Absorbing systematic effects to obtain a better background model in a search for new physics

TL;DR

This paper introduces a new method for estimating Standard Model backgrounds by absorbing systematic effects into correction functions, leading to improved background models with reduced uncertainties in high energy physics searches.

Contribution

The paper proposes a novel background estimation technique that modifies Monte Carlo predictions using correction functions, enhancing accuracy and uncertainty reduction compared to existing methods.

Findings

Improved background models with lower uncertainties.

Effective absorption of systematic effects into the background estimate.

Method applicable beyond high energy physics.

Abstract

This paper presents a novel approach to estimate the Standard Model backgrounds based on modifying Monte Carlo predictions within their systematic uncertainties. The improved background model is obtained by altering the original predictions with successively more complex correction functions in signal-free control selections. Statistical tests indicate when sufficient compatibility with data is reached. In this way, systematic effects are absorbed into the new background model. The same correction is then applied on the Monte Carlo prediction in the signal region. Comparing this method to other background estimation techniques shows improvements with respect to statistical and systematical uncertainties. The proposed method can also be applied in other fields beyond high energy physics.