Standardizing type Ia supernova absolute magnitudes using Gaussian process data regression
Date
2013
Authors
Kim, Alex G
Thomas, R. C.
Aldering, G
Antilogus, P
Aragon, C
Bailey, S
Baltay, C
Bongard, S
Buton, C
Canto, A
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IOP Publishing
Abstract
We present a novel class of models for Type Ia supernova time-evolving spectral energy distributions (SEDs) and absolute magnitudes: they are each modeled as stochastic functions described by Gaussian processes. The values of the SED and absolute magnitudes are defined through well-defined regression prescriptions, so that data directly inform the models. As a proof of concept, we implement a model for synthetic photometry built from the spectrophotometric time series from the Nearby Supernova Factory. Absolute magnitudes at peak B brightness are calibrated to 0.13 mag in the g band and to as low as 0.09 mag in the z = 0.25 blueshifted i band, where the dispersion includes contributions from measurement uncertainties and peculiar velocities. The methodology can be applied to spectrophotometric time series of supernovae that span a range of redshifts to simultaneously standardize supernovae together with fitting cosmological parameters.
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Keywords
Keywords: distance scale; methods: data analysis; supernovae: general
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Source
Astrophysical Journal, The
Type
Journal article
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Restricted until
2037-12-31
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