A critical question concerning generative networks applied to event generation in particle physics is if the generated events add statistical precision beyond the training sample. We show for a simple example with increasing dimensionality how generative networks indeed amplify the training statistics. We quantify their impact through an amplification factor or equivalent numbers of sampled events.
Authors / Affiliations: mappings to Contributors and OrganizationsSee all Organizations.
- 1 Ruprecht-Karls-Universität Heidelberg / Heidelberg University
- 2 Universität Hamburg / University of Hamburg [UH]
- 3 Lawrence Berkeley National Laboratory [LBNL]