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Abstract: Measurements of the equation of state of dark energy from surveys ofthousands of Type Ia Supernovae SNe Ia will be limited by spectroscopicfollow-up and must therefore rely on photometric identification, increasing thechance that the sample is contaminated by Core Collapse Supernovae CC SNe.Bayesian methods for supernova cosmology can remove contamination bias whilemaintaining high statistical precision but are sensitive to the choice ofparameterization of the contaminating distance distribution. We use simulationsto investigate the form of the contaminating distribution and its dependence onthe absolute magnitudes, light curve shapes, colors, extinction, and redshiftsof core collapse supernovae. We find that the CC luminosity function dominatesthe distance distribution function, but its shape is increasingly distorted asthe redshift increases and more CC SNe fall below the survey magnitude limit.The shapes and colors of the CC light curves generally shift the distancedistribution, and their effect on the CC distances is correlated. We comparethe simulated distances to the first year results of the SDSS-II SN survey andfind that the SDSS distance distributions can be reproduced with simulated CCSNe that are ~1 mag fainter than the standard Richardson et al. 2002luminosity functions, which do not produce a good fit. To exploit the fullpower of the Bayesian parameter estimation method, parameterization of thecontaminating distribution should be guided by the current knowledge of the CCluminosity functions, coupled with the effects of the survey selection andmagnitude-limit, and allow for systematic shifts caused by the parameters ofthe distance fit.



Autor: Bridget L. Falck, Adam G. Riess, Renee Hlozek

Fuente: https://arxiv.org/







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