Standardizing Type Ia Supernova Absolute Magnitudes Using Gaussian Process Data Regression
A. G. Kim
,
R. C. Thomas
,
G. Aldering
,
P. Antilogus
(1)
,
C. Aragon
,
S. Bailey
,
C. Baltay
,
S. Bongard
(1)
,
C. Buton
,
A. Canto
(1)
,
F. Cellier-Holzem
(1)
,
M. Childress
,
N. Chotard
,
Y. Copin
(2)
,
H. K. Fakhouri
,
E. Gangler
(2)
,
J. Guy
(1)
,
M. Kerschhaggl
,
M. Kowalski
,
J. Nordin
,
P. Nugent
,
K. Paech
,
R. Pain
(1)
,
E. Pécontal
(3)
,
R. Pereira
(2)
,
S. Perlmutter
,
D. Rabinowitz
,
M. Rigault
(2)
,
K. Runge
,
C. Saunders
,
R. Scalzo
,
G. Smadja
(2)
,
C. Tao
(4)
,
B. A. Weaver
,
C. Wu
(1)
A. G. Kim
- Function : Author
R. C. Thomas
- Function : Author
G. Aldering
- Function : Author
P. Antilogus
- Function : Author
- PersonId : 741722
- IdHAL : pierre-antilogus
- ORCID : 0000-0002-0389-5706
- IdRef : 116029315
C. Aragon
- Function : Author
S. Bailey
- Function : Author
C. Baltay
- Function : Author
S. Bongard
- Function : Author
- PersonId : 742831
- IdHAL : sebastien-bongard
C. Buton
- Function : Author
M. Childress
- Function : Author
N. Chotard
- Function : Author
Y. Copin
- Function : Author
- PersonId : 48
- IdHAL : yannick-copin
- ORCID : 0000-0002-5317-7518
- IdRef : 15009728X
H. K. Fakhouri
- Function : Author
M. Kerschhaggl
- Function : Author
M. Kowalski
- Function : Author
J. Nordin
- Function : Author
P. Nugent
- Function : Author
K. Paech
- Function : Author
R. Pain
- Function : Author
- PersonId : 742459
- IdHAL : reynald-pain
- ORCID : 0000-0003-4016-6067
- IdRef : 033075735
S. Perlmutter
- Function : Author
D. Rabinowitz
- Function : Author
M. Rigault
- Function : Author
- PersonId : 750032
- IdHAL : mickael-rigault
K. Runge
- Function : Author
C. Saunders
- Function : Author
R. Scalzo
- Function : Author
B. A. Weaver
- Function : Author
Abstract
We present a novel class of models for Type Ia supernova time-evolving spectral energy distributions (SED) 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.