Higgs boson discovery versus sparticles prediction: Impact on the pMSSM's posterior samples from a Bayesian global fit

TL;DR

This paper assesses how the discovery of the Higgs boson influences the parameter space of the pMSSM using Bayesian global fits, highlighting the impact of Higgs data on constraining superpartner masses.

Contribution

It introduces a new discriminant less affected by theoretical uncertainties and demonstrates its use in Bayesian analysis of the pMSSM with Higgs data.

Findings

Higgs data favors the existence of some light superpartners.

Posterior distributions for most masses are not highly restrictive without Higgs data.

Higgs data constraints are nearly prior-independent.

Abstract

The signal strength of the recently discovered Higgs boson-like particle in the diphoton channel seemingly constrains physics beyond the standard model to a severe degree. However, the reported signal strength is prone to possible underestimation of uncertainties. We propose a discriminant that is relatively free of many of the theoretical uncertainties, and use this to gauge the impact on the phenomenological MSSM. A Bayesian global fit to all the pre-LHC data results in posterior distributions for the masses that are neither very restrictive, nor sufficiently prior-independent (except for the Higgs and stop masses). The imposition of the Higgs data, on the other hand, yields interesting and nearly prior-independent constraints. In particular, the existence of some light superpartners is favoured.