limited energy range, it is sometimes possible to discern, even in this limited energy range, contributions such as thermal components in addition to the presumably non-thermal synchrotron emission represented by the Band function. The addition of such components to a Band function has the effect of modifying the parameter values, in the case of GRB 100724B raising and softening (Guiriec et al., 2011b). Whilst these more complex models are not statistically favored in most GRBs due to low photon statistics, their successful fits to some GRBs indicate that the representation of GRB emission by a Band function may be inadequate and lead to overestimates of fluxes when extrapolated to GeV energies. Because the Band function was developed to represent GRB spectra rather than to parametrize a physical model, it is difficult to decouple physical components from this empirical function, which probably incompletely describes elements of multiple physical phenomena. Additionally, the superposition of Band functions does not necessarily produce a Band function, so the presence of spectral evolution means that any extrapolation to higher energies from flux-averaged spectra may not be representative of the emission throughout the entire GRB emission period.

Granot et al. (2008) have shown that even when integrating over a single spike in a light curve there is a steepening to a softer power-law rather than an exponential cutoff. This is due to the high-energy power law arising from the sum of instantaneous spectra with an exponential cutoff whose break energy evolves with time. Likewise, Hascoët et al. (2011) have shown that the effect of averaging a time variable opacity cutoff would be manifested as a steepening in the power-law index of the high-energy spectral slope rather than as a sharp cutoff in the spectrum. Likewise, Baring (2006) has shown that skin-depth effects tend to smear out exponential attenuation when the source and target photons originate in the same volume, resulting in a similar effect. Such considerations could explain the softer values found when fitting both the GBM and LAT data, even in cases where a spectral break was not statistically preferred. Detailed time resolved spectroscopy of bright GBM detected GRBs should be able to discriminate between such pair opacity effects, intrinsically steeper high-energy spectra, or the more complex continuum models discussed above (Guiriec et al., 2011b).

The bursts in our spectroscopic subsample were chosen specifically because they were among the brightest bursts detected by the BGO and yet had no appreciable signal in the LAT. This makes them good candidates to examine for evidence of spectral breaks, but they may also form a biased data set. In order to understand how representative these bursts are of the general GRB population, we plot in Figure 11 the distribution of the time averaged photon flux as determined from fits to GBM data for bursts in our spectroscopic subsample (red), the bursts which appear in the first GBM spectral catalog (gold) the bursts in the bright BATSE catalog presented in Kaneko et al. (2006) (green), and a sample of simulated BATSE bursts (blue) using the spectral parameter distributions given in Preece et al. (2000b). The resulting distributions show that the spectroscopic subsample is consistent with being drawn from the distribution of the brightest bursts detected by BATSE.

We extend this analysis in Figure 12, where we plot the expected 0.110  GeV LAT photon flux versus the 202000 keV photon flux for our spectroscopic sample using spectral parameters from the GBM-only fits (green) and from the joint GBM-LAT fits (red), along with the bursts from the first GBM spectral catalog which were in the LAT FOV (blue). The color gradient in the GBM sample represents the burst’s duration, with darker (blue) symbols representing shorter duration bursts. In addition, we have plotted the 6 LAT-detected bursts (gold) that had spectra that could be fit with a single Band function (i.e., we excluded bursts with extra high-energy components). The dashed line represents the median T100 upper limit. The green data points demonstrate how fits to the GBM data without the inclusion of the LAT data yield spectral parameters that over-predict the flux in the LAT energy range, which can be seen by the number of bursts in our spectroscopic subsample that fall above the median upper limit values. The red data points represent the predicted LAT flux for the same GRBs using spectral parameters determined through fits to both the GBM and LAT data. Roughly 50% of the bursts from the GBM spectral catalog fall above the median T100 upper limit. This would imply that a large fraction of bright GBM detected bursts would have been detectable by the LAT assuming a direct extrapolation of their high-energy spectra. Therefore, we conclude that intrinsic spectral breaks and/or softer-than-measured high-energy spectra must be fairly common in the GRB population in order to explain the lack of LAT-detected GRBs.

Despite the unknown distances to all but one of the GRBs in our spectroscopic subsample, the allowed range of values for all lie well below. This range of for the relativistic outflow contrasts with the minimum Lorentz factors that have been calculated for the bright, LAT-detected GRBs using their highest detected photons. For GRB 080916C, GRB 090510, and GRB 09092B, the estimated lower limits for the Lorentz factors were found to be 887, 1200, and 867 when using single zone models, respectively. Therefore, measurements of and from both LAT detections and non-detections reveal a wide distribution in the bulk Lorentz factor of GRB outflows, with a potential range of over .

As discussed above, these estimates of and have been calculated using simple single-zone models, which may provide overestimated values compared to time-dependent multi-zone models that take into account the time variability of . In such a scenario, our estimates of the and would need to be rescaled downwards by a factor of 23, but the large difference between the LAT detected and non-detected GRBs would remain.

The Fermi LAT Collaboration acknowledges generous ongoing support from a number of agencies and institutes that have supported both the development and the operation of the LAT as well as scientific data analysis. These include the National Aeronautics and Space Administration and the Department of Energy in the United States, the Commissariat à l’Energie Atomique and the Centre National de la Recherche Scientifique / Institut National de Physique Nucléaire et de Physique des Particules in France, the Agenzia Spaziale Italiana and the Istituto Nazionale di Fisica Nucleare in Italy, the Ministry of Education, Culture, Sports, Science and Technology (MEXT), high-energy Accelerator Research Organization (KEK) and Japan Aerospace Exploration Agency (JAXA) in Japan, and the K. A. Wallenberg Foundation, the Swedish Research Council and the Swedish National Space Board in Sweden. Additional support for science analysis during the operations phase is gratefully acknowledged from the Istituto Nazionale di Astrofisica in Italy and the Centre National d’Études Spatiales in France. The Fermi GBM collaboration acknowledges support for GBM development, operations and data analysis from NASA in the US and BMWi/DLR in Germany.
Figure 1: The distribution of LAT off-axis angles of the 620 bursts that triggered the GBM from 2008 August 4th to 2011 January 1st. The red dashed line at an off-axis angle of indicates the nominal boundary of the LAT FOV. A total of 288 bursts (46% of all detected bursts) fell within the LAT FOV over this period.
Figure 2: The distributions of the 95% CL photon flux upper limits obtained via the likelihood and counting methods for the 30 s (upper-left), 100 s (upper-right), and T100 (lower-left) time intervals. A scatter plot comparison of the upper limits calculated over the three intervals is shown in the lower-right panel. The dashed line represents the line of equality between the likelihood and counting methods.
Figure 3: The 95% CL photon flux upper limits determined using the likelihood and counting methods as a function of off-axis angle. The decreasing exposure as a function of off-axis angle results in the shallowing of the LAT upper limits for bursts occurring away from the LAT bore sight.
Figure 4: The celestial distribution of 288 gamma-ray bursts as detected by Fermi-GBM in the first 2.5 years of LAT operations that fell in the LAT FOV, plotted in Galactic coordinates. The colors represents the 95% CL LAT photon flux upper limits.
Figure 5: The expected photon flux, based on fits to the prompt GBM spectrum and duration plotted versus the LAT flux upper limit for each burst. When fitting only to the GBM data, roughly 50 of the bursts in the spectroscopic sample have expected LAT fluxes that exceed the LAT 95% CL flux upper limit. When fitting both the GBM and LAT data, only 23% of our sample have expected flux values that exceed the 95% CL LAT flux upper limit. The dashed line represents the line of equality.
Figure 6: The ratio of the expected LAT flux, based on fits to the prompt GBM spectrum, to the LAT 95% CL LAT flux upper limit plotted versus the GBM determined high-energy spectral index. The degree to which the expected flux in the LAT energy range from these bursts exceed our estimated LAT upper limits correlates strongly with the measured high-energy spectral index.
Figure 7: A comparison between the high-energy spectral indices measured through spectral fits to the GBM data alone and joint fits to both the GBM and LAT data. The GBM-only distribution has a median value of , matching the distribution found by (Preece et al., 2000a; Kaneko et al., 2006). In contrast, the distribution found from the joint fits indicate spectra that are considerably softer, with a median value of .
Figure 8: Example spectral fits showing (clockwise) a Band model fit to GBM data alone, a Band model fit to both the GBM and LAT data, and a Band model plus a step function fit to the GBM and LAT data.
Figure 9: The ratio of the expected LAT flux (based on GBM-only fits) to the LAT 95% CL upper limit versus the C-Stat values for our spectroscopic subsample. The long and short dashed lines represents the line of equality between the LAT upper limits and the expected LAT flux and the C-Stat value representing a fit improvement respectively. The bursts for which a spectral break is statistically preferred have the most severe discrepancies between the GBM-only extrapolations and the LAT upper limits.
Figure 10: The symmetric uncertainty in the high-energy spectral index found from fits to the GBM data alone versus the C-Stat values for our spectroscopic subsample. The bursts for which a spectral break is statistically preferred also have the smallest uncertainties in their GBM-only values.
Figure 11: The normalized distribution of the time integrated photon flux as determined through our fits to GBM data for the spectroscopic subsample (red), the bursts in the bright BATSE catalog presented in Kaneko et al. (2006) (green), the bursts that appear in the first GBM spectral catalog (gold), and a sample of simulated BATSE bursts (blue) using the spectral parameter distributions given in Preece et al. (2000b). The resulting distributions show that our spectroscopic subsample is consistent with being drawn from the distribution of the brightest bursts detected by the GBM and BATSE.
Figure 12: Band function model fluxes in the 0.110 GeV energy range versus the 0.022 MeV energy range for various measure and simulated data. The gold stars represent the 6 Fermi bursts that were detected by the LAT during the first 18 months that can be well fit by a Band function model; the green circles represent spectral fits to GBM data for the 30 bright BGO bursts in our spectroscopic subsample; the red circles represent spectral fits to GBM and LAT data for the same 30 GRBs; and the blue circles represent bursts that appear in the first GBM spectral catalog for which a Band spectral model could be fit. The color gradient in the GBM sample represents the burst’s T90 duration.
Figure 13: The values for the 6 GRBs in our sample with evidence for spectral breaks compared to the values for the brightest LAT-detected GRBs. The allowed range of values for all lie well below the values of the LAT-detected GRBs. The estimate for GRB 090926A from Abdo et al. (2010) is shown as the filled blue circle. The grey dashed line demarcates the self-consistency line where the condition that is violated. The range of Lorentz factors obtained through the use of single-zone and time-dependent models places GRB 090926A between the LAT detected and LAT dark GRBs.
GRB METMission elapsed time relative to January 1, 2001, 0h:0m:0s UTC RA Dec Error AngleOff-axis angle with respect to the LAT boresight T100 F F F
Index  s          s ( photons cm s)
080804972 239584816 328.70 -53.20 0.0 56.4 22.0 7.1 5.3 1.7
080805496 239630032 322.70 47.90 5.6 13.0 28.0 - 2.3 0.8
080806896 239750976 241.80 46.70 2.9 59.6 44.0 8.4 12.4 4.0
080808565 239895232 33.60 5.40 2.6 57.9 18.0 10.5 8.1 2.3
080808772 239913104 96.70 -14.40 12.3 17.0 1.0 65.5 2.3 1.4
080810549 240066608 356.80 0.32 0.0 60.8 53.0 4.0 6.9 2.3
080816503 240581056 156.20 42.60 2.0 59.1 68.0 2.7 6.0 2.9
080824909 241307328 122.40 -2.80 1.0 18.1 10.0 7.6 4.6 1.9
080825593 241366432 232.20 -4.90 1.0 60.0 35.0 31.5 34.0 12.6
080830368 241779024 160.10 30.80 2.5 23.5 47.0 1.9 2.4 1.2
080904886 242255760 214.20 -30.30 2.1 21.8 18.0 4.2 3.3 0.9
080905499 242308736 287.70 -18.90 0.0 27.9 1.0 71.1 6.3 2.2
080906212 242370320 182.80 -6.40 1.3 34.9 3.0 60.7 3.9 1.6
080912360 242901536 25.80 -7.20 7.1 57.8 8.0 24.0 5.8 2.1
080916009 243216768 119.80 -56.60 0.0 48.8 86.0 76.7 171.8 68.6
080920268 243584752 121.60 8.90 5.4 21.0 1.0 79.9 4.9 1.2
080924766 243973360 72.80 32.50 4.4 60.1 17.0 12.0 6.2 2.1
080925775 244060560 96.10 18.20 1.2 38.0 33.0 6.0 6.6 2.7
080928628 244307104 95.10 -55.20 0.0 39.4 12.0 7.4 3.0 1.0
081003644 244740432 259.10 35.40 6.9 62.7 147.0 10.6 11.3 6.9
081006604 244996176 142.00 -67.40 8.0 16.0 144.0 1.2 3.4 0.9
081006872 245019344 172.20 -61.00 8.7 16.0 1.0 71.1 3.8 1.5
081008832 245188688 280.00 -57.40 0.0 64.2 126.0 6.2 9.6 5.9
081012549 245509824 30.20 -17.60 0.0 61.5 7.0 31.9 6.6 1.7
081024891 246576160 322.90 21.20 0.0 18.6 134.0 1.0 8.8 2.6
081101491 247232800 95.10 -0.10 0.0 29.9 1.0 71.9 3.5 1.1
081102365 247308304 225.30 22.00 8.6 61.0 147.0 2.2 6.7 2.0
081102739 247340656 331.20 53.00 0.0 50.9 41.0 3.3 4.6 2.3
081107321 247736528 51.00 17.10 3.5 52.0 3.0 60.1 4.9 2.0
081115891 248476944 190.60 63.30 15.1 53.0 1.0 131.4 4.7 2.5
081118876 248734848 54.60 -43.30 3.6 34.1 23.0 3.4 2.6 1.1
081122520 249049696 339.10 40.00 1.0 19.2 25.0 6.1 4.7 1.0
081122614 249057808 151.40 -2.10 11.2 52.0 1.0 120.7 4.2 1.2
081126899 249428048 323.50 48.70 0.0 17.5 8.0 10.2 4.0 2.8
081204004 250041920 63.30 -62.60 4.8 57.0 3.0 77.2 5.5 2.7
081207680 250359520 112.40 70.50 1.2 60.2 101.0 8.2 11.0 5.1
081213173 250834176 12.90 -33.90 13.2 55.0 1.0 145.8 6.2 2.1
081217983 251249696 116.80 26.80 2.0 53.5 24.0 7.6 6.2 1.9
081222204 251614448 22.70 -34.10 0.0 50.0 45.0 5.9 9.2 2.7
081223419 251719440 112.50 33.20 3.8 30.0 3.0 37.6 4.5 1.1
081224887 251846272 201.70 75.10 1.0 17.9 35.0 4.7 5.1 2.3
081225257 251878160 234.10 -64.60 6.9 46.4 15.0 21.3 10.6 5.3
081226156 251955888 193.00 26.80 2.4 51.8 11.0 13.3 4.7 1.6
081226509 251986384 25.50 -47.40 0.0 22.5 1.0 75.3 2.8 1.2
081229187 252217744 172.60 56.90 8.8 44.0 1.0 86.6 2.9 0.9
081230871 252363216 207.60 -17.30 7.7 23.0 1.0 69.6 2.4 0.9
081231140 252386464 208.60 -35.80 1.0 23.3 36.0 2.1 2.5 0.8
090112332 253439840 110.90 -30.40 1.0 4.1 52.0 1.6 3.1 1.1
090113778 253564848 32.10 33.40 0.0 31.2 9.0 9.2 4.2 1.1
090117335 253872128 227.30 -41.50 4.8 63.6 3.0 117.9 9.7 3.5
090117632 253897840 121.60 -38.80 1.9 57.7 27.0 6.0 5.3 1.7
090117640 253898528 164.00 -58.20 0.0 50.9 148.0 3.7 6.8 3.4
090126227 254640384 189.20 34.10 3.6 19.0 7.0 11.0 2.5 1.3
090129880 254956032 269.00 -32.80 0.0 24.4 16.0 7.1 3.5 1.0
090131090 255060560 352.30 21.20 1.0 42.2 55.0 2.4 3.0 1.2
090202347 255255568 274.30 -2.00 2.6 57.0 15.0 12.1 6.0 2.0
090207777 255724752 252.70 34.90 3.8 46.9 14.0 9.6 5.0 1.5
090213236 256196368 330.60 -55.00 3.1 19.2 1.0 67.8 4.7 1.5
090217206 256539408 204.90 -8.40 0.0 34.5 37.0 15.4 19.1 6.9
090227310 257412352 3.30 -43.00 1.2 21.3 15.0 6.2 4.0 2.5
090228204 257489600 106.80 -24.30 1.0 16.0 1.0 68.2 2.5 0.7
090228976 257556304 357.60 36.70 3.3 21.2 5.0 16.8 2.5 1.1
090301315 257585616 352.80 9.50 5.0 54.0 4.0 43.2 4.9 1.5
090303542 257778032 223.70 -68.20 12.1 26.0 1.0 63.2 2.5 1.4
090304216 257836256 195.90 -73.40 12.3 42.0 1.0 94.7 3.3 1.9
090305052 257908480 135.00 74.30 5.4 37.0 2.0 81.5 3.0 1.9
090306245 258011520 137.00 57.00 4.1 17.0 20.0 3.5 2.5 1.0
090308734 258226592 21.90 -54.30 4.8 50.0 1.0 111.2 8.0 2.2
090309767 258315904 174.30 -49.50 3.6 36.1 16.0 7.4 3.6 1.0
090319622 259167344 283.30 -8.90 2.6 17.9 37.0 2.4 3.0 0.9
090320045 259203920 108.30 -43.30 17.9 40.0 1.0 84.8 3.8 1.3
090320418 259236112 238.00 -46.50 12.0 61.0 1.0 194.8 17.3 5.9
090323002 259459360 190.70 17.10 0.0 57.2 144.0 6.9 14.8 9.1
090328401 259925808 90.90 -42.00 0.0 64.5 85.0 13.1 17.0 11.0
090330279 260088144 160.20 -8.20 2.1 51.4 27.0 6.3 5.7 2.1
090331681 260209216 210.50 3.10 9.3 41.0 1.0 83.9 3.1 1.4
090403314 260436768 67.10 47.20 9.7 42.1 14.0 7.6 5.0 1.8
090411838 261173200 156.00 -68.90 2.1 60.3 17.0 17.9 12.5 5.2
090413122 261284160 266.50 -9.20 5.5 50.8 12.0 23.7 7.4 2.1
090418816 261776128 262.80 -28.20 14.4 57.9 1.0 165.2 11.4 2.7
090419997 261878112 88.60 31.30 3.6 55.8 87.0 2.4 5.6 2.1
090422150 262064112 294.70 40.40 0.0 29.2 1.0 76.3 3.8 1.1
090426066 262402544 17.60 -19.20 18.1 56.0 1.0 149.8 5.2 1.8
090427644 262538816 210.00 -45.70 11.8 14.0 1.0 96.8 4.7 1.0
090429753 262721040 124.40 7.90 5.0 32.0 2.0 73.2 2.5 1.5
090510016 263607776 333.60 -26.60 0.0 13.6 1.0 1626.0 143.3 43.7
090514006 263952528 12.30 -10.90 4.6 17.0 44.0 2.3 2.3 1.2
090516137 264136640 122.20 -71.62 2.6 47.8 147.0 1.7 5.7 1.8
090516353 264155280 138.26 -11.85 0.0 19.3 85.0 1.3 2.7 1.1
090518080 264304480 119.95 0.75 0.0 36.8 1.0 78.3 3.2 1.4
090519462 264423936 119.00 -46.30 7.2 31.0 2.0 77.7 3.0 2.5
090519881 264460128 142.30 0.20 0.0 47.5 18.0 6.2 3.7 1.5
090520832 264542272 332.00 43.20 12.0 10.0 1.0 61.1 2.8 0.9
090522344 264672944 277.70 19.60 4.9 55.1 3.0 70.8 4.5 -
090524346 264845872 327.30 -66.90 1.5 62.3 55.0 4.2 8.5 2.4
090529310 265274784 231.20 32.20 7.2 39.0 147.0 1.0 3.2 1.0
090531775 265487760 252.06 -36.05 0.0 21.9 2.0 101.3 5.7 1.8
090612619 266511056 81.03 17.71 2.2 54.1 6.0 33.6 6.1 2.6
090617208 266907600 78.89 15.65 4.2 45.0 2.0 113.5 3.5 1.0
090620400 267183392 237.35 61.15 1.0 56.0 21.0 14.4 9.9 3.6
090621185 267251200 11.02 61.94 0.0 10.9 48.0 1.8 3.3 1.0
090621417 267271248 257.49 -28.46 3.2 52.6 36.0 4.1 5.1 1.4
090623913 267486864 41.70 1.80 1.5 36.8 7.0 11.7 2.6 1.3
090625234 267601024 20.29 -6.43 3.1 13.8 13.0 5.3 2.6 0.7
090626189 267683536 169.30 -36.05 1.0 18.3 79.0 3.7 3.3 4.2
090629543 267973280 8.48 17.67 7.4 40.0 1.0 96.8 3.6 1.7
090701225 268118640 114.69 -42.07 4.2 12.0 1.0 65.5 2.5 1.7
090703329 268300448 3.30 6.90 6.6 22.0 5.0 26.1 4.1 1.4
090704783 268426016 312.97 20.43 16.5 34.5 16.0 5.3 2.8 1.2
090706283 268555648 205.07 -47.07 3.0 20.8 86.0 1.5 3.4 1.3
090708152 268717088 154.63 26.64 0.1 54.7 9.0 18.3 5.2 3.2
090709630 268844864 93.59 64.08 0.1 46.9 30.0 7.0 7.0 2.4
090711850 269036608 139.61 -64.74 1.0 12.7 46.0 1.6 2.3 1.5
090712160 269063456 70.10 22.52 0.0 33.4 150.0 1.6 5.3 1.6
090713020 269137760 284.80 -3.33 2.4 59.0 51.0 4.7 8.0 4.2
090717111 269491232 246.95 22.97 3.9 35.1 1.0 84.6 5.2 1.4
090718720 269630208 243.76 -6.68 5.9 35.7 147.0 2.4 6.6 2.2
090720710 269802176 203.00 -54.80 2.9 56.0 8.0 40.5 9.7 4.6
090722447 269952224 344.13 -62.00 31.9 1.3 154.0 1.5 4.6 1.7
090726218 270278048 238.70 32.50 6.9 52.8 8.0 - - -
090807832 271367872 326.90 7.23 2.6 45.0 158.0 1.6 4.8 2.0
090811696 271701728 277.05 22.22 7.5 36.7 2.0 118.8 6.4 2.1
090813174 271829440 225.80 88.60 0.0 35.3 8.0 11.1 3.9 1.4
090814368 271932576 335.90 60.30 5.9 59.0 1.0 166.6 6.2 2.3
090815946 272068896 251.30 52.90 2.4 47.5 1.0 102.0 3.5 1.6
090819607 272385280 49.10 -67.10 3.3 47.0 1.0 103.9 5.9 2.4
090820509 272463200 321.00 -4.30 10.5 44.2 12.0 8.5 3.1 1.2
090826068 272943456 140.62 -0.11 9.7 27.1 8.0 11.6 2.8 1.1
090829672 273254848 329.20 -34.20 1.0 48.4 92.0 1.8 5.9 1.6
090829702 273257440 355.00 -9.40 3.2 42.0 24.0 5.3 5.5 2.1
090902462 273582304 264.94 27.32 0.0 50.8 30.0 265.2 265.3 84.6
090907808 274044224 81.10 20.50 3.7 32.0 1.0 - 3.1 0.9
090909854 274220992 54.18 -25.03 8.3 53.0 1.0 128.5 5.4 2.8
090917661 274895488 222.60 -19.80 7.4 37.9 3.0 40.7 3.8 1.6
090922539 275316992 13.10 74.00 1.0 20.0 146.0 1.2 3.4 1.3
090924625 275497184 50.80 -68.80 6.7 55.0 1.0 146.6 4.8 1.6
090926181 275631616 353.40 -66.32 0.0 48.1 30.0 274.7 274.8 99.9
091002685 276193568 41.00 -13.10 3.8 15.9 3.0 32.2 2.3 1.2
091003191 276237344 251.52 36.62 0.0 12.2 38.0 11.7 11.1 6.9
091010113 276835392 298.67 -22.54 0.1 55.7 15.0 18.7 9.1 3.2
091017985 277515552 204.80 -62.60 3.6 13.6 1.0 64.1 2.8 1.3
091019750 277668032 226.03 80.33 12.8 56.0 1.0 145.0 8.3 2.2
091020977 277773984 187.80 -13.40 2.2 44.9 38.0 7.4 9.5 4.2
091024380 278068000 339.25 56.89 0.0 15.5 36.0 2.0 2.5 1.0
091030613 278606592 249.00 23.54 5.6 47.9 148.0 1.8 4.5 2.6
091031500 278683232 71.70 -57.50 0.0 24.0 43.0 3.7 5.5 4.3
091103912 278978048 170.70 11.34 1.8 59.0 20.0 9.1 7.8 2.9
091107635 279299648 188.69 32.65 9.0 47.0 2.0 109.1 5.7 2.2
091109895 279494912 247.72 42.31 4.1 21.0 26.0 4.1 3.5 1.2
091115177 279951296 279.37 68.04 6.0 51.1 9.0 18.9 - 1.6
091120191 280384480 226.81 -21.79 0.5 46.0 53.0 4.2 6.9 2.4
091122163 280554848 91.28 6.02 17.7 56.0 1.0 146.0 6.8 3.4
091126389 280920000 48.72 28.26 12.6 57.0 1.0 167.7 11.1 2.6
091127976 281057152 36.60 -19.00 0.0 25.3 14.0 7.4 3.3 1.1
091202072 281411040 255.32 1.44 9.9 34.0 14.0 6.0 2.7 1.4
091207333 281865600 12.04 -48.42 1.7 36.3 146.0 1.1 3.1 1.2
091208410 281958592 29.40 16.90 0.0 55.6 16.0 25.3 17.8 4.7
091219462 282913472 294.49 71.91 5.4 36.0 1.0 78.6 3.4 0.8
091220442 282998208 167.76 3.92 1.5 60.1 23.0 12.3 9.0 2.1
091221870 283121568 55.80 23.20 0.0 53.4 34.0 5.8 6.6 1.5
091223191 283235712 203.23 76.35 8.9 33.0 1.0 77.6 2.7 1.0
091230260 283846464 101.53 0.68 18.0 59.0 1.0 149.9 5.2 1.7
091231206 283928192 197.09 -55.95 1.5 32.2 146.0 2.3 6.4 2.4
100101028 283999200 307.32 -27.00 17.4 31.0 1.0 85.8 4.4 1.7
100101988 284082144 70.66 18.69 9.3 47.0 1.0 102.0 4.0 1.2
100107074 284521600 6.31 -21.24 6.0 53.0 111.0 1.6 5.9 1.4
100111176 284875968 247.00 15.60 0.0 32.2 8.0 11.5 3.3 0.9
100112418 284983264 242.16 -77.54 14.0 57.0 25.0 8.2 6.5 3.4
100116897 285370272 305.00 14.50 0.0 26.5 108.0 1.2 4.1 1.5
100122616 285864448 79.20 -2.71 1.3 49.2 29.0 3.9 3.8 1.1
100130729 286565376 21.19 -24.75 2.5 48.0 92.0 1.3 4.0 1.2
100131730 286651872 120.39 16.49 1.2 27.0 11.0 10.3 5.8 2.3
100201588 286725984 133.10 -37.29 4.3 45.1 147.0 1.2 4.4 1.6
100204024 286936448 50.78 -47.89 3.0 55.1 30.0 6.6 6.6 1.7
100206563 287155808 47.16 13.16 0.0 44.7 2.0 100.5 3.5 1.5
100207721 287255904 321.78 -15.78 1.0 15.0 1.0 167.9 6.6 1.8
100208386 287313344 260.25 27.53 29.3 55.0 1.0 147.8 8.1 2.3
100210101 287461504 244.38 16.08 6.1 64.0 6.0 57.0 13.7 3.4
100212550 287673120 134.27 32.22 1.4 8.0 4.0 20.5 2.7 1.3
100212588 287676448 1.82 45.96 5.0 21.6 3.0 33.3 2.3 0.8
100218194 288160736 206.64 -11.94 2.2 37.5 147.0 1.0 4.9 1.3
100221368 288435040 27.12 -17.41 8.0 60.0 12.0 - - -
100225115 288758720 310.30 -59.40 0.9 58.2 12.0 27.7 13.9 4.5
100225580 288798944 314.27 0.21 1.1 55.1 8.0 33.1 11.4 3.6
100225703 288809536 147.91 34.01 3.9 49.9 12.0 15.2 5.9 3.3
100227067 288927392 0.00 0.00 0.0 35.6 0.0 0.8 2.7 0.8
100228873 289083456 117.99 18.63 11.1 55.0 4.0 49.1 6.9 3.4
100301068 289100256 110.14 -15.68 7.3 42.9 1.0 125.8 3.4 1.4
100301223 289113696 201.85 19.83 4.9 56.0 9.0 18.4 7.9 2.3
100313288 290156064 172.71 -52.58 2.9 59.1 7.0 27.8 5.8 2.7
100313509 290175136 186.37 11.72 9.6 43.8 28.0 3.6 3.3 1.3
100315361 290335168 208.90 30.14 5.5 7.0 1.0 62.2 2.2 0.8
100325246 291189280 209.14 -79.10 7.2 12.1 7.0 21.4 4.1 1.4
100325275 291191776 330.24 -26.47 0.9 9.1 8.0 18.8 6.2 2.1
100327405 291375808 334.93 -5.83 14.2 20.0 20.0 3.5 2.3 0.7
100328141 291439360 155.94 47.03 4.8 58.0 1.0 166.2 15.2 4.4
100330856 291673984 326.38 -6.97 7.7 21.0 24.0 3.0 2.4 0.8
100401297 291798464 281.85 -27.83 9.0 27.0 82.0 1.5 4.0 1.4
100414097 292904416 192.11 8.69 0.0 60.7 147.0 18.6 65.3 20.2
100417166 293169600 261.31 50.38 9.2 15.0 1.0 65.4 2.3 0.9
100420008 293415136 120.55 -5.82 2.8 58.7 25.0 10.3 8.6 2.9
100423244 293694688 119.67 5.78 1.5 40.3 13.0 7.6 6.0 2.0
100424876 293835712 7.79 43.35 2.4 53.5 27.0 7.0 6.3 1.7
100427356 294049920 89.17 -3.46 0.4 28.6 11.0 7.0 4.8 1.9
100429999 294278400 89.09 -69.96 4.0 41.0 9.0 10.6 2.9 -
100503554 294585472 147.48 3.96 1.5 61.6 135.0 2.4 8.0 3.2
100507577 294933088 2.90 -79.01 2.5 64.0 25.0 21.2 23.3 11.3
100511035 295231808 109.29 -4.65 1.0 43.6 41.0 2.6 3.6 1.1
100516014 295662016 117.32 55.14 5.3 19.0 1.0 66.7 2.5 1.1
100517132 295758592 40.63 -44.32 5.2 25.0 12.0 6.2 2.3 0.9
100519204 295937600 191.49 57.41 1.0 60.3 85.0 4.5 12.3 3.7
100527795 296679872 226.83 19.78 1.9 53.9 50.0 2.8 4.6 3.0
100528075 296704096 311.12 27.81 0.1 49.7 149.0 0.9 3.9 1.3
100604287 297327232 248.30 -73.19 3.6 52.0 13.0 13.4 5.6 1.9
100605774 297455712 273.43 -67.60 7.7 18.0 1.0 66.9 2.4 0.9
100608382 297681024 30.54 20.45 5.3 39.0 5.0 20.3 3.7 1.5
100614498 298209440 224.76 40.87 3.0 53.1 1.0 131.8 4.6 1.8
100620119 298695104 80.10 -51.68 1.5 20.1 21.0 7.0 4.8 1.5
100621529 298816928 160.86 14.72 11.4 64.0 1.0 286.7 10.7 3.0
100625891 299193760 338.26 20.29 4.4 30.8 9.0 8.8 2.5 1.0
100704149 299907296 133.64 -24.22 0.0 63.2 19.0 12.9 10.0 3.7
100715477 300886048 299.27 -54.71 9.3 42.0 14.0 7.0 3.1 1.6
100717446 301056096 304.31 19.53 9.2 59.0 1.0 165.7 9.9 2.4
100718160 301117824 121.83 -46.18 5.9 49.8 121.0 2.6 4.5 2.3
100719311 301217312 304.87 -67.14 15.4 43.0 1.0 96.0 3.7 1.5
100719825 301261696 231.41 18.56 10.3 58.0 1.0 167.4 6.5 1.6
100722096 301457920 238.77 -15.61 1.1 32.9 13.0 6.6 2.8 1.0
100724029 301624928 124.16 74.42 1.0 51.3 100.0 6.6 11.1 6.6
100725475 301749888 292.26 76.20 4.0 19.2 1.0 66.6 2.6 1.3
100728095 301976256 88.76 -15.26 0.0 59.9 147.0 6.4 19.8 7.2
100728439 302005920 44.05 0.28 0.1 57.0 6.0 33.6 5.8 1.8
100729415 302090240 349.59 -74.86 102.8 5.6 23.0 - - -
100802240 302420736 2.47 47.75 0.0 64.8 150.0 8.0 16.7 14.2
100805845 302732192 112.72 -35.93 3.8 64.7 44.0 8.9 15.8 3.8
100811108 303186944 345.87 15.86 6.0 64.0 1.0 229.4 26.4 10.1
100811781 303245056 108.14 62.19 3.6 17.9 16.0 5.7 2.9 1.2
100820373 303987424 258.79 -18.51 2.1 50.0 2.0 120.9 4.8 2.2
100826957 304556320 286.43 -32.63 3.8 64.2 103.0 4.0 9.9 3.8
100829374 304765152 115.45 -3.99 4.7 61.3 80.0 3.9 7.4 3.2
100905907 305416000 262.65 13.08 4.0 61.9 12.0 32.9 12.4 4.8
100910818 305840256 238.10 -34.62 1.0 50.8 21.0 8.2 7.8 4.7
100911816 305926528 151.32 58.99 11.8 59.0 1.0 12910.0 9.4 3.4
100919884 306623552 163.24 6.02 1.8 42.1 14.0 6.9 3.3 1.4
100923844 306965728 106.12 39.60 5.3 34.0 16.0 5.6 41.1 2.2
100924165 306993504 0.67 7.00 0.0 51.0 33.0 - - -
100926694 307212000 43.58 -11.10 12.0 46.0 1.0 113.3 6.1 2.4
100929235 307431520 166.33 62.29 13.4 41.0 1.0 85.2 2.9 1.0
101013412 308656352 292.08 -49.64 1.6 40.0 148.0 1.9 4.4 1.6
101014175 308722304 26.94 -51.07 1.0 54.1 116.0 2.8 6.6 -
101015558 308841856 73.16 15.46 5.9 57.0 21.0 13.5 9.5 -
101017619 309019904 27.47 -26.55 4.9 35.9 20.0 4.1 3.1 1.0
101025146 309670208 240.19 -8.49 24.4 55.0 1.0 134.6 7.0 2.2
101027230 309850240 79.02 43.97 11.4 30.0 1.0 75.1 3.8 1.0
101101899 310340064 266.04 -29.00 5.4 60.2 17.0 19.2 10.1 6.7
101102840 310421408 284.68 -37.03 7.8 39.1 148.0 1.0 2.9 1.2
101107011 310781792 168.33 22.43 4.1 36.2 147.0 1.4 2.7 1.1
101112984 311297824 100.10 9.62 5.1 46.9 70.0 1.8 4.2 1.2
101113483 311340928 29.08 0.21 2.7 46.3 147.0 0.9 3.6 1.1
101116481 311599936 32.00 -81.20 7.3 13.0 1.0 66.5 3.1 1.2
101126198 312439456 84.77 -22.55 1.0 63.5 25.0 10.5 8.9 2.9
101127093 312516832 290.31 7.89 23.2 64.9 1.0 282.1 12.4 7.6
101127102 312517664 70.95 -11.32 6.6 29.4 14.0 5.6 2.6 0.8
101128322 312623040 145.47 -35.20 5.7 7.0 2.0 62.1 3.1 0.8
101129652 312737984 157.75 -17.25 4.6 26.0 1.0 69.8 3.8 1.6
101129726 312744320 271.54 1.01 8.2 41.0 1.0 85.6 5.9 1.3
101204343 313143264 191.91 55.67 10.4 44.0 43.0 3.6 5.0 2.7
101206036 313289536 164.08 -38.11 3.5 57.5 8.0 25.2 12.8 3.2
101207536 313419104 175.75 8.72 3.7 57.3 148.0 1.3 6.2 1.6
101208203 313476768 212.40 4.04 11.7 39.2 1.0 - - -
101213849 313964544 260.99 -64.51 7.1 51.0 147.0 1.2 4.3 1.8
101214993 314063392 185.97 -24.27 10.0 60.0 13.0 16.2 6.7 2.1
101219686 314468896 12.23 -34.57 0.0 53.2 12.0 17.6 8.7 4.2
101220576 314545792 241.57 46.14 1.2 14.7 85.0 1.0 2.5 0.8
101220864 314570624 2.70 27.20 1.5 63.5 33.0 8.3 9.0 3.0
101224578 314891584 289.14 -55.25 4.8 49.6 47.0 2.9 3.7 1.3
101227406 315135904 240.50 -24.50 1.6 5.0 10.0 7.2 2.2 0.9
101227536 315147104 150.87 -49.44 2.6 57.7 16.0 11.5 8.3 4.0
Table 1: Burst Sample with Select Parameters
GRB Amplitude C-Stat
( photons cm s) (keV)
080824909 0.65 0.33 -1.02 0.25 -1.84 0.12 113.2 47.6 1.27
080906212 12.07 1.58 -0.42 0.09 -2.38 0.13 163.9 11.8 1.29
080925775 1.87 0.19 -1.00 0.05 -2.13 0.08 136.3 11.6 1.32
081122520 4.19 0.44 -0.64 0.07 -2.44 0.23 221.2 19.9 1.02
081207680 0.97 0.04 -0.66 0.03 -1.98 0.05 417.0 24.8 2.44
081223419 4.84 4.20 -0.25 0.46 -1.85 0.14 104.4 33.3 1.03
081231140 1.50 0.08 -1.07 0.04 -2.59 0.34 251.9 20.6 1.38
090129880 0.65 0.10 -1.52 0.09 -2.31 0.53 184.7 62.5 1.10
090131090 2.70 0.52 -1.11 0.08 -2.17 0.04 55.0 4.2 1.85
090514006 1.54 0.56 -0.81 0.19 -2.10 0.19 103.9 21.4 1.12
090528516 2.38 0.14 -1.00 0.03 -2.19 0.06 163.5 8.9 2.43
090612619 1.24 0.15 -0.81 0.10 -2.30 0.41 399.1 80.6 1.18
090620400 1.81 0.21 -0.45 0.07 -2.53 0.21 157.7 9.8 1.26
090829672 1.88 0.04 -1.59 0.01 -2.27 0.11 254.4 20.1 2.62
091031500 0.72 0.04 -0.91 0.05 -2.28 0.25 474.6 58.5 1.54
091109895 50.12 176.00 0.78 1.57 -2.28 0.23 46.3 13.6 1.10
091120191 2.58 0.27 -1.02 0.06 -2.50 0.13 101.4 5.8 2.30
091127976 10.01 1.61 -1.28 0.06 -2.22 0.02 34.1 1.4 1.53
091208410 1.32 0.20 -1.34 0.08 -2.32 0.24 110.3 17.3 1.30
091221870 1.20 0.17 -0.76 0.10 -2.09 0.12 205.7 26.8 1.53
100122616 6.89 1.65 -0.91 0.10 -2.32 0.04 42.7 2.3 1.49
100131730 11.80 1.32 -0.57 0.06 -2.21 0.08 138.1 8.4 1.02
100225115 0.56 0.06 -0.83 0.09 -2.48 0.74 493.4 107.0 1.37
100225580 3.71 0.46 -0.76 0.08 -2.11 0.12 194.5 21.4 1.22
100724029 3.36 0.04 -0.76 0.01 -2.03 0.02 413.1 8.9 3.19
100728095 1.33 0.02 -0.86 0.02 -3.03 0.35 413.5 13.3 15.24
101126198 3.10 0.13 -1.25 0.02 -2.56 0.15 156.7 7.5 1.62
101206036 0.49 0.11 -1.13 0.16 -1.84 0.28 467.6 324.0 1.20
101227406 3.15 0.91 -0.51 0.19 -2.18 0.13 148.9 20.9 1.48
101227536 0.48 0.03 -0.73 0.08 -2.26 0.32 828.2 172.0 1.19
Table 2: Spectral Parameters for 30 Bright GBM Detected Bursts - GBM Fits
GRB T90 Measured Flux 0.02–20 MeV Expected Flux 0.1–10 GeV Flux Limit 0.1–10 GeV
(s) (photons cm s) ( photons cm s) ( photons cm s)
080824909 28.67 1.04 0.04 9.75 8.87 4.50
080906212 2.69 12.20 0.18 3.87 3.32 43.60
080925775 38.14 3.08 0.03 3.85 2.04 5.09
081122520 4.10 6.37 0.12 1.71 2.49 24.75
081207680 104.45 2.26 0.02 20.50 6.49 4.31
081223419 2.36 2.90 0.13 30.00 29.70 34.95
081231140 27.65 3.37 0.04 0.34 0.66 2.49
090129880 16.38 2.03 0.05 0.68 2.26 6.94
090131090 57.35 2.98 0.03 1.64 0.49 2.21
090514006 12.97 1.70 0.06 2.31 3.10 5.05
090528516 61.44 4.25 0.03 3.71 1.50 5.05
090612619 6.14 2.91 0.09 3.26 7.79 32.23
090620400 49.41 1.81 0.03 0.19 0.26 5.31
090829672 94.21 6.61 0.03 3.31 2.20 1.76
091031500 45.06 1.89 0.03 2.60 3.65 4.07
091109895 6.14 1.44 0.11 0.36 0.64 20.74
091120191 53.25 3.56 0.04 0.25 0.23 3.80
091127976 14.08 10.70 0.05 3.49 0.48 6.73
091208410 16.38 2.87 0.06 0.69 1.15 7.69
091221870 34.82 1.98 0.04 4.78 3.93 4.86
100122616 29.70 4.11 0.04 0.63 0.22 3.69
100131730 3.46 12.20 0.15 9.81 5.04 10.33
100225115 18.99 1.44 0.05 0.69 2.73 7.16
100225580 5.12 5.86 0.10 11.60 9.48 25.36
100724029 100.35 8.02 0.03 48.40 5.20 13.52
100728095 147.46 3.20 0.02 0.06 0.11 3.81
101126198 25.60 6.91 0.05 0.45 0.44 10.43
101206036 17.92 1.44 0.07 23.70 39.70 13.89
101227406 10.50 3.27 0.10 3.51 3.10 6.23
101227536 18.82 1.55 0.05 5.00 8.10 13.32
Table 3: Measured and Expected Photon Fluxes in the GBM and LAT Bands
GRB Amplitude Cash DOF C-Stat
( photons cm s) (keV)
080824909 0.53 0.12 -1.11 0.13 -2.41 0.15 151.2 31.3 475.73 378 -0.56 0.15 2.32
080906212 10.79 1.10 -0.48 0.07 -2.55 0.12 176.4 10.1 639.11 504 -0.17 0.12 0.20
080925775 1.70 0.12 -1.05 0.04 -2.42 0.09 154.0 9.4 500.77 380 -0.30 0.09 9.53
081122520 3.99 0.35 -0.67 0.07 -2.64 0.19 232.7 17.0 501.82 502 -0.20 0.19 0.04
081207680 0.87 0.02 -0.73 0.02 -2.70 0.12 528.2 24.3 952.43 385 -0.72 0.12 14.57
081223419 2.57 1.02 -0.57 0.25 -2.23 0.15 149.6 32.0 399.95 380 -0.37 0.15 0.67
081231140 1.46 0.07 -1.08 0.03 -3.46 0.71 265.7 16.0 509.18 378 -0.88 0.71 0.01
090129880 0.61 0.07 -1.55 0.07 -4.16 36.00 219.9 56.2 406.74 379 -1.85 36.00 0.00
090131090 1.62 0.16 -1.33 0.05 -2.42 0.09 73.8 4.6 696.42 374 -0.25 0.09 15.51
090514006 1.49 0.41 -0.82 0.15 -2.30 0.10 109.1 15.1 424.25 380 -0.19 0.10 2.59
090528516 2.14 0.09 -1.06 0.03 -2.49 0.11 187.2 8.6 1216.40 504 -0.30 0.11 9.20
090612619 1.18 0.10 -0.84 0.08 -3.41 0.66 444.0 65.5 436.14 379 -1.11 0.66 0.00
090620400 1.77 0.18 -0.47 0.07 -2.60 0.14 160.0 8.6 469.50 377 -0.07 0.14 0.08
090829672 1.83 0.03 -1.60 0.01 -3.07 0.48 287.0 17.3 972.98 379 -0.80 0.48 0.39
091031500 0.70 0.03 -0.92 0.04 -2.63 0.09 501.1 50.2 567.74 378 -0.35 0.09 0.02
091109895 54.26 190.00 0.81 1.58 -2.24 0.11 45.6 12.3 272.81 255 0.04 0.11 -0.04
091120191 2.53 0.24 -1.03 0.05 -2.56 0.11 103.1 5.1 589.17 262 -0.06 0.11 0.31
091127976 8.55 1.16 -1.34 0.06 -2.26 0.02 36.4 1.4 774.38 495 -0.04 0.02 25.95
091208410 1.35 0.20 -1.33 0.07 -2.28 0.07 107.4 13.9 480.39 376 0.04 0.07 0.07
091221870 1.06 0.10 -0.84 0.07 -2.48 0.11 241.0 22.8 571.15 379 -0.40 0.11 2.67
100122616 6.01 1.28 -0.96 0.09 -2.38 0.05 44.6 2.3 557.59 379 -0.06 0.05 5.13
100131730 8.07 0.48 -0.78 0.04 -3.32 0.20 183.8 7.3 399.27 382 -1.11 0.20 2.59
100225115 0.56 0.05 -0.83 0.09 -2.54 0.17 496.8 94.8 506.20 379 -0.06 0.17 -0.02
100225580 3.02 0.21 -0.88 0.05 -3.25 0.24 248.8 17.7 619.61 509 -1.14 0.24 1.72
100724029 3.08 0.03 -0.82 0.01 -2.51 0.03 502.1 8.6 1435.30 378 -0.48 0.03 170.70
100728095 1.33 0.02 -0.86 0.02 -2.84 0.12 410.8 12.4 5633.20 379 0.19 0.12 0.70
101126198 3.08 0.12 -1.26 0.02 -2.62 0.16 158.4 7.2 603.71 379 -0.06 0.16 0.37
101206036 0.49 0.07 -1.12 0.12 -2.45 0.27 514.9 209.0 445.33 378 -0.62 0.27 0.06
101227406 2.18 0.38 -0.74 0.13 -2.53 0.20 188.7 21.3 549.62 378 -0.35 0.20 3.26
101227536 0.47 0.03 -0.75 0.07 -3.65 0.86 930.3 164.0 440.63 378 -1.39 0.86 0.01
Table 4: Spectral Parameters for 30 Bright GBM Detected Bursts - GBM LAT Fits

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