FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION
Abstract
Wide-field surveys will soon be discovering Type Ia supernovae (SNe) at rates of several thousand per year. Spectroscopic follow-up can only scratch the surface for such enormous samples, so these extensive data sets will only be useful to the extent that they can be characterized by the survey photometry alone. In a companion paper we introduced the Supernova Ontology with Fuzzy Templates (SOFT) method for analyzing SNe using direct comparison to template light curves, and demonstrated its application for photometric SN classification. In this work we extend the SOFT method to derive estimates of redshift and luminosity distance for Type Ia SNe, using light curves from the Sloan Digital Sky Survey (SDSS) and Supernova Legacy Survey (SNLS) as a validation set. Redshifts determined by SOFT using light curves alone are consistent with spectroscopic redshifts, showing an rms scatter in the residuals of rms{sub z} = 0.051. SOFT can also derive simultaneous redshift and distance estimates, yielding results that are consistent with the currently favored {Lambda}CDM cosmological model. When SOFT is given spectroscopic information for SN classification and redshift priors, the rms scatter in Hubble diagram residuals is 0.18 mag for the SDSS data and 0.28 mag for the SNLS objects.more »
- Authors:
-
- Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States)
- Publication Date:
- OSTI Identifier:
- 21448745
- Resource Type:
- Journal Article
- Journal Name:
- Astrophysical Journal
- Additional Journal Information:
- Journal Volume: 715; Journal Issue: 1; Other Information: DOI: 10.1088/0004-637X/715/1/323; Journal ID: ISSN 0004-637X
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; COMPUTERIZED SIMULATION; COSMOLOGICAL MODELS; FUZZY LOGIC; GALAXIES; LUMINOSITY; MONTE CARLO METHOD; NONLUMINOUS MATTER; PHOTOMETRY; RED SHIFT; SUPERNOVAE; BINARY STARS; CALCULATION METHODS; ERUPTIVE VARIABLE STARS; MATHEMATICAL LOGIC; MATHEMATICAL MODELS; MATTER; OPTICAL PROPERTIES; PHYSICAL PROPERTIES; SIMULATION; STARS; VARIABLE STARS
Citation Formats
Rodney, Steven A, and Tonry, John L., E-mail: rodney@jhu.ed, E-mail: jt@ifa.hawaii.ed. FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION. United States: N. p., 2010.
Web. doi:10.1088/0004-637X/715/1/323.
Rodney, Steven A, & Tonry, John L., E-mail: rodney@jhu.ed, E-mail: jt@ifa.hawaii.ed. FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION. United States. https://doi.org/10.1088/0004-637X/715/1/323
Rodney, Steven A, and Tonry, John L., E-mail: rodney@jhu.ed, E-mail: jt@ifa.hawaii.ed. 2010.
"FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION". United States. https://doi.org/10.1088/0004-637X/715/1/323.
@article{osti_21448745,
title = {FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION},
author = {Rodney, Steven A and Tonry, John L., E-mail: rodney@jhu.ed, E-mail: jt@ifa.hawaii.ed},
abstractNote = {Wide-field surveys will soon be discovering Type Ia supernovae (SNe) at rates of several thousand per year. Spectroscopic follow-up can only scratch the surface for such enormous samples, so these extensive data sets will only be useful to the extent that they can be characterized by the survey photometry alone. In a companion paper we introduced the Supernova Ontology with Fuzzy Templates (SOFT) method for analyzing SNe using direct comparison to template light curves, and demonstrated its application for photometric SN classification. In this work we extend the SOFT method to derive estimates of redshift and luminosity distance for Type Ia SNe, using light curves from the Sloan Digital Sky Survey (SDSS) and Supernova Legacy Survey (SNLS) as a validation set. Redshifts determined by SOFT using light curves alone are consistent with spectroscopic redshifts, showing an rms scatter in the residuals of rms{sub z} = 0.051. SOFT can also derive simultaneous redshift and distance estimates, yielding results that are consistent with the currently favored {Lambda}CDM cosmological model. When SOFT is given spectroscopic information for SN classification and redshift priors, the rms scatter in Hubble diagram residuals is 0.18 mag for the SDSS data and 0.28 mag for the SNLS objects. Without access to any spectroscopic information, and even without any redshift priors from host galaxy photometry, SOFT can still measure reliable redshifts and distances, with an increase in the Hubble residuals to 0.37 mag for the combined SDSS and SNLS data set. Using Monte Carlo simulations, we predict that SOFT will be able to improve constraints on time-variable dark energy models by a factor of 2-3 with each new generation of large-scale SN surveys.},
doi = {10.1088/0004-637X/715/1/323},
url = {https://www.osti.gov/biblio/21448745},
journal = {Astrophysical Journal},
issn = {0004-637X},
number = 1,
volume = 715,
place = {United States},
year = {Thu May 20 00:00:00 EDT 2010},
month = {Thu May 20 00:00:00 EDT 2010}
}