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Standardizing type Ia supernova absolute magnitudes using Gaussian process data regression

Kim, Alex G; Thomas, R. C.; Aldering, G; Antilogus, P; Aragon, C; Bailey, S; Baltay, C; Bongard, S; Buton, C; Canto, A; Cellier-Holzem, F; Childress, M; Chotard, N; Copin, Y; Fakhouri, H K; Gangler, E; Guy, J; Kerschhaggl, M; Kowalski, M; Nordin, J; Nugent, Peter; Paech, K; Scalzo, Richard

Description

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...[Show more]

dc.contributor.authorKim, Alex G
dc.contributor.authorThomas, R. C.
dc.contributor.authorAldering, G
dc.contributor.authorAntilogus, P
dc.contributor.authorAragon, C
dc.contributor.authorBailey, S
dc.contributor.authorBaltay, C
dc.contributor.authorBongard, S
dc.contributor.authorButon, C
dc.contributor.authorCanto, A
dc.contributor.authorCellier-Holzem, F
dc.contributor.authorChildress, M
dc.contributor.authorChotard, N
dc.contributor.authorCopin, Y
dc.contributor.authorFakhouri, H K
dc.contributor.authorGangler, E
dc.contributor.authorGuy, J
dc.contributor.authorKerschhaggl, M
dc.contributor.authorKowalski, M
dc.contributor.authorNordin, J
dc.contributor.authorNugent, Peter
dc.contributor.authorPaech, K
dc.contributor.authorScalzo, Richard
dc.date.accessioned2015-12-13T22:22:42Z
dc.identifier.issn0004-637X
dc.identifier.urihttp://hdl.handle.net/1885/72378
dc.description.abstractWe 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.
dc.publisherIOP Publishing
dc.sourceAstrophysical Journal, The
dc.subjectKeywords: distance scale; methods: data analysis; supernovae: general
dc.titleStandardizing type Ia supernova absolute magnitudes using Gaussian process data regression
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume766
dc.date.issued2013
local.identifier.absfor020100 - ASTRONOMICAL AND SPACE SCIENCES
local.identifier.ariespublicationf5625xPUB3216
local.identifier.ariespublicationu4630950xPUB164
local.type.statusPublished Version
local.contributor.affiliationKim, Alex G, Lawrence Berkeley National Laboratory
local.contributor.affiliationThomas, R. C., Lawrence Berkeley National Laboratory
local.contributor.affiliationAldering, G, Lawrence Berkeley National Laboratory
local.contributor.affiliationAntilogus, P, Universite Pierre et Marie Curie Paris
local.contributor.affiliationAragon, C, Lawrence Berkeley National Laboratory
local.contributor.affiliationBailey, S, Lawrence Berkeley National Laboratory
local.contributor.affiliationBaltay, C, Yale University
local.contributor.affiliationBongard, S, Université Pierre et Marie Curie Paris 6
local.contributor.affiliationButon, C, Universität Bonn
local.contributor.affiliationCanto, A, Université Pierre et Marie Curie Paris 6,
local.contributor.affiliationCellier-Holzem, F, Universite Pierre et Marie Curie Paris
local.contributor.affiliationChildress, M, Lawrence Berkeley National Laboratory
local.contributor.affiliationChotard, N, Tsinghua University
local.contributor.affiliationCopin, Y, Université de Lyon
local.contributor.affiliationFakhouri, H K, University of California
local.contributor.affiliationGangler, E, Université de Lyon
local.contributor.affiliationGuy, J, Universite Pierre et Marie Curie Paris 6
local.contributor.affiliationKerschhaggl, M, Universitat Bonn
local.contributor.affiliationKowalski, M, Universitat Bonn
local.contributor.affiliationNordin, J, Lawrence Berkeley National Laboratory
local.contributor.affiliationNugent, Peter, Lawrence Berkeley National Laboratory
local.contributor.affiliationPaech, K, Universitat Bonn
local.contributor.affiliationScalzo, Richard, College of Physical and Mathematical Sciences, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.issue2
local.bibliographicCitation.startpage84
local.identifier.doi10.1088/0004-637X/766/2/84
dc.date.updated2016-02-24T09:06:44Z
local.identifier.scopusID2-s2.0-84875448603
local.identifier.thomsonID000316320900018
CollectionsANU Research Publications

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