Impact of CMS Multi-jets and Missing Energy Search on CMSSM Fits

TL;DR

This paper assesses how recent CMS multi-jet and missing energy search data influence global fits of the CMSSM, showing that new collider constraints reshape the probability distributions of key supersymmetric parameters.

Contribution

It introduces a method to incorporate CMS search results into CMSSM fits by simulating signal events and constructing a likelihood map, updating previous global fits with new collider data.

Findings

CMS data reduces high-probability regions for scalar and gluino masses.

The search impacts the distribution of tan beta due to parameter correlations.

Likelihood mapping effectively integrates collider constraints into supersymmetric model fits.

Abstract

Recent CMS data significantly extend the direct search exclusion for supersymmetry. We examine the impact of such data on global fits of the constrained minimal supersymmetric standard model (CMSSM) to indirect and cosmological data. By simulating supersymmetric signal events at the LHC, we construct a likelihood map for the recent CMS data, validating it against the exclusion region calculated by the experiment itself. A previous CMSSM global fit is then re-weighted by our likelihood map. The CMS results nibble away at the high fit probability density region, transforming probability distributions for the scalar and gluino masses. The CMS search has a non-trivial effect on tan beta due to correlations between the parameters implied by the fits to indirect data.