Search

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. [ABSTRACT FROM AUTHOR]

We present an empirical study of contamination in wide-field optical follow-up searches of gravitational wave sources from Advanced LIGO/Virgo using dedicated observations with the Dark Energy Camera. Our search covered ∼56 deg2, with two visits per night, in the i and z bands, followed by an additional set of griz images three weeks later to serve as reference images for subtraction. We achieve 5σ point-source limiting magnitudes of i ≈ 23.5 and z ≈ 22.4 mag in the coadded single-epoch images. We conduct a search for transient objects that mimic the i − z color behavior of both red (i−z > 0.5 mag) and blue (i−z < 0 mag) kilonova emission, finding 11 and 10 contaminants, respectively. Independent of color, we identify 48 transients of interest. Additionally, we leverage the rapid cadence of our observations to search for sources with characteristic timescales of ≈1 day and ≈3 hr, finding no potential contaminants. We assess the efficiency of our search with injected point sources, finding that we are 90% (60%) efficient when searching for red (blue) kilonova-like sources to a limiting magnitude of i ≲ 22.5 mag. Using our efficiencies, we derive sky rates for kilonova contaminants of deg−2 and deg−2. The total contamination rate is deg−2. We compare our results to previous optical follow-up efforts and comment on the outlook for gravitational wave follow-up searches as additional detectors (e.g., KAGRA, LIGO India) come online in the next decade. [ABSTRACT FROM AUTHOR]

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) = w0 + wa(1 − a), we find w0 = −0.912 ± 0.149 and wa = −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, , is the third-smallest source of systematic uncertainty in this work. We find limited (1.6σ) 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 ∼5% CC SN contamination can give competitive cosmological constraints when the contaminating distribution is marginalized over in a Bayesian framework. [ABSTRACT FROM AUTHOR]

The Pan-STARRS (PS1) Medium Deep Survey discovered over 5000 likely supernovae (SNe) but obtained spectral classifications for just 10% of its SN candidates. We measured spectroscopic host galaxy redshifts for 3147 of these likely SNe and estimate that ∼1000 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, w. Using the method of Bayesian Estimation Applied to Multiple Species (BEAMS), distances to SNe Ia and the contaminating CC SN distribution are simultaneously determined. We test light-curve-based SN classification priors for BEAMS as well as a new classification method that relies upon host galaxy spectra and the association of SN type with host type. By testing several SN classification methods and CC SN parameterizations on large SN simulations, we estimate that CC SN contamination gives a systematic error on w () of 0.014, 29% of the statistical uncertainty. Our best method gives , just 8% of the statistical uncertainty, but could be affected by incomplete knowledge of the CC SN distribution. This method determines the SALT2 color and shape coefficients, α and β, with ∼3% bias. However, we find that some variants require α and β to be fixed to known values for BEAMS to yield accurate measurements of w. Finally, the inferred abundance of bright CC SNe in our sample is greater than expected based on measured CC SN rates and luminosity functions. [ABSTRACT FROM AUTHOR]