RUI: Experimental Subatomic Physics at Virginia Union University

该奖项支持一位弗吉尼亚联合大学（VUU）教授和学生与他一起工作，为两项旨在了解中子基本结构和动力学的高影响力测量做出重要贡献。该奖项将通过配备一个缓慢的控制开发设施，这将是有用的亚原子物理和潜在的应用，加强研究基础设施提供给VUU物理教师。学生的发展将通过增加研究机会和接触世界领先的研究设施来加强，该研究设施拥有经验丰富的科学家和工程师组成的多国小组，这些参与者将获得硬件和软件方面的培训和经验，这对他们未来的STEM职业生涯非常宝贵。 该奖项由物理学部门和HBCU-UP计划共同支持，该计划位于STEM卓越股权部门内。 计划中的研究有助于杰斐逊实验室的BONUS 12和TDIS实验，这些实验使近自由中子靶的研究成为可能，并寻求进一步完善中子结构函数。中子结构函数的知识目前代表了社区的理解差距，并影响中微子散射测量。建议的工作有助于开发一个缓慢的控制系统，以监测漂移和目标气体系统的TDIS实验。在另一项调查中，PI将合作利用AI和已发布的结构功能数据进行新的F2 A计算。为此目的的工作已被证明是亚原子物理学界感兴趣的，这种方法将是对目前可用的参数化的补充，因为它利用了一个经过训练的人工神经网络来计算这个量，与内插法相比/该奖项反映了NSF的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持和更广泛的影响审查标准。

This award supports one Virginia Union University (VUU) professor and students working with him in making important contributions to two high-impact measurements aimed at understanding the fundamental structure and dynamics of the neutron. The award will strengthen the research infrastructure available to VUU faculty in physics by outfitting a slow controls development facility that will be useful for subatomic physics and potential applications. Student development will be enhanced by the added availability of research opportunities and exposure to a world-leading research facility that hosts a multi-national group of experienced scientists and engineers, and these participants will gain training and experience in hardware and software that will be invaluable for their future STEM careers. This award is jointly supported by the Division of Physics and the HBCU-UP Program within the Division of Equity for Excellence in STEM. The planned research contributes to the BONuS12 and TDIS experiments at Jefferson Lab, which enable the study of near-free neutron targets and seek to further refine the neutron structure function. Knowledge of the neutron structure function currently represents a gap in the community’s understanding, and affects neutrino scattering measurements. The proposed work contributes to the development of a slow controls system to monitor drift and target gas systems for the TDIS experiment. In a separate line of inquiry, the PI will collaborate on utilizing AI and published structure function data for a new F2A calculation. Work to this end has proven interesting to the subatomic physics community and this method will be complementary to the parameterizations that are presently available, in that it utilizes an artificial neural network that is trained to calculate this quantity, compared to interpolation/extrapolation from fitting routines.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.