Precision Monte Carlo simulations with WHIZARD

The precision physics programs of FCC-ee demands for a precise simulation of all Standard Model (SM) processes and possible beyond the SM (BSM) signals in a state-of-the-art way by means of Monte Carlo (MC) techniques. As a standard tool for e +e − simulations, the multipurpose event generator WHIZARD [1, 2] has been used: this generator has been originally developed for the TESLA project, and later on been used e.g. for the ILC Technical Design Report [3,4]. The WHIZARD package has a modular structure which serves a modern unit-test driven software development and guarantees a high level of maintainability and extendability. WHIZARD comes with its own fully general tree-level matrix-element generator for the hard process, O’Mega [5]. It generates amplitudes in a recursive way based on the graph-theoretical concepts of directed acyclical graphs (DAGs), thereby avoiding all redundancies. The matrix elements are generated either as compilable modern Fortran code or as bytecode instructions interpreted by a virtual machine [6]. For QCD, WHIZARD uses the color-flow formalism [7]. Matrix elements support all kinds of particles and interactions up to spin-2. A large number of BSM models is hard-coded, particularly the MSSM and NMSSM [8, 9]. General BSM models can be loaded from a Lagrangian level tool, using the interface to FeynRules [10]; from the version 2.8.0 of WHIZARD on (early summer 2019) a full-fledged interface to the general UFO format will be available. One of the biggest assets of WHIZARD is its general phasespace parameterization which uses a heuristic based on the dominating sub-processes, which allows to integrate and simulate processes with up to 10 fermions in the final state. The integration is based on an adaptive multi-channel algorithm, called VAMP [11]. Recently, this multi-channel adaptive integration has been enhanced to a parallelized version using the MPI3 protocol showing speedups of up to 100 [12], while a first physics study using this MPI parallelized integration and event generation has been published in [13].