@article{ShilonKrausBuecheleetal.2018,
  author    = {Shilon, I. and Kraus, M. and B{\"u}chele, M. and Egberts, Kathrin and Fischer, Tobias and Holch, Tim Lukas and Lohse, T. and Schwanke, U. and Steppa, Constantin Beverly and Funk, Stefan},
  title     = {Application of deep learning methods to analysis of imaging atmospheric Cherenkov telescopes data},
  series = {Astroparticle physics},
  volume    = {105},
  journal   = {Astroparticle physics},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0927-6505},
  doi       = {10.1016/j.astropartphys.2018.10.003},
  pages     = {44 -- 53},
  year      = {2018},
  abstract  = {Ground based gamma-ray observations with Imaging Atmospheric Cherenkov Telescopes (IACTs) play a significant role in the discovery of very high energy (E > 100 GeV) gamma-ray emitters. The analysis of IACT data demands a highly efficient background rejection technique, as well as methods to accurately determine the position of its source in the sky and the energy of the recorded gamma-ray. We present results for background rejection and signal direction reconstruction from first studies of a novel data analysis scheme for IACT measurements. The new analysis is based on a set of Convolutional Neural Networks (CNNs) applied to images from the four H.E.S.S. phase-I telescopes. As the H.E.S.S. cameras pixels are arranged in a hexagonal array, we demonstrate two ways to use such image data to train CNNs: by resampling the images to a square grid and by applying modified convolution kernels that conserve the hexagonal grid properties. The networks were trained on sets of Monte-Carlo simulated events and tested on both simulations and measured data from the H.E.S.S. array. A comparison between the CNN analysis to current state-of-the-art algorithms reveals a clear improvement in background rejection performance. When applied to H.E.S.S. observation data, the CNN direction reconstruction performs at a similar level as traditional methods. These results serve as a proof-of-concept for the application of CNNs to the analysis of events recorded by IACTs. (C) 2018 Published by Elsevier B.V.},
  language  = {en}
}
@article{ArchambaultArcherBenbowetal.2017,
  author    = {Archambault, S. and Archer, A. and Benbow, W. and Bird, Ralph and Bourbeau, E. and Bouvier, A. and Buchovecky, M. and Bugaev, V. and Cardenzana, J. V. and Cerruti, M. and Ciupik, L. and Connolly, M. P. and Cui, W. and Daniel, M. K. and Errando, M. and Falcone, A. and Feng, Q. and Finley, J. P. and Fleischhack, H. and Fortson, L. and Furniss, A. and Gillanders, G. H. and Griffin, S. and Hanna, D. and Hervet, O. and Holder, J. and Hughes, G. and Humensky, T. B. and Hutten, M. and Johnson, C. A. and Kaaret, P. and Kar, P. and Kertzman, M. and Kieda, D. and Krause, M. and Lang, M. J. and Lin, T. T. Y. and Maier, G. and McArthur, S. and Moriarty, P. and Mukherjee, R. and Nieto, D. and Ong, R. A. and Otte, A. N. and Park, N. and Pohl, Martin and Popkow, A. and Pueschel, Elisa and Quinn, J. and Ragan, K. and Reynolds, P. T. and Richards, G. T. and Roache, E. and Rulten, C. and Sadeh, I. and Sembroski, G. H. and Shahinyan, K. and Staszak, D. and Telezhinsky, Igor O. and Trepanier, S. and Wakely, S. P. and Weinstein, A. and Wilcox, P. and Williams, D. A. and Zitzer, B.},
  title     = {Gamma-ray observations under bright moonlight with VERITAS},
  series = {Astroparticle physics},
  volume    = {91},
  journal   = {Astroparticle physics},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0927-6505},
  doi       = {10.1016/j.astropartphys.2017.03.001},
  pages     = {34 -- 43},
  year      = {2017},
  abstract  = {Imaging atmospheric Cherenkov telescopes (IACTs) are equipped with sensitive photomultiplier tube (PMT) cameras. Exposure to high levels of background illumination degrades the efficiency of and potentially destroys these photo-detectors over time, so IACTs cannot be operated in the same configuration in the presence of bright moonlight as under dark skies. Since September 2012, observations have been carried out with the VERITAS IACTs under bright moonlight (defined as about three times the night-sky-background (NSB) of a dark extragalactic field, typically occurring when Moon illumination > 35\%) in two observing modes, firstly by reducing the voltage applied to the PMTs and, secondly, with the addition of ultra-violet (UV) bandpass filters to the cameras. This has allowed observations at up to about 30 times previous NSB levels (around 80\% Moon illumination), resulting in 30\% more observing time between the two modes over the course of a year. These additional observations have already allowed for the detection of a flare from the 1ES 1727 + 502 and for an observing program targeting a measurement of the cosmic-ray positron fraction. We provide details of these new observing modes and their performance relative to the standard VERITAS observations. (C) 2017 Elsevier B.V. All rights reserved.},
  language  = {en}
}