The accurate simulation of particle detector responses is a crucial component of the experimental process in high energy physics. This task is achieved traditionally through software packages that describe the particle detector response to radiation in fine details. While such methods provide a very high accuracy, they are computationally very intensive. Reducing the computational resources is of crucial importance in view of the high luminosity run of the Large Hadron Collider at CERN, where exponentially larger amounts of interaction will need to be simulated, compared to present. We propose a method based on use deep Generative Adversarial Networks (GANs) to speed up the simulation process and thus complement the traditional methods. We show in particular that GANs can be used to simulate particle detector responses to hadronic jets with a very high level of accuracy.