319 citations · 3.3k across the 77 of their papers we have counts for
80 papers
Up and Down Quark Structure of the Proton
D0 Collaboration
We measure proton structure parameters sensitive primarily to valence quarks using 8.6 fb of data collected by the D0 detector in TeV collisions a…
Local Structure-aware Graph Contrastive Representation Learning
Kai Yang, Yuan Liu, Zijuan Zhao +2
Traditional Graph Neural Network (GNN), as a graph representation learning method, is constrained by label information. However, Graph Contrastive Learning (GCL) methods, which tac…
Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment
DUNE Collaboration, A. Abed Abud, B. Abi +1313
A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the MeV neutrinos produced by a Galactic core-collapse supernova if one s…
Highly-parallelized simulation of a pixelated LArTPC on a GPU
DUNE Collaboration, A. Abed Abud, B. Abi +1300
The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for part…
Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector
DUNE Collaboration, A. Abed Abud, B. Abi +1253
Measurements of electrons from interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyo…
Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment
M. A. Acero, B. Acharya, P. Adamson +218
Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confiden…