Now showing items 1-4 of 4

    • The Gamma Ray Burst section of the White Paper on the Status and Future of Very High Energy Gamma Ray Astronomy: A Brief Preliminary Report 

      Falcone, A.D.; Williams, D.A.; Baring, M.G.; Blandford, R.; Connaughton, V.; Coppi, P.; Dermer, C.; Dingus, B.; Fryer, C.; Gehrels, N.; Granot, J.; Horan, D.; Katz, J.I.; Kuehn, K.; Meszaros, P.; Norris, J.; Parkinson, P.S.; Pe'er, A.; Ramirez-Ruiz, E.; Razzaque, S.; Wang, X.; Zhang, B. (2008)
    • The Gamma Ray Burst section of the White Paper on the Status and Future of Very High Energy Gamma Ray Astronomy: A Brief Preliminary Report 

      Falcone, A.D.; Williams, D.A.; Baring, M.G.; Blandford, R.; Connaughton, V.; Coppi, P.; Dermer, C.; Dingus, B.; Fryer, C.; Gehrels, N.; Granot, J.; Horan, D.; Katz, J.I.; Kuehn, K.; Meszaros, P.; Norris, J.; Parkinson, P.S.; Pe'er, A.; Ramirez-Ruiz, E.; Razzaque, S.; Wang, X.; Zhang, B. (American Institute of Physics (AIP), 2008)
      This is a short report on the preliminary findings of the gamma ray burst (GRB) working group for the white paper on the status and future of very high energy (VHE; >50 GeV) gamma-ray astronomy. The white paper discusses ...
    • Transfer learning for galaxy morphology from one survey to another 

      Sánchez, H. Domínguez; Huertas-Company, M.; Bernardi, M.; Kaviraj, S.; Fischer, J. L.; Abbott, T. M. C.; Abdalla, F. B.; Annis, J.; Avila, S.; Buckley-Geer, E.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Cunha, C. E.; D'Andrea, C. B.; Costa, L. N. da; Davis, C.; Vicente, J. De; Doel, P.; Evrard, A. E.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gaztanaga, E.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Hartley, W. G.; Hollowood, D. L.; Honscheid, K.; Hoyle, B.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Maia, M. A. G.; March, M.; Melchior, P.; Menanteau, F.; Miquel, R.; Nord, B.; Plazas, A. A.; Sanchez, E.; Scarpine, V.; Schindler, R.; Schubnell, M.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Walker, A. R.; Zuntz, J. (2018-12-28)
      Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of ...
    • AN ULTRA-FAINT GALAXY CANDIDATE DISCOVERED in EARLY DATA from the MAGELLANIC SATELLITES SURVEY 

      Drlica-Wagner, A.; Bechtol, Keith; Allam, S.; Tucker, D. L.; Gruendl, R. A.; Johnson, M. D.; Walker, A. R.; James, D. J.; Nidever, D. L.; Olsen, K. A G; Wechsler, R. H.; Cioni, M. R L; Conn, B. C.; Kuehn, K.; Li, T. S.; Mao, Y. Y.; Martin, N. F.; Neilsen, E.; Noel, N. E D; Pieres, A.; Simon, J. D.; Stringfellow, G. S.; Marel, R. P Van Der; Yanny, B. (2016-12-10)
      We report a new ultra-faint stellar system found in Dark Energy Camera data from the first observing run of the Magellanic Satellites Survey (MagLiteS). MagLiteS J0644-5953 (Pictor II or Pic II) is a low surface brightness ...