Nuclear Physics Seminars This Term

The concept of “spin” was invented in the first part of the 20^th century when it was realized that if we try to assign the angular momentum of an electron to a rotating ball, the surface of the ball would necessarily travel faster than the speed of light.  In quantum theory matter is separated into fermions and bosons by the spin-statistics theorem.  Fermions occupy space and are subject to the Pauli selection constraints.  In contrast,  Bosons can cohere into extended condensates.  In the gauge field theories of the Standard Model, bosons and fermions are closely connected by gauge invariance.  My talk will use several props in addition to slides to motivate two conjectures connecting magnetic charges to the small-distance behavior of gravity.

Understanding the nucleon's internal structure remains a central challenge in nuclear physics. Generalized Parton Distributions (GPDs) and Transverse Momentum Distributions (TMDs) provide complementary perspectives on partonic spatial and momentum distributions, capturing essential nonperturbative nucleon dynamics. In this seminar, I will discuss ongoing theoretical and experimental efforts to characterize nucleon structure via GPDs and TMDs. I will then highlight recent progress using deep neural networks (DNNs) to extract the Sivers TMD, demonstrating how artificial intelligence (AI) enhances our ability to model nucleonic momentum correlations. Additionally, I will present the SpinQuest (E1039) experiment at Fermilab, which aims to measure sea-quark contributions to the nucleon spin by determining the Sivers function from dimuon production. Finally, I will introduce symbolic regression (SR) as a novel approach for deriving analytical expressions of TMDs and GPDs, offering new insights into the underlying partonic physics within hadrons.

Pancreatic cancer is one of the most lethal cancers with a five-year survival of 13%. Although Radiation Therapy (RT) plays a critical role in tumor control, its dual impact—stimulating anti-tumor T cell production while suppressing the immune system—presents a significant therapeutic challenge. Current national pancreatic protocols are oblivious to lymphopenia. We have analyzed a retrospective data set of 69 pancreatic non-SBRT patients. Maximum lymphocyte reduction from radiation treatment (RT) to pancreas could be as much as 78% from the pretreatment ALC value, including 81% with grade 3 lymphopenia and a nadir at day 35 following RT initiation. Currently there is no computational model to predict radiation induced immune suppression (RIIS) for pancreas that would allow the treatment team to optimize radiation therapy to minimize RIIS. To mitigate these effects, we developed a predictive algorithm for Radiation-Induced Immune Suppression (RIIS). This algorithm allows for a direct comparison of RT plans, identifying those that minimize immune suppression without compromising tumor-targeting efficacy. Additionally the impact of immune rich organ dose volumes on the overall survival could shed light on what immune rich organs, especially T cell rich should be spared and by how much. We have linked the overall survival calculations with organ specific static dose volumes to further select the impactful immune rich organ sparing. By automating the selection of constraints for immune system preservation, our approach offers a pathway to improved treatment personalization in RT clinics.

The Super BigBite Spectrometer (SBS) program at Jefferson Lab aims to measure nucleon electromagnetic form factors (EMFFs) at high momentum transfers. The GEn-RP experiment, the third in the SBS experiment series, concluded data taking in May 2024. This experiment is focused on measuring the neutron EMFF ratio GnE/GnM through recoil polarimetry at a Q2 = 4.5 (GeV/c)². Two polarimetry techniques have been used in this experiment: charge-exchange np→pn with a passive Fe analyzer, and conventional np→np scattering with an active CH analyzer. The results of this experiment will serve to optimize future even higher Q2 experiments aimed at measuring GnE/GnM. An overview of the experiment and post- experiment data analysis efforts will be presented.

The Nab experiment is a precision study of unpolarized neutron decay. Cold neutrons decay in flight inside a custom spectrometer. The goal of Nab is to measure a, the electron-neutrino coefficient, and b, the Fierz interference term that vanishes in the standard model (SM). A measured value of a at the Nab goal precision of △a/a ≈ 10-3 will provide an independent competitive evaluation of the Vud element of the Cabibbo-Kobayashi-Maskawa (CKM) matrix. The Nab precision goal for the measurement of b is Δb ≈ 0.003. In this way, Nab will provide a critical test CKM unitarity, and, combining a and b, sensitive new tests of physics beyond the SM. 

Generalized parton distributions (GPDs) are a key construct for understanding the spatial distribution of quarks and gluons inside nucleons. These distributions are accessed through deeply virtual exclusive processes, such as deeply virtual Compton scattering (DVCS) and deeply virtual meson production (DVMP). We present a spectator model-based parameterization of twist 2, chiral-even, GPDs in the quark, anti-quark, and the gluon sectors. Our model parameters are constrained using high precision electron-nucleon elastic scattering data, deep inelastic scattering data, and recent lattice QCD moment data. The parametrization is used to calculate Compton form factors (CFFs) which allow us to make predictions for DVCS experiments in the kinematic regions currently accessed at Jefferson Lab. Predictions for kinematic regions that will be accessible by the electron ion collider (EIC) are also presented. We also discuss preliminary results on an approach to learn GPDs with a neural network.