Detection of invisible particles at hadron collider experiments through the magnetic spectrometer

TL;DR

This paper introduces a novel spectrometer-based technique to detect invisible particles at hadron colliders, improving background rejection and background modeling in complex event topologies, validated with data and simulations from the CDF II detector.

Contribution

It presents a new method combining spectrometer and calorimeter data to infer invisible particles, applicable across various event topologies at hadron colliders.

Findings

Technique validated with CDF II data and simulations

Effective in events with multiple jets and invisible particles

Provides a new approach to measure QCD multijet backgrounds

Abstract

The production of invisible particles plays great importance in high energy physics. Large part of interesting electroweak processes include production of neutrinos, while many new physics scenarios predict the existence of similarly weakly-interacting particles. In events with associated production of invisible particles and hadronic jets, the measurement of the imbalance in transverse momentum of the final state particles is the major leverage to reject the otherwise dominant source of backgrounds in hadron colliders, i.e. the generic production of many jets by QCD interactions. Here we discuss a novel technique which utilizes the information derived from the spectrometer, eventually coupled with the more straightforward calorimeter information, to infer the passage of invisible particles. We check the validity of this technique in data and Monte Carlo simulations in a broad range of topologies, starting from the simplest, with two jets in the final state, to the ones with very large jet multiplicities. We also suggest a new way, based on the same approach, to measure the yields and model the kinematics of the QCD multijet background in invisible particles plus jets signatures. The results are derived using data collected with the CDF II detector; we argue that the application to LHC experiments is straightforward.