2 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
Machine Learning Neutrino-Nucleus Cross Sections II: More Leptons
Daniel C. Hackett, Joshua Isaacson, Shirley Weishi Li +2
Neutrino-nucleus cross sections are essential inputs for long-baseline neutrino oscillation experiments, yet remain challenging to model with high precision. Recent work demonstrat…
Drell-Yan lepton pair production from low to high transverse momentum
Benoît Assi, Enrico Bothmann, John Campbell +7
We present a technique for computing Drell-Yan lepton pair production at particle-level that achieves NLO and approximate NLL accuracy at small to moderate transverse mo…
An extraction of the Collins-Soper kernel from a joint analysis of experimental and lattice data
Artur Avkhadiev, Valerio Bertone, Chiara Bissolotti +6
We present a first joint extraction of the Collins-Soper kernel (CSK) combining experimental and lattice QCD data in the context of an analysis of transverse-momentum-dependent dis…
Machine Learning Neutrino-Nucleus Cross Sections
Daniel C. Hackett, Joshua Isaacson, Shirley Weishi Li +2
Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections rema…