DijetGAN: A Generative-Adversarial Network Approach for the Simulation of QCD Dijet Events at the LHC

Riccardo Di Sipio, Michele Faucci Giannelli, Sana Ketabchi Haghighat +1

A Generative-Adversarial Network (GAN) based on convolutional neural networks is used to simulate the production of pairs of jets at the LHC. The GAN is trained on events generated…