Abstract: We introduce FlexibleSUSY, a Mathematica and C++ package, which generates a fast, precise C++ spectrum generator for any SUSY model specified by the user. The generated code is designed with both speed and modularity in mind, making it easy to adapt and extend with new features. The model is specified by supplying the superpotential, gauge structure and particle content in a SARAH model file; specific boundary conditions e.g. at the GUT, weak or intermediate scales are defined in a separate FlexibleSUSY model file. From these model files, FlexibleSUSY generates C++ code for self-energies, tadpole corrections, renormalization group equations (RGEs) and electroweak symmetry breaking (EWSB) conditions and combines them with numerical routines for solving the RGEs and EWSB conditions simultaneously. The resulting spectrum generator is then able to solve for the spectrum of the model, including loop-corrected pole masses, consistent with user specified boundary conditions. The modular structure of the generated code allows for individual components to be replaced with an alternative if available. FlexibleSUSY has been carefully designed to grow as alternative solvers and calculators are added. Predefined models include the MSSM, NMSSM, E6SSM, USSM, R-symmetric models and models with right-handed neutrinos. Program Summary Program title: FlexibleSUSY Catalogue identifier: AEVIv10 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEVIv10.html obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 129406 No. of bytes in distributed program, including test data, etc.: 854831 Distribution format: tar.gz Programming language: C++, Wolfram/Mathematica, FORTRAN, Bourne shell. Computer: Personal computer. Operating system: Tested on Linux 3.x, Mac OS X. Classification: 11.1, 11.6, 6.5. External routines: SARAH 4.0.4, Boost library, Eigen, LAPACK Nature of problem: Determining the mass spectrum and mixings for any supersymmetric model. The generated code must find simultaneous solutions to constraints which are specified at two or more different renormalization scales, which are connected by renormalization group equations forming a large set of coupled first-order differential equations. Solution method: Nested iterative algorithm and numerical minimization of the Higgs potential. Restrictions: The couplings must remain perturbative at all scales between the highest and the lowest boundary condition. FlexibleSUSY assumes that all couplings of the model are real (i.e. CP-conserving). Due to the modular nature of the generated code, adaption and extension to overcome restrictions in scope is quite straightforward. Running time: 0.06-0.2 seconds per parameter point.

Abstract: We give the superalgebra of N = 2 chiral (and antichiral) quantum superfields realized as a subalgebra of the quantum supergroup SL q (4|2). The multiplication law in the quantum supergroup induces a coaction on the set of chiral superfields. We also realize the quantum deformation of the chiral Minkowski superspace as a quantum principal bundle.

Abstract: We investigate couplings of squarks to gauge and Higgs-bosons within the framework of non-minimal flavour violation in the Minimal Supersymmetric Standard Model. Introducing non-diagonal elements in the mass matrices of squarks, we first study their impact on the self-energies and physical mass eigenvalues of squarks. We then present an extensive analysis of bosonic squark decays for variations of the flavour-violating parameters around the two benchmark scenarios SPS1a' and SPS1b. Signatures, that would be characteristic for a non-minimal flavour structure in the squark sector, can be found in wide regions of the parameter space.

Abstract: We study the phenomenology of a supersymmetric left-right model, assuming minimal supergravity boundary conditions. Both left-right and (B-L) symmetries are broken at an energy scale close to, but significantly below the GUT scale. Neutrino data is explained via a seesaw mechanism. We calculate the RGEs for superpotential and soft parameters complete at 2-loop order. At low energies lepton flavour violation (LFV) and small, but potentially measurable mass splittings in the charged scalar lepton sector appear, due to the RGE running. Different from the supersymmetric “pure seesaw” models, both, LFV and slepton mass splittings, occur not only in the left-but also in the right slepton sector. Especially, ratios of LFV slepton decays, such as Br((tau) over bar (R) -> μchi(0)(1))/Br((tau) over bar (L) -> μchi(0)(1)) are sensitive to the ratio of (B-L) and left-right symmetry breaking scales. Also the model predicts a polarization asymmetry of the outgoing positrons in the decay mu(+) -> e(+)gamma, A similar to [0, 1], which differs from the pure seesaw “prediction” A = 1. Observation of any of these signals allows to distinguish this model from any of the three standard, pure (mSugra) seesaw setups.

Abstract: Statistical inference of the fundamental parameters of supersymmetric theories is a challenging and active endeavor. Several sophisticated algorithms have been employed to this end. While Markov-Chain Monte Carlo (MCMC) and nested sampling techniques are geared towards Bayesian inference, they have also been used to estimate frequentist confidence intervals based on the profile likelihood ratio. We investigate the performance and appropriate configuration of MULTINEST, a nested sampling based algorithm, when used for profile likelihood-based analyses both on toy models and on the parameter space of the Constrained MSSM. We find that while the standard configuration previously used in the literarture is appropriate for an accurate reconstruction of the Bayesian posterior, the profile likelihood is poorly approximated. We identify a more appropriate MULTINEST configuration for profile likelihood analyses, which gives an excellent exploration of the profile likelihood (albeit at a larger computational cost), including the identification of the global maximum likelihood value. We conclude that with the appropriate configuration MULTINEST is a suitable tool for profile likelihood studies, indicating previous claims to the contrary are not well founded.