Data-driven Estimation of SM Backgrounds for SUSY Searches at the LHC

TL;DR

This paper presents a data-driven method for estimating Standard Model backgrounds in early SUSY searches at the LHC, aiming to improve detection sensitivity for new physics.

Contribution

It introduces a novel strategy specifically designed for early-stage LHC data to accurately estimate SM backgrounds in SUSY searches.

Findings

Effective background estimation improves SUSY detection prospects.

Method reduces reliance on theoretical models for background prediction.

Enhances early search strategies at the LHC.

Abstract

Searches for supersymmetry (SUSY) are very important tasks at the Large Hadron colleder(LHC). If SUSY exists at the TeV scale, clear excess above the Standard Model (SM) background will be observed. SM background should be estimated from real data self. In this paper, we descrive the strategy for the early SUSY searches at the LHC and focus on the data-driven estimation of the SM background in the early stage of collision.