Data-driven estimation of neutral pileup particle multiplicity in high-luminosity hadron collider environments

TL;DR

This paper introduces a novel data-driven method for estimating neutral pileup particle multiplicity in high-luminosity collider environments, enhancing pileup rejection by leveraging particle kinematic signatures.

Contribution

It proposes a new weighting technique based on particle kinematics, improving pileup estimation and suggesting combining multiple methods for better subtraction at high luminosity.

Findings

Effective estimation of neutral pileup particle density within events.

Complementarity of the new weights with existing methods.

Potential for improved pileup subtraction by combining different weights.

Abstract

The upcoming operation regimes of the Large Hadron Collider are going to place stronger requirements on the rejection of particles originating from pileup, i.e. from interactions between other protons. For this reason, particle weighting techniques have recently been proposed in order to subtract pileup at the level of individual particles. We describe a choice of weights that, unlike others that rely on particle proximity, exploits the particle-level kinematic signatures of the high-energy scattering and of the pileup interactions. We illustrate the use of the weights to estimate the number density of neutral pileup particles inside individual events, and we elaborate on the complementarity between ours and other methods. We conclude by suggesting the idea of combining different sets of weights with a view to exploiting different features of the underlying processes for improved pileup subtraction at higher luminosity.