U.S. Department of EnergyOffice of Scientific and Technical Information
Identifying Interaction Location in SuperCDMS Detectors
Abstract
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 aremore »
- Authors:
-
;
- Univ. of Minnesota, Minneapolis, MN (United States); University of Minnesota, Minneapolis, MN
- Univ. of Minnesota, Minneapolis, MN (United States)
- University of Minnesota, Saint Paul, MN (United States)
- Publication Date:
- Other Number(s):
- 10.34740/kaggle/dsv/2660709
- DOE Contract Number:
- SC0021395
- Research Org.:
- University of Minnesota, Minneapolis, MN
- Sponsoring Org.:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- Collaborations:
- SuperCDMS Collaboration
- Subject:
- 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; FAIR4HEP, SuperCDMS, Dataset, Machine Learning
- OSTI Identifier:
- 2281643
- DOI:
- https://doi.org/10.34740/kaggle/dsv/2660709
Citation Formats
Li, Taihui, Cushman, Priscilla, and Fritts, Matthew. Identifying Interaction Location in SuperCDMS Detectors. United States: N. p., 2024.
Web. doi:10.34740/kaggle/dsv/2660709.
Li, Taihui, Cushman, Priscilla, & Fritts, Matthew. Identifying Interaction Location in SuperCDMS Detectors. United States. doi:https://doi.org/10.34740/kaggle/dsv/2660709
Li, Taihui, Cushman, Priscilla, and Fritts, Matthew. 2024.
"Identifying Interaction Location in SuperCDMS Detectors". United States. doi:https://doi.org/10.34740/kaggle/dsv/2660709. https://www.osti.gov/servlets/purl/2281643. Pub date:Wed Jan 17 23:00:00 EST 2024
@article{osti_2281643,
title = {Identifying Interaction Location in SuperCDMS Detectors},
author = {Li, Taihui and Cushman, Priscilla and Fritts, Matthew},
abstractNote = {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/},
doi = {10.34740/kaggle/dsv/2660709},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2024},
month = {1}
}