102 citations · 144 across the 4 of their papers we have counts for
10 papers
Exploring the substructure of nucleons and nuclei with machine learning
Rabah Abdul Khalek
Perturbative quantum chromodynamics (QCD) ceases to be applicable at low interaction energies due to the rapid increase of the strong coupling. In that limit, the non-perturbative…
Self-consistent determination of proton and nuclear PDFs at the Electron Ion Collider
Rabah Abdul Khalek, Jacob J. Ethier, Emanuele R. Nocera +1
We quantify the impact of unpolarized lepton-proton and lepton-nucleus inclusive deep-inelastic scattering (DIS) cross section measurements from the future Electron-Ion Collider (E…
nNNPDF2.0: Quark Flavor Separation in Nuclei from LHC Data
Rabah Abdul Khalek, Jacob J. Ethier, Juan Rojo +1
We present a model-independent determination of the nuclear parton distribution functions (nPDFs) using machine learning methods and Monte Carlo techniques based on the NNPDF frame…
On the derivatives of feed-forward neural networks
Rabah Abdul Khalek, Valerio Bertone
In this paper we present a C++ implementation of the analytic derivative of a feed-forward neural network with respect to its free parameters for an arbitrary architecture, known a…
Phenomenology of NNLO jet production at the LHC and its impact on parton distributions
Rabah Abdul Khalek, Stefano Forte, Thomas Gehrmann +8
We present a systematic investigation of jet production at hadron colliders from a phenomenological point of view, with the dual aim of providing a validation of theoretical calcul…
Probing Proton Structure at the Large Hadron electron Collider
Rabah Abdul Khalek, Shaun Bailey, Jun Gao +2
For the foreseeable future, the exploration of the high-energy frontier will be the domain of the Large Hadron Collider (LHC). Of particular significance will be its high-luminosit…