429 citations · 620 across the 7 of their papers we have counts for
7 papers
A new generation of simultaneous fits to LHC data using deep learning
Shayan Iranipour, Maria Ubiali
We present a new methodology that is able to yield a simultaneous determination of the Parton Distribution Functions (PDFs) of the proton alongside any set of parameters that deter…
Parton distributions in the SMEFT from high-energy Drell-Yan tails
Maeve Madigan, James Moore
We present a study of the interplay between PDF and EFT effects in high-mass Drell-Yan at the LHC. We quantify the impact of a consistent joint determination of the PDFs and Wilson…
An open-source machine learning framework for global analyses of parton distributions
Richard D. Ball, Stefano Carrazza, Juan Cruz-Martinez +14
We present the software framework underlying the NNPDF4.0 global determination of parton distribution functions (PDFs). The code is released under an open source licence and is acc…
The Path to Proton Structure at One-Percent Accuracy
Richard D. Ball, Stefano Carrazza, Juan Cruz-Martinez +14
We present a new set of parton distribution functions (PDFs) based on a fully global dataset and machine learning techniques: NNPDF4.0. We expand the NNPDF3.1 determination with 44…
Parton distributions in the SMEFT from high-energy Drell-Yan tails
Admir Greljo, Shayan Iranipour, Zahari Kassabov +5
The high-energy tails of charged- and neutral-current Drell-Yan processes provide important constraints on the light quark and anti-quark parton distribution functions (PDFs) in th…
The Strangest Proton?
Ferran Faura, Shayan Iranipour, Emanuele R. Nocera +2
We present an improved determination of the strange quark and anti-quark parton distribution functions of the proton by means of a global QCD analysis that takes into account a com…
Can New Physics hide inside the proton?
Stefano Carrazza, Celine Degrande, Shayan Iranipour +2
Modern global analyses of the structure of the proton include collider measurements which probe energies well above the electroweak scale. While these provide powerful constraints…