Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/19345
Title: | Particle-level kinematic fingerprints and the multiplicity of neutral particles from low-energy strong interactions |
Authors: | Colecchia, F |
Keywords: | 29.85.F;high energy physics;particle physics;Large Hadron Collider;LCH;background discrimination;mixture models;latent variable models;sampling;Gibbs sample;Markov Chain Monte Carlo;expectation maximisation |
Issue Date: | 2014 |
Publisher: | Cornell University |
Citation: | arXiv:1412.1989 [hep-ph] (17 pp.) |
Abstract: | [arXiv] The contamination, or background, from uninteresting low-energy strong interactions is a major issue for data analysis at the Large Hadron Collider. In the light of the challenges associated with the upcoming higher-luminosity scenarios, methods of assigning weights to individual particles have recently started to be used with a view to rescaling the particle four-momentum vectors. We propose a different approach whereby the weights are instead employed to reshape the particle-level kinematic distributions in the data. We use this method to estimate the number of neutral particles originating from low-energy strong interactions in different kinematic regions inside individual collision events. Given the parallel nature of this technique, we anticipate the possibility of using it as part of particle-by-particle event filtering procedures at the reconstruction level at future high-luminosity hadron collider experiments. |
URI: | https://bura.brunel.ac.uk/handle/2438/19345 https://arxiv.org/abs/1412.1989 |
Appears in Collections: | Dept of Computer Science Research Papers |
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