Particle-level kinematic fingerprints and the multiplicity of neutral particles from low-energy strong interactions

TL;DR

This paper introduces a novel method for estimating neutral particle multiplicity from low-energy strong interactions by reshaping particle kinematic distributions, aiding data analysis at high-luminosity colliders.

Contribution

The paper presents a new approach that uses particle weights to reshape kinematic distributions, improving neutral particle estimation in collider data analysis.

Findings

Effective estimation of neutral particle multiplicity in various kinematic regions.

Potential application in particle-by-particle event filtering at future colliders.

Method demonstrates parallel processing capabilities for high-luminosity scenarios.

Abstract

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.