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Identification of RR Lyrae stars in multiband, sparsely sampled data from the Dark Energy Survey using template fitting and random forest classification
DES Collaboration, Daniel Thomas
- Texas A&M University
- Kavli Institute for Cosmological Physics
- University College London
- Fermi National Accelerator Laboratory
- The University of Chicago
- National Optical Astronomy Observatory
- LSST Corporation
- Large Synoptic Survey Telescope
- University of Illinois at Urbana-Champaign
- Cerro Tololo Inter-American Observatory
- SLAC National Accelerator Laboratory
- Stanford University
- Observatório Nacional
- Laboratório Interinstitucional de e-Astronomia
- CIEMAT
- University of Michigan, Ann Arbor
- University of Wyoming
- CNRS
- Université Paris Cité
- Sorbonne Université
- Universite Blaise Pascal
- Institut d 'Astrophysique de Paris
- Autonomous University of Barcelona
- Institute of Space Studies of Catalonia
- The Barcelona Institute of Science and Technology
- Institute for High Energy Physics
- University of Pennsylvania
- Indian Institute of Technology Hyderabad
- Jet Propulsion Laboratory, California Institute of Technology
- California Institute of Technology
- University of Arizona
- Universidad Autónoma de Madrid
- CSIC
- Max Planck Institute for Extraterrestrial Physics
- Ludwig Maximilian University of Munich
- Swiss Federal Institute of Technology Zurich
- University of California at Santa Cruz
- University of Washington
- Harvard University
- Ohio University
- Ohio State University
- Princeton University
- ICREA
- Astronomical Society of the Pacific
- Universidade Federal do Rio Grande do Sul
- University of Southampton
- University of the Western Cape
- University of Cape Town
- Brandeis University
- Universidade Federal do ABC
- Oak Ridge National Laboratory
- Universidade Estadual de Campinas
- Universidade Estadual Paulista Júlio de Mesquita Filho
- Argonne National Laboratory
Research output: Contribution to journal › Article › peer-review
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