Examinando por Autor "Gonzalez-Gaitan, S"

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    THE HIGH CADENCE TRANSIENT SURVEY (HITS). I. SURVEY DESIGN AND SUPERNOVA SHOCK BREAKOUT CONSTRAINTS
    (Universidad Andrés Bello, 2016-12) Forster, F; Maureira, JC; San Martin, J; Hamuy, M; Martinez, J; Huijse, P; Cabrera, G; Galbany, L; de Jaeger, T; Gonzalez-Gaitan, S; Anderson, JP; Kunkarayakti, H; Pignata, G; Bufano, F; Littin, J; Olivares, F; Medina, G; Smith, RC; Vivas, AK; Estevez, PA; Munoz, R; Vera, E
    We present the first results of the High Cadence Transient Survey (HiTS), a survey for which the objective is to detect and follow-up optical transients with characteristic timescales from hours to days, especially the earliest hours of supernova (SN) explosions. HiTS uses the Dark Energy Camera and a custom pipeline for image subtraction, candidate filtering and candidate visualization, which runs in real-time to be able to react rapidly to the new transients. We discuss the survey design, the technical challenges associated with the real-time analysis of these large volumes of data and our first results. In our 2013, 2014, and 2015 campaigns, we detected more than 120 young SN candidates, but we did not find a clear signature from the short-lived SN shock breakouts (SBOs) originating after the core collapse of red supergiant stars, which was the initial science aim of this survey. Using the empirical distribution of limiting magnitudes from our observational campaigns, we measured the expected recovery fraction of randomly injected SN light curves, which included SBO optical peaks produced with models from Tominaga et al. (2011) and Nakar & Sari (2010). From this analysis, we cannot rule out the models from Tominaga et al. (2011) under any reasonable distributions of progenitor masses, but we can marginally rule out the brighter and longer-lived SBO models from Nakar & Sari (2010) under our best-guess distribution of progenitor masses. Finally, we highlight the implications of this work for future massive data sets produced by astronomical observatories, such as LSST.