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BEAMS: separating the wheat from the chaff in supernova analysis

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arxiv 1210.7762 v1 pith:AJ24CRBS submitted 2012-10-29 astro-ph.IM astro-ph.COphysics.data-anstat.AP

BEAMS: separating the wheat from the chaff in supernova analysis

Martin Kunz , Ren\'ee Hlozek , Bruce A. Bassett , Mathew Smith , James Newling , Melvin Varughese This is my paper
classification astro-ph.IM astro-ph.COphysics.data-anstat.AP
keywords algorithmbeamsdataestimationsupernovaanalysisappliedapply
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We introduce Bayesian Estimation Applied to Multiple Species (BEAMS), an algorithm designed to deal with parameter estimation when using contaminated data. We present the algorithm and demonstrate how it works with the help of a Gaussian simulation. We then apply it to supernova data from the Sloan Digital Sky Survey (SDSS), showing how the resulting confidence contours of the cosmological parameters shrink significantly.

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  1. BayeSN $\times$ Dovekie: Joint Photometric Cross-calibration and SED Modelling of Type Ia Supernovae

    astro-ph.CO 2026-06 unverdicted novelty 7.0

    Joint photometric cross-calibration and SED modeling in BayeSN yields G26 model with 12% NMAD scatter reduction on DES-SN5YR supernovae at z<0.7.