6 papers
Extractions of the strong coupling from collider data without PDF refitting are biased
Stefano Forte, Juan Rojo, Roy Stegeman
We present an explicit demonstration that a determination of the strong coupling constant from deep-inelastic scattering and hadron collider data without a simultaneous…
A Determination of at Accuracy from a Global PDF Analysis
The NNPDF Collaboration, Richard D. Ball, Andrea Barontini +6
We present a determination of the strong coupling from a global dataset including both fixed-target and collider data from deep-inelastic scattering and a variety of ha…
Combination of aNLO PDFs and implications for Higgs production cross-sections at the LHC
Thomas Cridge, Lucian A. Harland-Lang, Jamie McGowan +14
We discuss how the two existing approximate NLO (aNLO) sets of parton distributions (PDFs) from the MSHT20 and NNPDF4.0 series can be combined for LHC phenomenology, both i…
NNPDFpol2.0: a global determination of polarised PDFs and their uncertainties at next-to-next-to-leading order
Juan Cruz-Martinez, Toon Hasenack, Felix Hekhorn +6
We present NNPDFpol2.0, a new set of collinear helicity parton distribution functions (PDFs) of the proton based on legacy measurements of structure functions in inclusive neutral-…
Mapping the SMEFT at High-Energy Colliders: from LEP and the (HL-)LHC to the FCC-ee
Eugenia Celada, Tommaso Giani, Jaco ter Hoeve +5
We present SMEFiT3.0, an updated global SMEFT analysis of Higgs, top quark, and diboson production data from the LHC complemented by electroweak precision observables (EWPOs) from…
Hyperparameter Optimisation in Deep Learning from Ensemble Methods: Applications to Proton Structure
Juan Cruz-Martinez, Aaron Jansen, Gijs van Oord +4
Deep learning models are defined in terms of a large number of hyperparameters, such as network architectures and optimiser settings. These hyperparameters must be determined separ…