The Foundation Supernova Survey: Measuring Cosmological Parameters with Supernovae from a Single Telescope

David O Jones ,R J Wainscoat,M E Huber,S J Smartt,M R Siebert,R J Foley,E Berger,C Waters,M Willman,E A Magnier,D A Coulter,A S B Schultz,A Rest,H Flewelling,Y.-C Pan,R Chornock,C D Kilpatrick,Michael Foley ,K Dettman ,Adam G Riess ,Gautham Narayan ,R Keßler ,Joseph Manuel ,R Kirshner ,Saurabh W Jha ,K Smith ,P Challis ,K Chambers ,Emily Johnson ,D Scolnic

doi:10.3847/1538-4357/ab2bec

Abstract

Abstract Measurements of the dark energy equation-of-state parameter, w, have been limited by uncertainty in the selection effects and photometric calibration of z < 0.1 Type Ia supernovae (SNe Ia). The Foundation Supernova Survey is designed to lower these uncertainties by creating a new sample of z < 0.1 SNe Ia observed on the Pan-STARRS system. Here we combine the Foundation sample with SNe from the Pan-STARRS Medium Deep Survey and measure cosmological parameters with 1338 SNe from a single telescope and a single, well-calibrated photometric system. For the first time, both the low-z and high-z data are predominantly discovered by surveys that do not target preselected galaxies, reducing selection bias uncertainties. The z > 0.1 data include 875 SNe without spectroscopic classifications, and we show that we can robustly marginalize over CC SN contamination. We measure Foundation Hubble residuals to be fainter than the preexisting low-z Hubble residuals by 0.046 ± 0.027 mag (stat + sys). By combining the SN Ia data with cosmic microwave background constraints, we find w = −0.938 ± 0.053, consistent with ΛCDM. With 463 spectroscopically classified SNe Ia alone, we measure w = −0.933 ± 0.061. Using the more homogeneous and better-characterized Foundation sample gives a 55% reduction in the systematic uncertainty attributed to SN Ia sample selection biases. Although use of just a single photometric system at low and high redshift increases the impact of photometric calibration uncertainties in this analysis, previous low-z samples may have correlated calibration uncertainties that were neglected in past studies. The full Foundation sample will observe up to 800 SNe to anchor the LSST and WFIRST Hubble diagrams.

Highlights

For Photometric Supernovae with BEAMS method (PSBEAMS) we use PSNID as the baseline classifier for determining prior probabilities that a given SN is of Type Ia and Nearest Neighbor (NN) as the baseline classifier for BEAMS with Bias Corrections method (BBC), as we found that excluding a linear shift parameter can give biased results when using PSNID probabilities
Distances and cosmological parameters for the combination of CfA, CSP, and Medium Deep Survey (MDS) SNe were reported in J18; we begin with the PSBEAMS method from J18 of correcting for distance biases and marginalizing over CC SNe to allow a direct comparison to the J18 results
We discuss the results from the alternate BBC method, which reduces the dispersion of the SN Ia sample and improves the precision of the results, albeit with additional differences in methodology

Summary

Introduction

Since the discovery of dark energy 20 years ago (Riess et al 1998; Perlmutter et al 1999), measurements of the dark energy equation-of-state parameter, w, have been steadily improving (Garnavich et al 1998; Knop et al 2003; Tonry et al 2003; Riess et al 2004, 2007; Astier et al 2006; Wood-Vasey et al 2007; Kowalski et al 2008; Kessler et al 2009; Sullivan et al 2011; Betoule et al 2014; Scolnic et al 2018). In support of a better understanding of dark energy, recent cosmic microwave background (CMB) experiments have yielded improved. As Type Ia supernova (SN Ia) sample sizes have steadily increased, their systematic uncertainties have steadily decreased. Their reduced systematic uncertainties are primarily due to improvements in photometric calibration and a better understanding of the ways in which

Methods

Results

Conclusion