Chasing New Physics in Stacks of Soft Tracks

TL;DR

This paper introduces a new variable, ξ, based on soft tracks associated with the primary vertex, which enhances the detection of new physics signals in monojet plus missing transverse momentum searches, outperforming traditional analysis methods.

Contribution

The paper proposes using the variable ξ, binned in p_T, to improve discrimination of new physics events from background, demonstrating its effectiveness and robustness against pile-up.

Findings

ξ can distinguish new physics from Z+jets background

Combining ξ with traditional variables increases discovery potential by over 200%

Simple cuts on ξ outperform complex multivariate analyses

Abstract

In this letter we introduce a new variable $\xi$, namely the number of tracks associated with the primary vertex, which are not parts of reconstructed objects such as jets/isolated leptons etc. We demonstrate its usefulness in the context of new physics searches in the channel monojet$+$missing transverse momentum (MET). In models such as in compressed supersymmetry, events are often characterized by a rather large number of soft partons from the cascade decays, none of which result in reconstructed objects. We find that $\xi$, binned in $p_T$, can discriminate these new physics events from events due to $Z+\text{jets}$, that is, the main background in the channel monojet+ MET. The information contained in soft tracks is largely uncorrelated with traditional variables such as the effective mass, MET, $p_T$ of the jet, etc. and, therefore, can be combined with these to increase the discovery potential by more than $200\%$ (depending on the spectra, of course). In fact, we find that simple cuts on $\xi(p_T)$ along with cuts on MET, and the effective mass outperforms sophisticated optimized MultiVariate Analyses using all conventional variables. One can model the background distribution of $\xi(p_T)$ in an entirely data-driven way, and make these robust against pile-up by identifying the primary vertex.