13 papers
A global analysis of ALP-mediated multiboson production at the LHC
Fabian Esser, Alexandre Salas-Bernardez, Maria Ubiali +1
Axion-like particles (ALPs) provide a well-motivated framework for physics beyond the Standard Model, coupling to gauge bosons through dimension-five operators protected by an appr…
Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation
Manuel HauÃmann, Ramon Winterhalder, Maria Ubiali
Reliable uncertainty quantification is essential for the use of machine learning in physics, where scientific discoveries depend on validated probabilistic statements. We provide a…
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…
A linear PDF model for Bayesian inference
Mark N. Costantini, Luca Mantani, James M. Moore +1
A robust uncertainty estimate in global analyses of Parton Distribution Functions (PDFs) is essential at the Large Hadron Collider (LHC), especially in view of the high-precision d…
Parton distribution functions and theory parameters: an NNPDF perspective
Richard D. Ball, Tommaso Giani, Felix Hekhorn +5
Parton Distribution Functions (PDFs) are a key ingredient in theoretical predictions for Large Hadron Collider (LHC) observables and play a central role in the extraction of precis…
Tailored PDFs for New Physics searches
Ella Cole, Mark N. Costantini, Elie Hammou +4
Given the non-negligible interplay between parton distribution functions (PDFs) at large x and potential New Physics (NP) effects in the high-energy tails of hadron collider observ…