A profile likelihood analysis of the constrained MSSM with genetic algorithms

DOI10.1007/JHEP04(2010)057zbMath1272.81204arXiv0910.3950MaRDI QIDQ367795

Lars Bergström, Joakim Edsjö, Yashar Akrami, Pat Scott, Jan O. Conrad

Publication date: 16 September 2013

Published in: Journal of High Energy Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0910.3950

zbMATH Keywords

supersymmetry phenomenology

Mathematics Subject Classification ID

Bayesian inference (62F15) Unified quantum theories (81V22) Supersymmetric field theories in quantum mechanics (81T60)

Related Items (9)

Machine learning meets the redshift evolution of the CMB temperature ⋮ Testing the ΛCDM paradigm with growth rate data and machine learning ⋮ Data science applications to string theory ⋮ Challenges of profile likelihood evaluation in multi-dimensional SUSY scans ⋮ A coverage study of the CMSSM based on ATLAS sensitivity using fast neural networks techniques ⋮ A systematic approach to Kähler moduli stabilisation ⋮ Searching the landscape of flux vacua with genetic algorithms ⋮ A robust and efficient algorithm to find profile likelihood confidence intervals ⋮ Constraints on the distance duality relation with standard sirens

Uses Software

• FeynHiggs
• SOFTSUSY
• PIKAIA
• HiggsBounds
• DarkSUSY
• MultiNest
• CosmoMC

Cites Work

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• \textit{FeynHiggs}: A program for the calculation of the masses of the neutral \({\mathcal C}P\)-even Higgs bosons in the MSSM
• Effective Lagrangian approach to pion photoproduction from the nucleon
• Introduction to Fuzzy Logic using MATLAB
• Genetic Algorithms and Genetic Programming
• The search for black hole binaries using a genetic algorithm
• Supersymmetry in Particle Physics
• Weak Scale Supersymmetry
• Genetic algorithm for SU(\(N\)) gauge theory on a lattice
• Nested sampling for general Bayesian computation

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