Statistical Challenges of Global SUSY Fits

TL;DR

This paper evaluates the statistical challenges in reconstructing supersymmetric parameters from simulated LHC data, comparing Bayesian and frequentist methods and addressing algorithmic difficulties in profile likelihood estimation.

Contribution

It provides an assessment of coverage properties and discusses the algorithmic challenges in accurate profile likelihood estimation for SUSY parameter reconstruction.

Findings

Bayesian and frequentist methods have different coverage properties.

Algorithmic difficulties impact the accuracy of profile likelihood estimates.

The study highlights the need for improved statistical techniques in SUSY analyses.

Abstract

We present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical challenges of the reconstruction procedure, and highlight the algorithmic difficulties of obtaining accurate profile likelihood estimates.