Speaker
Description
In High Energy Physics, the interaction of particles with matter at
the detectors are best simulated with the GEANT4 software. Alternatively,
less precise but faster simulations are sometimes preferred to
reach higher statistical precision. We present recent progress of refinement
of fast simulations with ML techniques to enhance the quality of
such fast simulations. We demonstrate the use of adversarial
networks in the context of jet simulation using a Wasserstein loss
function. The architecture consists of two opposing networks, Refiner
and Critic. The Refiner, refines the distribution of the energy of the
jets obtained with the fast simulation. The Critic is used to effectively
differentiate between the distributions of refined energy and the distribution
obtained by the GEANT4 simulation. The Refiner can be used
solely to obtain a fast but refined jet simulation.
