Thesis
Improving the sensitivity to neutrinoless double beta decay in SNO+
- Abstract:
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SNO+ is a multi-purpose neutrino detector located 2 km underground in Sudbury, Canada. The inside of the detector is currently being filled with liquid scintillator, which will then be loaded with tellurium-130 in order to search for neutrinoless double beta decay (0νββ).
This thesis concerns itself with ways to improve the sensitivity of SNO+ to this process and achieves it in two ways. Firstly, it is demonstrated that an increase of the light output of 15−20% can be achieved with the addition of an amine to the tellurium-loaded scintillator mixture. The higher light output results in better energy resolution of the detector, which conversely translates in higher sensitivity to 0νββ. Furthermore, it is demonstrated that this addition is important for stabilisation of the tellurium-loaded scintillator with regards to water exposure. Secondly, the application of multi-site event classification techniques in signal extraction in SNO+ is discussed. A likelihood analysis including topological and timing pulse shape discrimination (PSD) parameters as additional observables is presented. These PSD parameters differentiate between interactions with point-like and multi-site energy depositions. Their use can therefore break the degeneracy between any "point-like" 0νββ signal and more distributed energy depositions from radioactive background decays involving γs, such as from cosmogenic or external sources. The resulting expected lower limit on 0νββ half-life is 1.80 ×10^26 years at 90% confidence after 3 years of data taking. Furthermore, it is demonstrated that this analysis would allow for a genuine 0νββ observation for effective Majorana mass of 75−181 meV at 99% confidence after 3 years, which is 40−50% lower than what is achievable without the inclusion of PSD.
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- Files:
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(Preview, Dissemination version, pdf, 13.5MB, Terms of use)
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Authors
Contributors
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Physics
- Role:
- Supervisor
- Funder identifier:
- https://ror.org/057g20z61
- Grant:
- ST/N504233/1
- Programme:
- STFC DTP, project reference: 1793321
- DOI:
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- Language:
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English
- Keywords:
- Subjects:
- Deposit date:
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2025-10-16
- ARK identifier:
Terms of use
- Copyright holder:
- Tereza Kroupová
- Copyright date:
- 2020
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