This article was accepted into the corpus but its outbound wikilinks were never NER-processed — typical at the deepest BFS hop or when the run's entity cap was reached. No expansion funnel to show.
| Dark Energy Survey Supernova Program | |
|---|---|
| Name | Dark Energy Survey Supernova Program |
| Mission | Dark Energy Survey |
| Operator | Fermi National Accelerator Laboratory; Cerro Tololo Inter-American Observatory |
| Telescope | Victor M. Blanco Telescope |
| Instrumentation | Dark Energy Camera |
| Location | Cerro Tololo Inter-American Observatory |
| Started | 2013 |
| Concluded | 2019 |
Dark Energy Survey Supernova Program The Dark Energy Survey Supernova Program is a targeted transient search nested within the Dark Energy Survey designed to discover and follow Type Ia supernovae to measure cosmic acceleration. It used the Victor M. Blanco Telescope and the Dark Energy Camera to survey four deep fields with coordinated follow-up from facilities such as Gemini Observatory, Magellan Telescopes, and Southern Astrophysical Research Telescope. The program contributed to joint analyses with datasets from Planck (spacecraft), Sloan Digital Sky Survey, and Pan-STARRS to constrain dark energy and cosmic expansion history.
The program operated as a component of the Dark Energy Survey, integrating teams from institutions including Fermi National Accelerator Laboratory, Lawrence Berkeley National Laboratory, SLAC National Accelerator Laboratory, University of Chicago, and UC Berkeley. Observing campaigns targeted the same extragalactic deep fields monitored by collaborations such as The Dark Energy Spectroscopic Instrument precursor programs and complementary programs like Supernova Legacy Survey and ESSENCE Project. Scientific aims aligned with those of projects funded by agencies such as the National Science Foundation, the Department of Energy (United States), and international partners from Brazilian Centro de Pesquisas Físicas, Australian Astronomical Observatory, and European Southern Observatory affiliates.
Survey operations centered on the Dark Energy Camera, a 570-megapixel imager built by a consortium including Fermi National Accelerator Laboratory and University College London. Mounted on the Victor M. Blanco Telescope at Cerro Tololo Inter-American Observatory, the camera delivered wide-field imaging comparable to instruments used by Hyper Suprime-Cam and predecessor imagers on Kitt Peak National Observatory telescopes. The program executed a rolling search strategy adapted from methods used by Supernova Cosmology Project and High-Z Supernova Search Team, balancing cadence, filter allocation, and depth across fields overlapping legacy surveys like COSMOS, Stripe 82, and Chandra Deep Field South. Calibration references included standard star catalogs compiled by projects such as Pan-STARRS1 and photometric systems tied to Hubble Space Telescope spectrophotometric standards used by the Carnegie Supernova Project.
Transient identification relied on image subtraction pipelines developed collaboratively with teams from Lawrence Berkeley National Laboratory and National Optical Astronomy Observatory. Candidate vetting used machine-learning classifiers influenced by algorithms from SExtractor and pipelines similar to those used by Zwicky Transient Facility and Palomar Transient Factory. Spectroscopic follow-up programs scheduled time on Gemini Observatory instruments including GMOS, on Magellan Telescopes instruments such as IMACS, and on Very Large Telescope facilities coordinated with the European Southern Observatory. Classification incorporated comparisons to spectral libraries maintained by the CfA Supernova Program and light-curve fitting codes developed in the Supernova Cosmology Project tradition and by groups at Harvard–Smithsonian Center for Astrophysics.
Data processing pipelines were built on software ecosystems contributed by Lawrence Berkeley National Laboratory, SLAC National Accelerator Laboratory, and the National Center for Supercomputing Applications, with workflows compatible with resources like NERSC. Photometric calibration exploited stellar catalogs from Gaia (spacecraft), the Two Micron All Sky Survey, and cross-calibration with Sloan Digital Sky Survey photometry. Image reduction incorporated dark and flat-field correction approaches refined in projects such as Dark Energy Spectroscopic Instrument commissioning. Systematic error budgets referenced calibration studies by the Carnegie Supernova Project, K-correction methods from P. Nugent and collaborators, and Milky Way extinction maps from Schlegel, Finkbeiner, and Davis used across cosmological analyses.
Results from the program contributed distance measurements that, when combined with Planck (spacecraft) cosmic microwave background priors and baryon acoustic oscillation data from BOSS, provided constraints on the dark energy equation-of-state parameter in analyses akin to those by the Joint Light-curve Analysis and Pantheon Compilation. The sample informed studies of Type Ia supernova population evolution investigated by teams at University of Utah and Max Planck Institute for Astrophysics, host-galaxy correlations examined in work from University of Portsmouth and National Optical Astronomy Observatory, and tests of alternative cosmological models explored by researchers associated with University of Oxford and Kavli Institute for Cosmology. The program's measurements were incorporated into multi-probe cosmology efforts alongside data from DES Year 1, DES Year 3, and ongoing analyses by the Dark Energy Science Collaboration.
The supernova program assembled a collaboration of scientists from institutions such as University of Michigan, University of Illinois Urbana-Champaign, University of Pennsylvania, Yale University, University of Cambridge, and ETH Zurich. Time-domain coordination included target-of-opportunity arrangements with facilities like SOAR Telescope, Keck Observatory, and Very Large Telescope to secure spectra and host-galaxy redshifts. The collaboration engaged in joint working groups modeled on organizational structures used by LSST Dark Energy Science Collaboration and coordinated analysis standards with consortia including Pan-STARRS Team and Supernova Cosmology Project collaborators.
Legacy releases delivered calibrated light curves, difference-image stacks, and spectroscopic classifications used by researchers at California Institute of Technology, Princeton University, University of Toronto, and Stanford University. The dataset informed simulations and survey planning for next-generation facilities like the Vera C. Rubin Observatory and influenced strategy for the Euclid (spacecraft) mission and the Nancy Grace Roman Space Telescope. Methods and software from the program propagated into training sets for machine-learning classifiers used by Zwicky Transient Facility and assisted consortiums such as the LSST Science Collaborations in preparing for large-scale time-domain cosmology.
Category:Astronomical surveys Category:Supernovae Category:Dark energy