Efficient propagation of systematic uncertainties from calibration to analysis with the SnowStorm method in IceCube
Name
1909.01530.pdf
Description
Submitted version
Size
5.78 MB
Format
Unknown
Checksum (MD5)
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Author(s)
Arguelles Delgado, Carlos A
Axani, Spencer Nicholas
Collin, G. H.
Conrad, Janet Marie
Diaz, Alejandro
Moulai, Marjon H.
Date Issued
2019
Journal
Journal of Cosmology and Astroparticle Physics
Publisher
IOP Publishing
Version
Original manuscript
Abstract
© 2019 IOP Publishing Ltd and Sissa Medialab. Efficient treatment of systematic uncertainties that depend on a large number of nuisance parameters is a persistent difficulty in particle physics and astrophysics experiments. Where low-level effects are not amenable to simple parameterization or re-weighting, analyses often rely on discrete simulation sets to quantify the effects of nuisance parameters on key analysis observables. Such methods may become computationally untenable for analyses requiring high statistics Monte Carlo with a large number of nuisance degrees of freedom, especially in cases where these degrees of freedom parameterize the shape of a continuous distribution. In this paper we present a method for treating systematic uncertainties in a computationally efficient and comprehensive manner using a single simulation set with multiple and continuously varied nuisance parameters. This method is demonstrated for the case of the depth-dependent effective dust distribution within the IceCube Neutrino Telescope.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1088/1475-7516/2019/10/048
