Authors

Gajendra Gurung

Document Type

Honors Thesis

Abstract

Dark Matter (DM) is a form of matter that makes about 25% of the universe as indicated by cosmological evidence, like weak gravitational lensing, cosmic microwave background, rotation of spiral galaxies, etc. Despite its abundance, DM limitedly interacts with light or normal matter, thus, it is difficult to study and d etect. In search of DM, we go beyond the Standard Model (SM) of Particle Physics by introducing models with particles that only interact weakly with known SM particles. We study different models and search for signatures of such particles in the proton dump mode of neutrino experiments, such as the Mini Booster Neutrino Experiment (MiniBooNE) and the near detector of the Deep Underground Neutrino Experiment (DUNE). Neutrinos are elementary particles with spin- 1/2 and a neutral charge. They come in three flavors: electron, muon, and tau neutrinos. They are elusive because they only interact via weak force and gravity. One of the promising anomaly-free models, which fits the description of low-mass DM is an extension of the Standard Model featuring a gauge boson Z′. Z′’s are leptophilic bosons belonging to U(1) gauge group, which gauges the differences in the lepton number as Lµ −Le, Le −Lτ and Lµ −Lτ . Such low-mass Z′’s are also able to explain the measured value of the muon’s anomalous magnetic moment. We look at the production of Z′’s through meson decay, electron bremsstrahlung, and resonant production by e+e−collision. In this model, we look for electron-like and photon-like signatures as Z′ decays into e± and µ±. We analyze the existing proton beam dump data from MiniBooNE, and GEANT-based simulation data of DUNE near detector to achieve competitive constraints on the gauge coupling parameter gZ′ of Z′. This enables us to forward the understanding of DM. In our work, we found a considerable increase in the expected number of Z′ passing through the MiniBooNE and DUNE detectors. The larger Z′ production is enough to suggest that DUNE could potentially probe new areas of parameter space, which is a qualitative improvement from previously published works.

Publication Date

12-1-2021

Language

English

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