SARAH is a Mathematica package optimized for the fast and exhaustive analysis of supersymmetric models. It has been designed to handle every N = 1 SUSY theory with an arbitrary direct product of SU (n) and/or U (1) factors as gauge group. The chiral superfields can transform under arbitrary, irreducible representations with regard to this gauge group, and all possible renormalizable superpotential terms are supported. New models can be implemented in an easy and straight-forward manner and SARAH can create as output model files for FeynArts/FormCalc, CalcHep/CompHep, WHIZARD and Madgraph. In addition, SARAH can be used as spectrum-generator-generatore because it writes modules for SPheno to create a full-fledged spectrum calculator for new models. The features of these spectrum generators include a precise mass spectrum calculation using two-loop RGEs and full one-loop corrections, two and three body decays of SUSY and Higgs particles as well as the calculation of electroweak precision observables. Furthermore, SARAH is the heart of the recently presented 'SUSY toolbox' which provides an environment for the study of MSSM extensions using SPheno, CalcHep/MicrOmegas, WHIZARD and Higgsbounds. This framework combines the different outputs of SARAH to provide a closed tool-chain from model building to phenomenology.

In this presentation we release the new version 2.1 of the Monte Carlo event generator WHIZARD for high-energy physics collider experiment simulations. After reviewing the status of the new development line 2.x, we discuss news and improvements coming with the first major revision 2.1. These include the analytic parton shower for initial and final state radiation, developments in the direction of support for NLO calculations, more efficient generation and evaluation of multi-parton SM matrix elements, new BSM features as well as important technical improvements.

We describe recent extensions of the program SPheno including flavour aspects, CP-phases, R-parity violation and low energy observables. In case of flavour mixing all masses of supersymmetric particles are calculated including the complete flavour structure and all possible CP-phases at the 1-loop level. We give details on implemented seesaw models, low energy observables and the corresponding extension of the SUSY Les Houches Accord. Moreover, we comment on the possiblities to include MSSM extensions in SPheno.

We present a Fortran code which calculates the production cross section for the (lightest) Higgs boson in the SM and MSSM resulting from gluon fusion and bottom-quark annihilation. Differential and total cross sections are obtained at NLO in gluon fusion, taking into account the full contribution from the third generation of quarks and squarks in the MSSM. Inclusive weighted results up to NNLO from gluon and/or bottom-quark fusion can be added. In addition to the features of this program, the talk discusses the impact of different renormalization schemes for the squark sector in the MSSM.

In this talk I will demonstrate how to use the AMIDAS package online for both Monte-Carlo simulations and analyzing (pseudo)data sets to extract properties of halo WIMPs, e.g., the mass and the (ratios between the) spin-independent and spin-dependent couplings/cross sections on nucleons. In order to show the model-independence of the AMIDAS package, a comparison between the blindly reconstructed results and the original (non-standard) input setup for generating both the WIMP signals as well as a small amount of artificially added background events will also be given.

I will discuss the new neutrino telescope likelihood routines in DarkSUSY. These are based on a fast method for including event-level IceCube data in likelihood calculations, and are optimised for global-fit type parameter explorations of theories for new physics. The likelihood construction is not at all specific to SUSY, and includes both angular and spectral information about neutrino events, as well as their total number. I'll also discuss a corresponding measure for simple model exclusion, which can be used for single models without reference to the rest of a parameter space. I'll illustrate the use of the new routines with a number of examples from the MSSM, and show that including spectral information significantly improves model reconstructions.

We present MadAnalysis 5, a new framework for phenomenological inves- tigations at particle colliders. Based on a C++ kernel, this program allows to efficiently perform, in a straightforward and user-friendly fashion, sophis- ticated physics analyses of event files such as those generated by a large class of Monte Carlo event generators. MadAnalysis 5 comes with two modes of running. The first one, easier to handle, uses the strengths of a powerful Python interface in order to implement the analysis by the mean of a set of intuitive commands. The second one requires to implement the analysis in the C++ programming language, directly within the core of the anal- ysis framework. This opens unlimited possibilities concerning the level of complexity which can be reached by the analysis, being only limited by the programming skills and the originality of the user.

We perform global fits to the parameters of the Constrained Minimal Supersymmetric Standard Model (CMSSM) and to a variant with non-universal Higgs masses (NUHM1), taking into account the current LHC exclusions from searches in jets plus missing transverse energy signatures with about 5/fb integrated luminosity. We include the recent LHCb upper bound on the branching ratio Bs->mu+mu-. Also, constraints from and implications for direct and indirect dark matter searches are discussed. The minimum of the CMSSM fit prefers a light Higgs boson just above the experimentally excluded mass. A potential SM-like Higgs boson with mass around 126GeV can barely be accommodated. Values for Bs->mu+mu- just around the Standard Model prediction are naturally expected in the best fit region. The most-preferred region is not yet affected by limits on direct WIMP searches, but the next generation of experiments will probe this region. Finally, we consider the fine-tuning implications of our best fit regions.