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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Bethel University |
| Country | United States |
| Start Date | Aug 15, 2021 |
| End Date | Jul 31, 2025 |
| Duration | 1,446 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2110972 |
A major scientific achievement of the 20th century was the development of the Standard Model of particle physics. The Standard Model is a successful theory, agreeing with decades of experimental observations involving weak, electromagnetic, and strong interactions. The Higgs boson discovery at the Large Hadron Collider (LHC) at CERN completes the suite of predicted Standard Model particles and provides a mechanism for generating elementary particle masses.
However, the current formulation of the Standard Model does not account for the observed value of the Higgs boson mass, making discovery of physics beyond the Standard Model a primary goal of the LHC experiments, including those being carried out in this project involving the Compact Muon Solenoid (CMS).
This work will focus on searches for new physics, as well as upgrade developments toward the silicon-based outer tracker for the CMS experiment during the High-Luminosity LHC run in the mid-2020s. This research will also engage undergraduate students in CMS data analysis and detector hardware projects at Bethel University, Fermilab, and CERN. The primary analysis goal is to search for vector-like quark (VLQ) pair production with the record-breaking CMS dataset.
Several deep machine learning algorithms will be developed to identify hadronic decays of bottom quarks, top quarks, W, Z, and Higgs bosons, which are all reconstructed as jets with unique internal structure. With these deep learning techniques, VLQ pair production searches can be dramatically improved to include identification and mass reconstruction.
Specifically, this work will use image recognition machine learning techniques to develop jet identification algorithms for HL-LHC studies. Additionally, extensive development will be made on design features and assembly procedures for upgraded silicon tracker modules. The Bethel CMS group will characterize silicon sensors with updates to an existing probe station and will participate in module production tests at Fermilab.
The Bethel group is also engaged with several outreach and education activities, reaching high school students and the general public through tours of detector exhibits and preparing new students and collaborators for CMS analysis via an annual Data Analysis School and hands-on summer tutorials. The Bethel group will also develop inquiry-based Open Data analysis exercises appropriate for upper-level modern physics courses and/or advanced laboratory courses to be shared with other universities.
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.
Bethel University
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