CaloShowerGAN, a Generative Adversarial Networks model for fast calorimeter shower simulation

In particle physics, the demand for rapid and precise simulations is rising. The shift from traditional methods to machine learning-based approaches has led to significant advancements in simulating complex detector responses. CaloShowerGAN is a new approach for fast calorimeter simulation based on Generative Adversarial Network (GAN). We use Dataset 1 of the Fast Calorimeter Simulation Challenge 2022 to demonstrate the efficacy of the model to simulate calorimeter showers produced by photons and pions. The dataset is originated from the ATLAS experiment, and we anticipate that this approach can be seamlessly integrated into the ATLAS system. This development marks a significant improvement compared to the deployed GANs by ATLAS and could offer substantial enhancement to the current ATLAS fast simulations.Comment: 26 pages, 17 figure

Interactions of hadrons in the CALICE SiW ECAL prototype

This article presents results of test beams obtained for pions with energies between 2 and 10 GeV which interact in the volume of the highly granular CALICE Silicon-Tungsten electromagnetic calorimeter prototype (SiW ECAL). An algorithm optimised to find interactions in the SiW ECAL at small hadron energies is developed. This allows identifying the interaction point in the calorimeter at an efficiency between 62% and 83% depending on the energy of the primary particle. The unprecedented granularity of the SiW ECAL allows for the distinction between different interaction types. This in turn permits more detailed examinations of hadronic models than was possible with traditional calorimeters. So far, it is possible to disentangle minimum ionising particle (MIP) events, elastic π-nucleus scattering and spallation reactions which lead to the start of a internuclear cascade or which result in a small number of highly ionising particles. Various observables are compared with predictions from hadronic physics lists as contained in the simulation toolkit geant4