# Higgs Assisted Razor Search for Higgsinos at a 100 TeV pp Collider

## TL;DR

This paper proposes a novel search strategy for Higgsino-like particles at a future 100 TeV collider, utilizing Higgs-assisted signatures and machine learning to improve detection sensitivity for supersymmetric particles.

## Contribution

It introduces a new Higgs-assisted razor search method for Higgsinos at a 100 TeV collider, incorporating machine learning to enhance discovery potential.

## Key findings

- Higgsinos up to 1.4 TeV can be discovered with 3000 fb$^{-1}$ of data.
- Higgsinos up to 1.8 TeV can be excluded at 95% C.L.
- The method extends multi-lepton search limits, especially for small mass differences.

## Abstract

A 100 TeV proton-proton collider will be an extremely effective way to probe the electroweak sector of the Minimal Supersymmetric Standard Model (MSSM). In this paper, we describe a search strategy for discovering pair-produced Higgsino-like next-to-lightest supersymmetric particles (NLSPs) at a 100 TeV hadron collider that decay to Bino-like lightest supersymmetric particle (LSP) via intermediate Z and SM Higgs boson that in turn decay to a pair of leptons and a pair of b-quarks respectively: $\widetilde{N}_2^0\widetilde{N}_3^0 \rightarrow (Z\widetilde{N}_1^0)(h\widetilde{N}_1^0)\rightarrow bb\ell\ell+\widetilde{N}_1^0\widetilde{N}_1^0$. In addition, we examine the potential for machine learning techniques to boost the power of our searches. Using this analysis, Higgsinos up to 1.4 TeV can be discovered at $5\sigma$ level for a Bino with mass of about 0.9 TeV using 3000 fb$^{-1}$ of data. Additionally, Higgsinos up to 1.8 TeV can be excluded at 95% C.L. for Binos with mass of about 1.4 TeV. This search channel extends the multi-lepton search limits, especially in the region where the mass difference between the Higgsino NLSPs and the Bino LSP is small.