Journal
ASTROPHYSICAL JOURNAL
Volume 857, Issue 1, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.3847/1538-4357/aab6b1
Keywords
cosmology: observations; dark energy; supernovae: general
Categories
Funding
- Gordon and Betty Moore Foundation postdoctoral fellowship at the University of California, Santa Cruz
- National Aeronautics and Space Administration [NNG16PJ34C]
- NASA [14-WPS14-0048, NAS 5-26555]
- NSF [AST-1518052, AST-95-09298, AST-0071048, AST-0507428, AST-0507483]
- Alfred P. Sloan Foundation
- David and Lucile Packard Foundation
- Kavli Institute for Cosmological Physics at the University of Chicago [NSF PHY-1125897]
- Space Telescope Science Institute
- Smithsonian Astrophysical Observatory
- University of Chicago Research Computing Center
- FAS Division of Science, Research Computing Group, at Harvard University
- U.S. Department of Energy Office of Science
- Center for High-Performance Computing at the University of Utah
- NASA by the California Institute of Technology under NASA [5-98034]
- NASA LTSA [NNG04GC89G]
- Brazilian Participation Group
- Carnegie Institution for Science
- Carnegie Mellon University
- Chilean Participation Group
- French Participation Group
- Harvard-Smithsonian Center for Astrophysics
- Instituto de Astrofisica de Canarias
- Johns Hopkins University
- Kavli Institute for the Physics and Mathematics of the Universe(IPMU)/University of Tokyo
- Lawrence Berkeley National Laboratory
- Leibniz Institut fur Astrophysik Potsdam (AIP)
- Max-Planck-InstitutfurAstronomie(MPIA Heidelberg)
- Max-Planck-Institut fur Astrophysik (MPA Garching)
- Max-Planck-Institut fur Extraterrestrische Physik (MPE)
- National Astronomical Observatory of China
- New Mexico State University
- New York University
- University of Notre Dame
- Observatorio Nacional/MCTI
- Ohio State University
- Pennsylvania State University
- Shanghai Astronomical Observatory
- United Kingdom Participation Group
- Universidad Nacional Autonoma de Mexico
- University of Arizona
- University of Colorado-Boulder
- University of Oxford
- University of Portsmouth
- University of Utah
- University of Virginia
- University of Washington
- University of Wisconsin
- Vanderbilt University
- Yale University
- Division Of Physics
- Direct For Mathematical & Physical Scien [1125897] Funding Source: National Science Foundation
- Science and Technology Facilities Council [ST/P000312/1] Funding Source: researchfish
- STFC [ST/P000312/1] Funding Source: UKRI
Ask authors/readers for more resources
We use 1169 Pan-STARRS supernovae (SNe) and 195 low-z (z < 0.1) SNe Ia to measure cosmological parameters. Though most Pan-STARRS SNe lack spectroscopic classifications, in a previous paper we demonstrated that photometrically classified SNe can be used to infer unbiased cosmological parameters by using a Bayesian methodology that marginalizes over core-collapse (CC) SN contamination. Our sample contains nearly twice as many SNe as the largest previous SN Ia compilation. Combining SNe with cosmic microwave background (CMB) constraints from Planck, we measure the dark energy equation-of-state parameter w to be -0.989 +/- 0.057 (stat+sys). If w evolves with redshift as w(a) = w(0)(1 - a), we find w(0) = -0.912 +/- 0.149 and w(a) = -0.513 +/- 0.826. These results are consistent with cosmological parameters from the Joint Light-curve Analysis and the Pantheon sample. We try four different photometric classification priors for Pan-STARRS SNe and two alternate ways of modeling CC SN contamination, finding that no variant gives a w differing by more than 2% from the baseline measurement. The systematic uncertainty on w due to marginalizing over CC SN contamination, sigma(cc)(w) = 0.012, is the third smallest source of systematic uncertainty in this work. We find limited (1.6 sigma) evidence for evolution of the SN color-luminosity relation with redshift, a possible systematic that could constitute a significant uncertainty in future high-z analyses. Our data provide one of the best current constraints on w, demonstrating that samples with similar to 5% CC SN contamination can give competitive cosmological constraints when the contaminating distribution is marginalized over in a Bayesian framework.
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