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Title: Systematic uncertainties associated with the cosmological analysis of the first Pan-STARRS1 type Ia supernova sample

Abstract

We probe the systematic uncertainties from the 113 Type Ia supernovae (SN Ia) in the Pan-STARRS1 (PS1) sample along with 197 SN Ia from a combination of low-redshift surveys. The companion paper by Rest et al. describes the photometric measurements and cosmological inferences from the PS1 sample. The largest systematic uncertainty stems from the photometric calibration of the PS1 and low-z samples. We increase the sample of observed Calspec standards from 7 to 10 used to define the PS1 calibration system. The PS1 and SDSS-II calibration systems are compared and discrepancies up to ∼0.02 mag are recovered. We find uncertainties in the proper way to treat intrinsic colors and reddening produce differences in the recovered value of w up to 3%. We estimate masses of host galaxies of PS1 supernovae and detect an insignificant difference in distance residuals of the full sample of 0.037 ± 0.031 mag for host galaxies with high and low masses. Assuming flatness and including systematic uncertainties in our analysis of only SNe measurements, we find w =−1.120{sub −0.206}{sup +0.360}(Stat){sub −0.291}{sup +0.269}(Sys). With additional constraints from Baryon acoustic oscillation, cosmic microwave background (CMB) (Planck) and H {sub 0} measurements, we find w=−1.166{sub −0.069}{sup +0.072} and Ω{submore » m}=0.280{sub −0.012}{sup +0.013} (statistical and systematic errors added in quadrature). The significance of the inconsistency with w = –1 depends on whether we use Planck or Wilkinson Microwave Anisotropy Probe measurements of the CMB: w{sub BAO+H0+SN+WMAP}=−1.124{sub −0.065}{sup +0.083}.« less

Authors:
; ; ;  [1];  [2]; ;  [3]; ; ; ; ; ; ; ; ;  [4];  [5]; ;  [6];  [7] more »; « less
  1. Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States)
  2. Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States)
  3. Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States)
  4. Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States)
  5. Department of Physics, Harvard University, 17 Oxford Street, Cambridge, MA 02138 (United States)
  6. Astrophysics Research Centre, School of Mathematics and Physics, Queens University Belfast, Belfast BT7 1NN (United Kingdom)
  7. Max Planck Institute for Astronomy, Konigstuhl 17, D-69117 Heidelberg (Germany)
Publication Date:
OSTI Identifier:
22370309
Resource Type:
Journal Article
Resource Relation:
Journal Name: Astrophysical Journal; Journal Volume: 795; Journal Issue: 1; Other Information: Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; ANISOTROPY; CALIBRATION; COLOR; COMPARATIVE EVALUATIONS; DISTANCE; GALAXIES; MASS; NONLUMINOUS MATTER; OSCILLATIONS; QUADRATURES; RED SHIFT; RELICT RADIATION; TYPE I SUPERNOVAE

Citation Formats

Scolnic, D., Riess, A., Brout, D., Rodney, S., Rest, A., Huber, M. E., Tonry, J. L., Foley, R. J., Chornock, R., Berger, E., Soderberg, A. M., Stubbs, C. W., Kirshner, R. P., Challis, P., Czekala, I., Drout, M., Narayan, G., Smartt, S. J., Botticella, M. T., Schlafly, E., and and others. Systematic uncertainties associated with the cosmological analysis of the first Pan-STARRS1 type Ia supernova sample. United States: N. p., 2014. Web. doi:10.1088/0004-637X/795/1/45.
Scolnic, D., Riess, A., Brout, D., Rodney, S., Rest, A., Huber, M. E., Tonry, J. L., Foley, R. J., Chornock, R., Berger, E., Soderberg, A. M., Stubbs, C. W., Kirshner, R. P., Challis, P., Czekala, I., Drout, M., Narayan, G., Smartt, S. J., Botticella, M. T., Schlafly, E., & and others. Systematic uncertainties associated with the cosmological analysis of the first Pan-STARRS1 type Ia supernova sample. United States. doi:10.1088/0004-637X/795/1/45.
Scolnic, D., Riess, A., Brout, D., Rodney, S., Rest, A., Huber, M. E., Tonry, J. L., Foley, R. J., Chornock, R., Berger, E., Soderberg, A. M., Stubbs, C. W., Kirshner, R. P., Challis, P., Czekala, I., Drout, M., Narayan, G., Smartt, S. J., Botticella, M. T., Schlafly, E., and and others. Sat . "Systematic uncertainties associated with the cosmological analysis of the first Pan-STARRS1 type Ia supernova sample". United States. doi:10.1088/0004-637X/795/1/45.
@article{osti_22370309,
title = {Systematic uncertainties associated with the cosmological analysis of the first Pan-STARRS1 type Ia supernova sample},
author = {Scolnic, D. and Riess, A. and Brout, D. and Rodney, S. and Rest, A. and Huber, M. E. and Tonry, J. L. and Foley, R. J. and Chornock, R. and Berger, E. and Soderberg, A. M. and Stubbs, C. W. and Kirshner, R. P. and Challis, P. and Czekala, I. and Drout, M. and Narayan, G. and Smartt, S. J. and Botticella, M. T. and Schlafly, E. and and others},
abstractNote = {We probe the systematic uncertainties from the 113 Type Ia supernovae (SN Ia) in the Pan-STARRS1 (PS1) sample along with 197 SN Ia from a combination of low-redshift surveys. The companion paper by Rest et al. describes the photometric measurements and cosmological inferences from the PS1 sample. The largest systematic uncertainty stems from the photometric calibration of the PS1 and low-z samples. We increase the sample of observed Calspec standards from 7 to 10 used to define the PS1 calibration system. The PS1 and SDSS-II calibration systems are compared and discrepancies up to ∼0.02 mag are recovered. We find uncertainties in the proper way to treat intrinsic colors and reddening produce differences in the recovered value of w up to 3%. We estimate masses of host galaxies of PS1 supernovae and detect an insignificant difference in distance residuals of the full sample of 0.037 ± 0.031 mag for host galaxies with high and low masses. Assuming flatness and including systematic uncertainties in our analysis of only SNe measurements, we find w =−1.120{sub −0.206}{sup +0.360}(Stat){sub −0.291}{sup +0.269}(Sys). With additional constraints from Baryon acoustic oscillation, cosmic microwave background (CMB) (Planck) and H {sub 0} measurements, we find w=−1.166{sub −0.069}{sup +0.072} and Ω{sub m}=0.280{sub −0.012}{sup +0.013} (statistical and systematic errors added in quadrature). The significance of the inconsistency with w = –1 depends on whether we use Planck or Wilkinson Microwave Anisotropy Probe measurements of the CMB: w{sub BAO+H0+SN+WMAP}=−1.124{sub −0.065}{sup +0.083}.},
doi = {10.1088/0004-637X/795/1/45},
journal = {Astrophysical Journal},
number = 1,
volume = 795,
place = {United States},
year = {Sat Nov 01 00:00:00 EDT 2014},
month = {Sat Nov 01 00:00:00 EDT 2014}
}
  • We present griz {sub P1} light curves of 146 spectroscopically confirmed Type Ia supernovae (SNe Ia; 0.03 < z < 0.65) discovered during the first 1.5 yr of the Pan-STARRS1 Medium Deep Survey. The Pan-STARRS1 natural photometric system is determined by a combination of on-site measurements of the instrument response function and observations of spectrophotometric standard stars. We find that the systematic uncertainties in the photometric system are currently 1.2% without accounting for the uncertainty in the Hubble Space Telescope Calspec definition of the AB system. A Hubble diagram is constructed with a subset of 113 out of 146 SNemore » Ia that pass our light curve quality cuts. The cosmological fit to 310 SNe Ia (113 PS1 SNe Ia + 222 light curves from 197 low-z SNe Ia), using only supernovae (SNe) and assuming a constant dark energy equation of state and flatness, yields w=−1.120{sub −0.206}{sup +0.360}(Stat){sub −0.291}{sup +0.269}(Sys). When combined with BAO+CMB(Planck)+H {sub 0}, the analysis yields Ω{sub M}=0.280{sub −0.012}{sup +0.013} and w=−1.166{sub −0.069}{sup +0.072} including all identified systematics. The value of w is inconsistent with the cosmological constant value of –1 at the 2.3σ level. Tension endures after removing either the baryon acoustic oscillation (BAO) or the H {sub 0} constraint, though it is strongest when including the H {sub 0} constraint. If we include WMAP9 cosmic microwave background (CMB) constraints instead of those from Planck, we find w=−1.124{sub −0.065}{sup +0.083}, which diminishes the discord to <2σ. We cannot conclude whether the tension with flat ΛCDM is a feature of dark energy, new physics, or a combination of chance and systematic errors. The full Pan-STARRS1 SN sample with ∼three times as many SNe should provide more conclusive results.« less
  • In recent years, wide-field sky surveys providing deep multiband imaging have presented a new path for indirectly characterizing the progenitor populations of core-collapse supernovae (SNe): systematic light-curve studies. We assemble a set of 76 grizy-band Type IIP SN light curves from Pan-STARRS1, obtained over a constant survey program of 4 yr and classified using both spectroscopy and machine-learning-based photometric techniques. We develop and apply a new Bayesian model for the full multiband evolution of each light curve in the sample. We find no evidence of a subpopulation of fast-declining explosions (historically referred to as ''Type IIL'' SNe). However, we identify a highly significantmore » relation between the plateau phase decay rate and peak luminosity among our SNe IIP. These results argue in favor of a single parameter, likely determined by initial stellar mass, predominantly controlling the explosions of red supergiants. This relation could also be applied for SN cosmology, offering a standardizable candle good to an intrinsic scatter of ≲ 0.2 mag. We compare each light curve to physical models from hydrodynamic simulations to estimate progenitor initial masses and other properties of the Pan-STARRS1 Type IIP SN sample. We show that correction of systematic discrepancies between modeled and observed SN IIP light-curve properties and an expanded grid of progenitor properties are needed to enable robust progenitor inferences from multiband light-curve samples of this kind. This work will serve as a pathfinder for photometric studies of core-collapse SNe to be conducted through future wide-field transient searches.« less
  • An analysis of the first set of low-redshift (z < 0.08) Type Ia supernovae (SNe Ia) monitored by the Carnegie Supernova Project between 2004 and 2006 is presented. The data consist of well-sampled, high-precision optical (ugriBV) and near-infrared (NIR; YJHK{sub s} ) light curves in a well-understood photometric system. Methods are described for deriving light-curve parameters, and for building template light curves which are used to fit SN Ia data in the ugriBVYJH bands. The intrinsic colors at maximum light are calibrated using a subsample of supernovae (SNe) assumed to have suffered little or no reddening, enabling color excesses tomore » be estimated for the full sample. The optical-NIR color excesses allow the properties of the reddening law in the host galaxies to be studied. A low average value of the total-to-selective absorption coefficient, R{sub V} {approx} 1.7, is derived when using the entire sample of SNe. However, when the two highly reddened SNe (SN 2005A and SN 2006X) in the sample are excluded, a value R{sub V} {approx} 3.2 is obtained, similar to the standard value for the Galaxy. The red colors of these two events are well matched by a model where multiple scattering of photons by circumstellar dust steepens the effective extinction law. The absolute peak magnitudes of the SNe are studied in all bands using a two-parameter linear fit to the decline rates and the colors at maximum light, or alternatively, the color excesses. In both cases, similar results are obtained with dispersions in absolute magnitudes of 0.12-0.16 mag, depending on the specific filter-color combination. In contrast to the results obtained from the comparison of the color excesses, these fits of absolute magnitude give R{sub V} {approx} 1-2 when the dispersion is minimized, even when the two highly reddened SNe are excluded. This discrepancy suggests that, beyond the 'normal' interstellar reddening produced in the host galaxies, there is an intrinsic dispersion in the colors of SNe Ia which is correlated with luminosity but independent of the decline rate. Finally, a Hubble diagram for the best-observed subsample of SNe is produced by combining the results of the fits of absolute magnitude versus decline rate and color excess for each filter. The resulting scatter of 0.12 mag appears to be limited by the peculiar velocities of the host galaxies as evidenced by the strong correlation between the distance-modulus residuals observed in the individual filters. The implication is that the actual precision of SNe Ia distances is 3%-4%.« less
  • We use simulated type Ia supernova (SN Ia) samples, including both photometry and spectra, to perform the first direct validation of cosmology analysis using the SALT-II light curve model. This validation includes residuals from the light curve training process, systematic biases in SN Ia distance measurements, and a bias on the dark energy equation of state parameter w. Using the SN-analysis package SNANA, we simulate and analyze realistic samples corresponding to the data samples used in the SNLS3 analysis: ~120 low-redshift (z < 0.1) SNe Ia, ~255 Sloan Digital Sky Survey SNe Ia (z < 0.4), and ~290 SNLS SNemore » Ia (z ≤ 1). To probe systematic uncertainties in detail, we vary the input spectral model, the model of intrinsic scatter, and the smoothing (i.e., regularization) parameters used during the SALT-II model training. Using realistic intrinsic scatter models results in a slight bias in the ultraviolet portion of the trained SALT-II model, and w biases (w (input) – w (recovered)) ranging from –0.005 ± 0.012 to –0.024 ± 0.010. These biases are indistinguishable from each other within the uncertainty, the average bias on w is –0.014 ± 0.007.« less
  • We use simulated type Ia supernova (SN Ia) samples, including both photometry and spectra, to perform the first direct validation of cosmology analysis using the SALT-II light curve model. This validation includes residuals from the light curve training process, systematic biases in SN Ia distance measurements, and a bias on the dark energy equation of state parameter w. Using the SN-analysis package SNANA, we simulate and analyze realistic samples corresponding to the data samples used in the SNLS3 analysis: ∼120 low-redshift (z < 0.1) SNe Ia, ∼255 Sloan Digital Sky Survey SNe Ia (z < 0.4), and ∼290 SNLS SNemore » Ia (z ≤ 1). To probe systematic uncertainties in detail, we vary the input spectral model, the model of intrinsic scatter, and the smoothing (i.e., regularization) parameters used during the SALT-II model training. Using realistic intrinsic scatter models results in a slight bias in the ultraviolet portion of the trained SALT-II model, and w biases (w {sub input} – w {sub recovered}) ranging from –0.005 ± 0.012 to –0.024 ± 0.010. These biases are indistinguishable from each other within the uncertainty; the average bias on w is –0.014 ± 0.007.« less