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Efficient treatment of systematic uncertainties that depend on a large numberof nuisance parameters is a persistent difficulty in particle physicsexperiments. Where low-level effects are not amenable to simpleparameterization or re-weighting, analyses often rely on discrete simulationsets to quantify the effects of nuisance parameters on key analysisobservables. Such methods may become computationally untenable for analysesrequiring high statistics Monte Carlo with a large number of nuisance degreesof freedom, especially in cases where these degrees of freedom parameterize theshape of a continuous distribution. In this paper we present a method fortreating systematic uncertainties in a computationally efficient andcomprehensive manner using a single simulation set with multiple andcontinuously varied nuisance parameters. This method is demonstrated for thecase of the depth-dependent effective dust distribution within the IceCubeNeutrino Telescope.

Efficient propagation of systematic uncertainties from calibration to analysis with the SnowStorm method in IceCube