Searching for Neutrino Tridents in the NOvA Near Detector
Thesis/Dissertation
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OSTI ID:3006316
- Indiana U.
This dissertation presents a search for neutrino trident production in the NOvA near detector through the coherent ``dimuon" channel: $$\nu_\mu +\hspace{1pt}\text{X} \rightarrow \nu_\mu + \mu^- + \mu^+ +\hspace{1pt}\text{X}$$. Trident production is a rare, purely electroweak process with sensitivity to physics beyond the Standard Model. The theoretical background, motivation for studying the process, and previous experimental measurements are reviewed. The analysis uses data collected by the NOvA near detector (ND) from Fermilab's Neutrinos at the Main Injector (NuMI) beam between November 2014 and February 2024, corresponding to an exposure of $$25.5\times 10^{20}$$ protons on target. The ND is a segmented tracking calorimeter located 800~m from the beam target, receiving neutrinos with a mean energy of 2~GeV. A multi-pass background reduction strategy is implemented, including the development of a novel dimuon-specific tracking technique. Trident candidates are identified using a boost ed decision tree classifier trained on simulated signal and background events. Limited background Monte Carlo statistics necessitate the use of functional fits to sideband data, which are extrapolated to estimate backgrounds in the signal region. The unblinded data contain 9 trident-like events, with an estimated background of 5.66 $$\pm$$ 5.15 events. This yields a best fit estimate of 3.34 tridents compared to the Standard Model prediction of 4.66. A profiled Feldman-Cousins method is used to determine a 90\% confidence interval of [0,9.1] on the number of signal events, corresponding to an upper limit of 1.95$$\times$$ the Standard Model prediction. This result represents the lowest energy search for trident events to date, and the first experimental contribution to the process in 27 years.
- Research Organization:
- Indiana U.
- Sponsoring Organization:
- US Department of Energy
- DOE Contract Number:
- 89243024CSC000002
- OSTI ID:
- 3006316
- Report Number(s):
- FERMILAB-THESIS-2025-14; oai:inspirehep.net:3082417
- Country of Publication:
- United States
- Language:
- English
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