2017
DOI: 10.3847/1538-4357/aa767b
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Measuring the Properties of Dark Energy with Photometrically Classified Pan-STARRS Supernovae. I. Systematic Uncertainty from Core-collapse Supernova Contamination

Abstract: The Pan-STARRS (PS1) Medium Deep Survey discovered over 5,000 likely supernovae (SNe) but obtained spectral classifications for just 10% of its SN candidates. We measured spectroscopic host galaxy redshifts for 3,147 of these likely SNe and estimate that ∼1,000 are Type Ia SNe (SNe Ia) with light-curve quality sufficient for a cosmological analysis. We use these data with simulations to determine the impact of core-collapse SN (CC SN) contamination on measurements of the dark energy equation of state parameter… Show more

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Cited by 62 publications
(62 citation statements)
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“…These smaller, more focused, missions can provide exquisite observations of a select handful of SNe that can be used to drive the priors in our inference. While there have been thousands of SNe Ia studied to date (e.g., Jones et al 2017), more examples are indeed still needed: there are only four normal, z<0.03 SNe Ia in our sample, and these four are nearly as valuable as the entire remainder of the sample for establishing the diversity of SNe Ia. As low-z, high-cadence surveys improve our understanding of these priors, we can combine that knowledge with the hitherto unimaginable statistical samples from LSST (∼millions of SNe), to better understand the early evolution and rise time distribution of Type Ia SNe.…”
Section: Discussionmentioning
confidence: 99%
“…These smaller, more focused, missions can provide exquisite observations of a select handful of SNe that can be used to drive the priors in our inference. While there have been thousands of SNe Ia studied to date (e.g., Jones et al 2017), more examples are indeed still needed: there are only four normal, z<0.03 SNe Ia in our sample, and these four are nearly as valuable as the entire remainder of the sample for establishing the diversity of SNe Ia. As low-z, high-cadence surveys improve our understanding of these priors, we can combine that knowledge with the hitherto unimaginable statistical samples from LSST (∼millions of SNe), to better understand the early evolution and rise time distribution of Type Ia SNe.…”
Section: Discussionmentioning
confidence: 99%
“…Examples include CC simulations to model contamination in photometrically identified SN Ia samples (Kessler et al 2010a;Rodney et al 2012;Kessler & Scolnic 2017;Jones et al 2017), and simulating Kilonovae (Barnes & Kasen 2013) to model the search efficiency (Soares-Santos et al 2016;Doctor et al 2017), and to predict discovery rates (Scolnic et al 2018a).…”
Section: A1 Sed Time Seriesmentioning
confidence: 99%
“…In current SN Ia photometric cosmological analyses, the effect of contamination is assessed using simulation techniques (Kunz et al 2007;Hlozek et al 2012;Kessler & Scolnic 2017), which are sensitive to how well the contamination can be modelled, rather than to the classification techniques used. The recent analysis of the photometric SN Ia sample from the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS 1; Jones et al 2017Jones et al , 2018 has shown that simulations of core collapse SNe using currently available template libraries and luminosity functions significantly underestimate the apparent core collapse SN contamination in the data, and a significant tuning of the underlying properties of the core collapse SN population is required.…”
Section: Introductionmentioning
confidence: 99%