Mass distributions marginalized over per-event errors
By D. M. Santos, F. Dupertuis. 2013
267 citations recorded by the source corpus.
We present generalizations of the Crystal Ball function to describe mass peaks in which the per event mass resolution is unknown and marginalized over. The presented probability density functions are tested using a series of toy Monte Carlo samples generated with Pythia and smeared with different amounts of multiple scattering and for different detector resolutions. (C) 2014 Elsevier B.V. All rights reserved.
Subfields: Nuclear and High Energy Physics, Radiation
View Paper: https://www.semanticscholar.org/paper/77c697100570b2b5ad4defc9d0dea416e7cd75b0
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In Nuclear and High Energy Physics
In Radiation
Citations in the corpus
- Measurement of the $J/\psi$ pair production cross-section in $pp$ collisions at $\sqrt{s} = 13 \,{\mathrm{TeV}}$ (2016, methodology): “The uncertainty due to the signal shape description is estimated by replacing the nominal model with two alternative models, the Hypatia function [86] and a kernel estimate for the underlying probability distribution function of the simulated sample convolved with a Gaussian function [87].”
- Observation of $J/\psi p$ Resonances Consistent with Pentaquark States in $\Lambda_b^0 \to J/\psi K^- p$ Decays (2015, methodology): “the Λb signal shape is parametrized by a double-sided Hypatia function [25], where the signal radiative tail parameters are fixed to values obtained from simulation.”