Mathematics – Probability
Scientific paper
Jan 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21537007b&link_type=abstract
American Astronomical Society, AAS Meeting #215, #370.07; Bulletin of the American Astronomical Society, Vol. 42, p.562
Mathematics
Probability
Scientific paper
We present an analysis of supernova (SN) light curves simulated for the upcoming Dark Energy Survey (DES). We employed a code suite (SNANA) that generates and fits realistic SN light curves. We forecast that the DES sample of well measured Type Ia supernovae (SNe Ia) will number from 2300 to 3000 or more out to a redshift of 1 depending on selection cuts. The DES will obtain spectra for only 10-20 percent of the SN Ia sample. Since photometrically identified SNe Ia have never been used for cosmology analyses, we have undertaken a study of non-Type Ia SN (non-Ia) contamination in the DES SN Ia sample. For a given set of selection cuts, we estimate 2-7 percent contamination depending on a SN Ia light curve fit probability cut. We find that this level of non-Ia contamination significantly biases the determination of the dark energy equation of state parameter and that a more strict requirement on the fit probability results in a notable loss of SNe Ia. Initial results show that fitting for individual SN Ia and non-Ia contributions to the Hubble diagram may sufficiently control contamination without increasing the fit probability cut thereby reducing SN Ia losses. While these simulations are based on sparse non-Ia data with large uncertainties, such studies are useful for learning how to mitigate contamination in samples without a confirmation spectrum for every SN. In addition, these simulations can provide guidance on future non-Ia observing strategies. We further discuss the first results of an analysis of light curves simulated for combined DES and VISTA Deep Extragalactic Observations Survey (VIDEO) infrared data. The DES and VIDEO temporally overlap and some of the supernova fields are shared. This presents an outstanding opportunity to enhance supernova color determinations due to an expanded optical plus infrared wavelength range.
Bernstein Joseph P.
Crane I.
Dark Energy Survey Collaboration
Hufford Tara
Kessler Richard
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