Conveners
Generative Models
- Jana Schaarschmidt (University of Washington (US))
- Martin Erdmann (Rheinisch Westfaelische Tech. Hoch. (DE))
In the coming years, the experiments at the LHC will collect a significant amount of data which will require a similarly large increase in number of Monte Carlo (MC) events. This will force experiments to move to fast simulation to be able to produce the required number of MC events. At the same time, theorists are developing better but more time-consuming event generators that will put...
We present a network for generative modeling of LHC events. We use Lorentz boosts, rotations, momentum and energy conservation to build a network cell generating a 2-body particle decay. We allow for modifications of the resulting four-vectors following a StyleGAN approach. We train the generator using the Lorentz Boost Network as a pre-stage of the critic’s network. We present first...
Event generation for the LHC can be supplemented by generative adversarial networks, which generate physical events and avoid highly inefficient event unweighting. For top pair production we show how such a network describes intermediate on-shell particles, phase space boundaries, and tails of distributions. It can be extended in a straightforward manner to include for instance off-shell...
Abstract: As the integrated luminosity of the LHC increases, the number of Monte Carlo (MC) events required increases as well. The cost of generating these events will eventually be cost prohibitive. Thus, improvements are required in event generation. The major inefficiency in the MC generation is from generating unweighted events. Using machine learning techniques, I will propose a new phase...
We introduce a generative model to simulate radiation patterns within a jet using the Lund jet plane. We show that using an appropriate neural network architecture with a stochastic generation of images, it is possible to construct a generative model which retrieves the underlying two-dimensional distribution to within a few percent. We compare our model with several alternative...
The ATLAS physics program relies on very large samples of GEANT4 simulated events, which provide a highly detailed and accurate simulation of the ATLAS detector. But this accuracy comes with a high price in CPU, predominantly caused by the calorimeter simulation. The sensitivity of many physics analyses is already limited by the available Monte Carlo statistics and will be even more so in the...
The ATLAS physics program relies on very large samples of GEANT4 simulated events, which provide a highly detailed and accurate simulation of the ATLAS detector. But this accuracy comes with a high price in CPU, predominantly caused by the calorimeter simulation. The sensitivity of many physics analyses is already limited by the available Monte Carlo statistics and will be even more so in the...
