Licentiate Thesis: Weak Scale Supersymmetry: Parameter Spaces, Complexity and Global Fits

by Yashar Akrami (SU Fysikum)

Tuesday 22 Dec 2009, 13:15 → 15:45 Europe/Stockholm

FB42

TeV energy scales are thrilling. New physics beyond the Standard Model (SM) of particle physics is broadly conjectured to appear at these scales. One of the strongest motivations for this new weak‐scale physics is the theoretical demand for a solution to the so‐called hierarchy problem, to which, softly‐broken weak‐scale supersymmetry (SUSY) provides a natural solution. This is one reason why particular attention has been paid to SUSY extensions of the SM, widely hoped to show up at the Large Hadron Collider (LHC). In addition to this, the natural connection between SUSY and grand unified theories (GUTs) offers extensive scope for achieving gauge‐coupling unification in this framework. Another major theoretical motivation for SUSY is that most weak‐scale versions contain a viable dark matter (DM) candidate, such as the lightest neutralino. Neutralino is a weakly‐interacting massive particle (WIMP) and remains arguably the leading candidate for DM. The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely‐studied SUSY extensions of the SM, in which, the number of free parameters is dramatically reduced in order to make phenomenological analyses possible. There has recently been considerable effort to constrain SUSY parameter spaces, in particular the CMSSM, using existing cosmological and collider data, as well as direct and indirect detections of DM. This thesis presents two different, although related, types of these phenomenological studies. In the first part, by focusing on the CMSSM as our test‐bed model, we mainly investigate the complexity of SUSY global fits in terms of statistical inferences. Scanning of SUSY parameter spaces is nowadays a highly developed art. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning SUSY parameter spaces, optimized for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing constraints from accelerator bounds, the relic density of DM, electroweak precision observables, the anomalous magnetic moment of the muon and B‐physics. We compare our method to nested sampling, an efficient Bayesian technique, paying particular attention to the best‐fit points and implications for particle masses at the LHC and DM searches. We show that there are many high‐likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans. In the second study, we examine what constraints 9 months of Fermi‐LAT gamma‐ray observations of the dwarf galaxy Segue 1, as one of the most promising targets for the indirect detection of DM, place upon the CMSSM with the lightest neutralino as the DM particle. We use nested sampling to explore the CMSSM parameter space, simultaneously fitting other relevant constraints from existing collider and cosmological data. We include spectral and spatial fits to the Fermi observations, a full treatment of the instrumental response and its related uncertainty, and detailed background models. We also perform an extrapolation to 5 years of observations, assuming no signal is observed from Segue 1 in that time. Results marginally disfavor models with low neutralino masses and high annihilation cross‐sections. Virtually all of these models are however already disfavored by existing experimental or relic density constraints.