Type Ia supernova colors and ejecta velocities: Hierarchical Bayesian regression with non-Gaussian distributions

Kaisey S. Mandel, Ryan J. Foley, Robert P. Kirshner

Research output: Contribution to journalArticlepeer-review

Abstract

We investigate the statistical dependence of the peak intrinsic colors of Type Ia supernovae (SNe Ia) on their expansion velocities at maximum light, measured from the Si II λ6355 spectral feature. We construct a new hierarchical Bayesian regression model, accounting for the random effects of intrinsic scatter, measurement error, and reddening by host galaxy dust, and implement a Gibbs sampler and deviance information criteria to estimate the correlation. The method is applied to the apparent colors from BVRI light curves and Si II velocity data for 79 nearby SNe Ia. The apparent color distributions of high-velocity (HV) and normal velocity (NV) supernovae exhibit significant discrepancies for B - V and B - R, but not other colors. Hence, they are likely due to intrinsic color differences originating in the B band, rather than dust reddening. The mean intrinsic B - V and B - R color differences between HV and NV groups are 0.06 ± 0.02 and 0.09 ± 0.02 mag, respectively. A linear model finds significant slopes of -0.021 ± 0.006 and -0.030 ± 0.009 mag (103 km s-1)-1 for intrinsic B - V and B - R colors versus velocity, respectively. Because the ejecta velocity distribution is skewed toward high velocities, these effects imply non-Gaussian intrinsic color distributions with skewness up to +0.3. Accounting for the intrinsic-color-velocity correlation results in corrections to AV extinction estimates as large as -0.12 mag for HV SNe Ia and +0.06 mag for NV events. Velocity measurements from SN Ia spectra have the potential to diminish systematic errors from the confounding of intrinsic colors and dust reddening affecting supernova distances.

Original languageEnglish (US)
Article number75
JournalAstrophysical Journal
Volume797
Issue number2
DOIs
StatePublished - Dec 20 2014

Keywords

  • Methods: statistical
  • Supernovae: general

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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