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

The Supernova Cosmology Project, Brian Hayden, David Rubin, Kyle Boone, Greg Aldering, Jakob Nordin, Mark Brodwin, Susana Deustua, Sam Dixon, Parker Fagrelius, Andy Fruchter, Peter Eisenhardt, Anthony Gonzalez, Ravi Gupta, Isobel Hook, Chris Lidman, Kyle Luther, Adam Muzzin, Zachary Raha, Pilar Ruiz-LapuenteClare Saunders, Caroline Sofiatti, Adam Stanford, Nao Suzuki, Tracy Webb, Steven C. Williams, Gillian Wilson, Mike Yen, Rahman Amanullah, Kyle Barbary, Hans Böhringer, Greta Chappell, Carlos Cunha, Miles Currie, Rene Fassbender, Michael Gladders, Ariel Goobar, Hendrik Hildebrandt, Henk Hoekstra, Xiaosheng Huang, Dragan Huterer, M. James Jee, Alex Kim, Marek Kowalski, Eric Linder, Joshua E. Meyers, Reynald Pain, Saul Perlmutter, Johan Richard, Piero Rosati, Eduardo Rozo, Eli Rykoff, Joana Santos, Anthony Spadafora, Daniel Stern, Risa Wechsler

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number87
JournalAstrophysical Journal
Volume912
Issue number2
DOIs
StatePublished - May 10 2021

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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