The HST See Change Program. I. Survey Design, Pipeline, and Supernova Discoveries

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The See Change survey was designed to make z > 1 cosmological measurements by efficiently discovering high-redshift Type Ia supernovae (SNe Ia) and improving cluster mass measurements through weak lensing. This survey observed twelve galaxy clusters with the Hubble Space Telescope (HST) spanning the redshift range z = 1.13-1.75, discovering 57 likely transients and 27 likely SNe Ia at z ~ 0.8-2.3. As in similar previous surveys, this proved to be a highly efficient use of HST for supernova observations; the See Change survey additionally tested the feasibility of maintaining, or further increasing, the efficiency at yet higher redshifts, where we have less detailed information on the expected cluster masses and star formation rates. We find that the resulting number of SNe Ia per orbit is a factor of ~8 higher than for a field search, and 45% of our orbits contained an active SN Ia within 22 rest-frame days of peak, with one of the clusters by itself yielding 6 of the SNe Ia. We present the survey design, pipeline, and supernova discoveries. Novel features include fully blinded supernova searches, the first random forest candidate classifier for undersampled IR data (with a 50% detection threshold within 0.05 mag of human searchers), real-time forward-modeling photometry of candidates, and semi-automated photometric classifications and follow-up forecasts. We also describe the spectroscopic follow-up, instrumental in measuring host galaxy redshifts. The cosmology analysis of our sample will be presented in a companion paper. * Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS 5-26555, under programs 13677, 14327.
Based in part on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), Ministério da Ciência, Tecnologia e Inovação (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea). Based on observations collected at the Table 4. European Organisation for Astronomical Research in the Southern Hemisphere under ESO program(s) 294.A-5025(A), 095.A-0830(A, B, C), 096.A-0926(B, C), 097.A-0442(A, B, C), and 0100.A-0851(A). G.W. acknowledges support from the National Science Foundation through grant AST-1517863, by HST program numbers GO-13677/14327.01 and GO-15294, and by grant No. 80NSSC17K0019 issued through the NASA Astrophysics Data Analysis Program (ADAP). G.A. and R.G. acknowledge support from HST program NASA HST-GO14163.002-A, and by grant No. NNH16AC25I issued through NASA ADAP. M. J. J. acknowledges support for the current research from the National Research Foundation (NRF) of Korea under the programs 2017R1A2B2004644 and 2020R1A4A2002885. H. Hildebrandt is supported by a Heisenberg grant of the Deutsche Forschungsgemeinschaft (Hi 1495/5-1) as well as an ERC Consolidator Grant (No. 770935). Support for program numbers GO-13677/14327.01 and GO-15294 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. This work was also partially supported by the Office of Science, Office of High Energy Physics, of the U.S. Department of Energy, under contract no. DE-AC02-05CH11231. Facilities: Hubble Space Telescope, Keck:I (LRIS), Keck:I (MOSFIRE), VLT, Gemini, GTC, Subaru. Software: astropy (Astropy Collaboration 2013), DrizzlePac (Gonzaga et al. 2012), iPython (Pérez & Granger 2007), Matplotlib (Hunter 2007), Numpy (van der Walt et al. 2011), SEP (Barbary 2016), scikit-learn (Pedregosa et al. 2011), SciPy