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Full-Text Articles in Physics
Neutrino-Tagged Jets At The Electron Ion Collider, Miguel Arratia, Zhong-Bo Kang, Sebouh J. Paul, Alexei Prokudin, Felix Ringer, Fanyi Zhao
Neutrino-Tagged Jets At The Electron Ion Collider, Miguel Arratia, Zhong-Bo Kang, Sebouh J. Paul, Alexei Prokudin, Felix Ringer, Fanyi Zhao
Physics Faculty Publications
We explore the potential of jet observables in charged-current deep inelastic scattering events at the future Electron-Ion Collider. Tagging jets with a recoiling neutrino, which can be identified by the event’s missing transverse momentum, will allow for flavor-sensitive measurements of transverse momentum dependent parton distribution functions. We present the first predictions for transverse-spin asymmetries in azimuthal neutrino-jet correlations and hadron-in-jet measurements. We study the kinematic reach and the precision of these measurements and explore their feasibility using parametrized detector simulations. We conclude that jet production in charged-current deep inelastic scattering, while challenging in terms of luminosity requirements, will complement the …
Resolution To The Problem Of Consistent Large Transverse Momentum In Tmds, J. O. Gonzalez-Hernandez, Tommaso Rainaldi, Ted Rogers
Resolution To The Problem Of Consistent Large Transverse Momentum In Tmds, J. O. Gonzalez-Hernandez, Tommaso Rainaldi, Ted Rogers
Physics Faculty Publications
Parametrizing TMD parton densities and fragmentation functions in ways that consistently match their large transverse-momentum behavior in standard collinear factorization has remained notoriously difficult. We show how the problem is solved in a recently introduced set of steps for combining perturbative and nonperturbative transverse momentum in TMD factorization. Called a “bottom-up” approach in a previous article, here we call it a “hadron structure oriented” (HSO) approach to emphasize its focus on preserving a connection to the TMD parton model interpretation. We show that the associated consistency constraints improve considerably the agreement between parametrizations of TMD functions and their large-kT behavior, …
Deeply Learning Deep Inelastic Scattering Kinematics, Markus Diefenthaler, Abdullah Farhat, Andrii Verbytskyi, Yuesheng Xu
Deeply Learning Deep Inelastic Scattering Kinematics, Markus Diefenthaler, Abdullah Farhat, Andrii Verbytskyi, Yuesheng Xu
Mathematics & Statistics Faculty Publications
We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables Q2 and x. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection …
Experimental Results In Dis, Sidis And Des From Jefferson Lab, Sebastian E. Kuhn
Experimental Results In Dis, Sidis And Des From Jefferson Lab, Sebastian E. Kuhn
Physics Faculty Publications
Jefferson Lab’s electron accelerator in its present incarnation, with a maximum beam energy slightly above 6 GeV, has already enabled a large number of experiments expanding our knowledge of nucleon and nuclear structure (especially in Deep Inelastic Scattering—DIS—at moderately high x, and in the resonance region). Several pioneering experiments have yielded first results on Deeply Virtual Compton Scattering (DVCS) and other Deep Exclusive Processes (DES), and the exploration of the rich landscape of transverse momentum‐dependent (TMD) structure functions using Semi‐Inclusive electron scattering (SIDIS) has begun. With the upgrade of CEBAF to 12 GeV now underway, a significantly larger kinematic …