Speaker
Description
Computing the decay rate of a meta-stable state is a well-known problem with relevance in various areas of physics. The decay rate is dominated by an exponential factor called the bounce action. Determining the bounce action for a given potential and meta-stable vacuum involves solving a set of partial differential equations with intricate boundary conditions. There are several dedicated solvers available for this problem, however finding bounce actions in potentials of many variables still remains a challenge. We use a neural network to solve the partial differential equation for finding the tunneling path. We apply this approach to analyze vacuum stability in both the Minimal Supersymmetric extension of the Standard Model (MSSM) and the Next-to-MSSM (NMSSM), where we determine bounce actions for the tree-level potential including all Higgs fields and 3rd generation sfermions. We compare the resulting constraints on the parameter space of the (N)MSSM to the ones from LHC Higgs measurements.
