Global Fits of the Large Volume String Scenario to WMAP5 and Other Indirect Constraints Using Markov Chain Monte Carlo

TL;DR

This paper performs comprehensive global fits of the Large Volume Scenario in string models using current cosmological and collider data, predicting sparticle masses below 1 TeV and highlighting key experimental constraints.

Contribution

It introduces a robust method for fitting LVS models to data and identifies the most influential experimental constraints on the parameter space.

Findings

LVS can adequately fit current indirect data.

Sparticle masses are constrained below 1 TeV.

LEP2 Higgs, dark matter relic density, and muon g-2 are key constraints.

Abstract

We present global fits to the Large Volume Scenario (LVS) of string models using current indirect data. We use WMAP5 constraints on dark matter relic density, b-physics and electroweak observables as well as direct search constraints. Such data can be adequately fit by LVS, with the best-fit point for mu>0 having chi^2=13.6 for 8 degrees of freedom. The resulting constraints on parameter space are robust in that they do not depend much upon the prior, or upon whether one uses Bayesian or frequentist interpretations of the data. Sparticle masses are constrained to be well below the 1 TeV level, predicting early SUSY discovery at the LHC. We devise a method of quantifying which are the most important constraints. We find that the LEP2 Higgs mass constraint, the relic density of dark matter and the anomalous magnetic moment of the muon affect the fits to the strongest degree.