Title: FastCaloGAN, a fast calorimeter simulation tool using Generative Adversarial Networks
ATLAS relies on gargantuan amounts of simulated Monte Carlo events to carry out its wide physics programme. Currently, the detector simulation is performed predominantly using Geant4 but the CPU resources required are extraordinary and will not be sufficient for the HL-LHC requirements. Therefore, the collaboration has being using and developing alternative fast simulation tools, focussing specifically on fast calorimeter shower simulation. FastCaloGAN is the most recent tool developed for this task and exploits Generative Adversarial Networks (GANs) for the generation of these showers. FastCaloGAN is one of the tools deployed in AtlFast3 (AF3), the latest fast simulation application in ATLAS. AF3 meet the computing challenges and Monte Carlo needs for Run 3 and significantly improved the precision of the simulation that can now be used to simulate almost all physics processes. Recent developments of the tools that were submitted for the #CaloChallenge will also be presented.
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