Engineering topics

Cushman, Priscilla

Publications and source records attributed to Cushman, Priscilla.

3 records

DOE OSTI2024

FAIR Framework for Physics-Inspired AI in High Energy Physics (Final Technical Report)

The main deliverable of this proposal was to publish data from high energy physics experiments in a FAIR format so that non-specialists could develop machine learning technologies using our data. The Minnesota team of Profs. Cushman, Furmanski and Rusack, from the high energy experiments CDMS, Micro-Boone and CMS, respectively, and Prof J. Sun from Computer Science worked to organize the data, to provide code to access the data, and where relevant provide documentation describing the data. The FAIR4HEP collaboration was formed with groups from UC San Diego, MIT, and the University of Illinois, with the principal investigator was Dr. Huerta. Collectively we collaborated on the publication of datasets from the LHC experiments. Members of the Minnesota group contributed to the common papers published by the collaboration

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Identifying Interaction Location in SuperCDMS Detectors

The Super Cryogenic Dark Matter Search (SuperCDMS) experiment uses silicon and germanium particle detectors operated at temperatures of ∼ 30 mK to search for Weakly Interacting Massive Particles (WIMPs), which are candidate dark matter particles that interact weakly with nuclei in the detectors. In operating these detectors, it is required not only to measure the energy of the interaction between the WIMP and the nuclei, but also to reconstruct where the interaction occurred, as the location can be used to separate background interactions from signal and to correct for variations with the location of the energy response. In this project, we, as a team from the University of Minnesota, aim to address the problem of accurately reconstructing the locations of interactions in the SuperCDMS detectors using machine learning methods. The dataset we provided here includes interactions at thirteen different locations from test data taken at the University of Minnesota. For each interaction, a set of parameters was extracted from the signals from each of the five sensors. These parameters represent information known to be sensitive to interaction location, including the relative timing between pulses in different channels, and features like the pulse shape. The relative amplitudes of the pulses are also relevant but due to instabilities in amplification during the test, this data is not included. The parameters included for each interaction are described in our project document. For more details, feel free to check our Github page: https://fair-umn.github.io/FAIR-UMN-CDMS/

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Report of the 2021 U.S. Community Study on the Future of Particle Physics (Snowmass 2021)

In 2019, with the construction of the projects supported by the 2014 P5 process well underway or in an advanced stage of planning, the Division of Particle and Fields (DPF) of the American Physical Society (APS) began to prepare a new community study of U.S. high energy physics (HEP) for the decade of 2025 – 2035, and beyond. This “Snowmass 2021” HEP Community Planning Exercise began formally with a kick-off meeting at the 2020 APS April Meeting and a Community-wide Planning Meeting in October of 2020. The exercise was to conclude in July of 2021 with a workshop in Seattle hosted by the University of Washington. The COVID-19 pandemic severely disrupted these plans. Work was paused from January to September of 2021 to lighten the burden on our younger scientists. We resumed work by September of 2021 and, despite the continuing challenges of COVID-19, our community was well prepared for the Seattle meeting, which had been rescheduled for July 17–26, 2022.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗