The Matrix Element Method as a tool for precision and accuracy

TL;DR

This paper extends the Matrix Element Method to next-to-leading order in QCD, improving precision in LHC data analysis for top-quark mass and BSM parameter determination, reducing biases and uncertainties.

Contribution

It introduces a NLO extension of the Matrix Element Method for LHC data, enhancing accuracy in parameter extraction and reducing biases compared to leading-order approaches.

Findings

Demonstrated improved top-quark mass measurement accuracy.

Showcased potential for precise BSM parameter extraction.

Reduced theoretical bias and uncertainty in analyses.

Abstract

The Matrix Element Method is a promising multi-variate analysis tool which offers an optimal approach to compare theory and experiment according to the Neyman-Pearson lemma. However, until recently its usage has been limited by the fact that only leading-order predictions could be employed. The imperfect approximation of the underlying probability distribution can introduce a significant bias into the analysis which requires a major calibration for the method when applied to parameter determination. Moreover, estimating theoretical uncertainties by scale variation may yield unreliable results. We present the extension of the Matrix Element Method to next-to-leading order in QCD applicable to LHC data defined by common jet algorithms. The accuracy gain is illustrated by simulating a top-quark mass determination from single top-quark events generated with POWHEG+PYTHIA. Additionally, the method's potential for BSM parameter determination is demonstrated by simulating the extraction of a CP-violating Top-Yukawa coupling from events of single top-quarks in association with a Higgs boson.