Mathematics – Logic
Scientific paper
May 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21812709s&link_type=abstract
American Astronomical Society, AAS Meeting #218, #127.09; Bulletin of the American Astronomical Society, Vol. 43, 2011
Mathematics
Logic
Scientific paper
Increasingly large photometric surveys of transient phenomena, such as Pan-STARRS, DES and LSST, will locate thousands to millions of SNe Ia candidates per year, a rate prohibitive for acquiring spectroscopy to determine each candidate's type and redshift. Multiple supernova photometric classification/photo-z algorithms have been developed in recent years to deal with the issue of limited spectroscopic follow-up, and the Supernova Photometric Classification Challenge (Kessler et al. 2010) has shown the highest SN Ia classification purity is 80% and redshift determination is accurate to a photo-z residual of 0.05. In response, we have developed an economical approach to identifying SNe Ia and their redshifts using an uncommon type of optical filter with offset, multiple, narrow bandpasses that are designed to match the undulations of a Type Ia supernova spectrum. Observation of a supernova through a specially designed pair of these `SuperNovAe Cross-Correlation ’ (SNACC) filters measures the approximate amplitude and phase of the cross-correlation between the spectrum and a SN Ia template, a quantity typically used to determine the redshift and type of a high-redshift SN Ia. We present 98 PS1 SNe candidates that were followed-up with 4-passband SNACC filters on Subaru Telescope's SuprimeCam. 60 of these SN candidates were classified as SNe Ia with the SNACC approach, and the subset of 20 SNe Ia with spectroscopic identifications shows, given a photometric redshift to resolve SNACC's periodic z±0.2 ambiguity, that the SNACC rms_z 0.01. From our limited non-Ia supernova, spectroscopically verified sample, we find the bifurcation in the SNACC color space that yields a Ia classification purity of 95%. We demonstrate here the cosmological significance of our SNACC sample and discuss further advantages over photometric classification/photo-z algorithms critical for photometric supernova surveys.
Huber Marcus
PS1 Science Consortium
Riess Adam
Rodney Steve
Scolnic Daniel
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