Recognition: unknown
Penalized Splines for Smooth Representation of High-dimensional Monte Carlo Datasets
read the original abstract
Detector response to a high-energy physics process is often estimated by Monte Carlo simulation. For purposes of data analysis, the results of this simulation are typically stored in large multi-dimensional histograms, which can quickly become both too large to easily store and manipulate and numerically problematic due to unfilled bins or interpolation artifacts. We describe here an application of the penalized spline technique to efficiently compute B-spline representations of such tables and discuss aspects of the resulting B-spline fits that simplify many common tasks in handling tabulated Monte Carlo data in high-energy physics analysis, in particular their use in maximum-likelihood fitting.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
Probabilistic modeling of Cherenkov emission from particle showers
Probabilistic distributions are built for Cherenkov emission parameters from particle showers to model fluctuations in amplitude and shape along the shower axis for neutrino telescope simulations.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.