Improving cosmological distance measurements using twin type Ia supernovae
Journal Article
·
· The Astrophysical Journal (Online)
We introduce a method for identifying “twin” Type Ia supernovae (SNe Ia) and using them to improve distance measurements. This novel approach to SN Ia standardization is made possible by spectrophotometric time series observations from the Nearby Supernova Factory (SNfactory). We begin with a well-measured set of SNe, find pairs whose spectra match well across the entire optical window, and then test whether this leads to a smaller dispersion in their absolute brightnesses. This analysis is completed in a blinded fashion, ensuring that decisions made in implementing the method do not inadvertently bias the result. We find that pairs of SNe with more closely matched spectra indeed have reduced brightness dispersion. We are able to standardize this initial set of SNfactory SNe to 0.083 ± 0.012 mag, implying a dispersion of 0.072 ± 0.010 mag in the absence of peculiar velocities. We estimate that with larger numbers of comparison SNe, e.g., using the final SNfactory spectrophotometric data set as a reference, this method will be capable of standardizing high-redshift SNe to within 0.06–0.07 mag. Finally, these results imply that at least 3/4 of the variance in Hubble residuals in current SN cosmology analyses is due to previously unaccounted-for astrophysical differences among the SNe.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
- Contributing Organization:
- The Nearby Supernova Factory
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1465697
- Alternate ID(s):
- OSTI ID: 22521785
- Journal Information:
- The Astrophysical Journal (Online), Journal Name: The Astrophysical Journal (Online) Journal Issue: 1 Vol. 815; ISSN 1538-4357
- Publisher:
- Institute of Physics (IOP)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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