5 citations · 10 across the 7 of their papers we have counts for
4 papers · 1 filter
Proton Structure from Neural Simulation-Based Inference at the LHC
Ricardo Barrué, Lisa Benato, Ali Kaan Güven +10
The precise determination of the parton distribution functions (PDFs) of the proton is an essential ingredient for LHC analyses, including for those at the upcoming High-Luminosity…
LHC EFT WG Note: SMEFT predictions, event reweighting, and simulation
Alberto Belvedere, Saptaparna Bhattacharya, Giacomo Boldrini +16
This note gives an overview of the tools for predicting expectations in the Standard Model effective field theory (SMEFT) at the tree level and one loop available through event gen…
Equivariant neural networks for robust observables
Sergio Sánchez Cruz, Marina Kolosova, Clara Ramón Álvarez +2
We introduce the usage of equivariant neural networks in the search for violations of the charge-parity () symmetry in particle interactions at the CERN Large Hadron C…
A rotation-equivariant graph neural network for learning hadronic SMEFT effects
Suman Chatterjee, Sergio Sánchez Cruz, Robert Schöfbeck +1
We introduce a graph neural network architecture designed to extract novel phenomena in the Standard Model Effective Field Theory (SMEFT) context from LHC collision data. The propo…