First steps towards the reconstruction of the squark flavour structure

TL;DR

This paper explores methods to determine the flavour composition of squarks observed at the LHC, aiming to uncover the underlying flavour structure of supersymmetric theories using likelihood inference and multivariate analysis.

Contribution

It introduces and compares likelihood inference and multivariate analysis techniques for identifying squark flavour content in simplified and MSSM models.

Findings

Likelihood inference estimates top-flavour content with additional gaugino knowledge.

Multivariate analysis classifies flavour hypotheses with minimal observables.

Both methods help understand squark flavour structure in supersymmetry.

Abstract

Assuming the observation of a squark at the Large Hadron Collider, we investigate methods to access its flavour content and thus gain information on the underlying flavour structure of the theory. Based on simple observables, we apply a likelihood inference method to determine the top-flavour content of the observed particle. In addition, we employ a multivariate analysis in order to classify different flavour hypotheses. Both methods are discussed within a simplified model and the more general Minimal Supersymmetric Standard Model including most general squark mixing. We conclude that the likelihood inference may provide an estimation of the top-flavour content if additional knowledge, especially on the gaugino sector is available, while the multivariate analysis identifies different flavour patterns and can accommodate a more minimalistic set of observables.