BibTeX
@article{2509.05409v2,
Author = {Henning Bahl and Tilman Plehn and Nikita Schmal},
Title = {Unbinning global LHC analyses},
Eprint = {2509.05409v2},
ArchivePrefix = {arXiv},
PrimaryClass = {hep-ph},
Abstract = {Neural simulation-based inference has been shown to outperform traditional, histogram-based inference in numerous phenomenological and experimental studies at the LHC. So far, these analyses have focused on individual processes. We study the combination of four different di-boson processes in terms of the Standard Model Effective Field Theory. Our results demonstrate how neural simulation-based inference also wins over traditional methods for more global LHC analyses.},
Year = {2025},
Month = {Sep},
Url = {http://arxiv.org/abs/2509.05409v2},
File = {2509.05409v2.pdf}
}