Quasi-Background-Free Neutrinoless Double-Beta Decay Searches with LEGEND: Statistical Methods and Cryogenic SiPM Characterization
| dc.contributor.advisor | Detwiler, Jason | |
| dc.contributor.author | Borden, Samuel | |
| dc.date.accessioned | 2026-02-05T19:40:22Z | |
| dc.date.available | 2026-02-05T19:40:22Z | |
| dc.date.issued | 2026-02-05 | |
| dc.date.submitted | 2025 | |
| dc.description | Thesis (Ph.D.)--University of Washington, 2025 | |
| dc.description.abstract | As an electrically neutral and massive fermion, the neutrino is the only Standard Model particle whose Lagrangian mass term could include a Majorana term. The nature of the neutrino mass is exciting because it is inherently Beyond the Standard Model: neutrino oscillations show that the neutrino has a mass and that it violates conservation of individual lepton numbers, in direct contradiction to predictions of the Standard Model. The most sensitive probe of the Majorana nature of the neutrino is the search for a hypothetical second-order weak decay called neutrinoless double-beta decay. Observation of this decay would prove that conservation of total baryon minus lepton number is violated and that the neutrino has a Majorana mass term. The Large Enriched Germanium Experiment for Neutrinoless-double beta Decay (LEGEND) collaboration is searching for the neutrinoless double-beta decay of 76Ge by deploying an array of highly enriched germanium detectors inside of a liquid argon cryostat. In order to fully cover the allowed parameter space for inverted ordered light Majorana neutrinos, the LEGEND collaboration is pursuing a phased approach. The already-built LEGEND-200 experiment aims for a half-life discovery sensitivity of 1E+27 years using 200 kg of enriched detectors, and the proposed tonne-scale follow-on experiment LEGEND-1000 aims for a discovery sensitivity of 1E+28 years. The success of these experiments rests in their great ability to reduce external background through techniques such as pulse shape discrimination and liquid argon scintillation anti-coincidence vetoing. The LEGEND-200 experiment has completed its first year of searching for neutrinoless double-beta decay with an accumulated exposure of 61 kg·yr. This thesis reports the first frequentist statistical analysis performed on data from the LEGEND experiment. A new Python-based framework, freqfit, is introduced to robustly and rapidly produce frequentist statistical inference on unbinned data. Using this framework, no evidence of neutrinoless double-beta decay is found (p = 0.1), and a lower limit on the half-life is placed at T_1/2 > 5 × 1E+25 years (90% confidence level). The background index for the group of detectors mainly comprised of the geometry to be used in LEGEND-1000 is computed to be 5^+3_-2 × 1E−4 counts/keV/kg/yr. A frequentist joint analysis incorporating LEGEND-200 data and the data from two recent 76Ge experiments, the MAJORANA DEMONSTRATOR (MJD) and Germanium Detector Array (GERDA), is also presented. The combined analysis also observes no evidence for a signal (p = 0.29) and results in the strongest lower limit, and highest half-life sensitivity, on the half-life in 76 Ge to-date: T_1/2 > 1.9 × 1E+26 years (90% confidence level). This half-life limit can be converted into a limit of the effective Majorana mass of the neutrino, assuming mediation by a light Majorana neutrino and a range of phenomenological nuclear matrix elements, and yields mββ < 75 − 200 meV (90% confidence level). With fewer than one expected count due to accidental radioactive background near the Q-value of neutrinoless double-beta decay, LEGEND-1000 will be a quasi-background-free experiment. The behavior of the frequentist profile likelihood ratio treatment for statistical inference on unbinned data from quasi-background-free experiments is investigated. It is found that test statistic distributions in this regime deviate from the asymptotic form predicted by Wilks’ theorem — it is required to generate pseudo-experiments for these statistical analyses. The coverage is computed for ensembles of pseudo-experiments generated with a known Poisson-distributed background index. We show that the profile likelihood ratio treatment guarantees coverage very close to the nominal value for these ensembles. In order for LEGEND-1000 to reach its nominal background index goal of 1E−5 counts/keV/kg/yr, it is necessary that its liquid argon detector collects as much scintillation light in its silicon photomultiplier (SiPM) readout as possible. The detection efficiency of the liquid argon system is directly proportional to the photon detection efficiency (PDE) of the SiPMs. The PDE is a well-known quantity reported by the manufacturer, at room temperature; however, LEGEND operates its SiPMs at cryogenic temperature. This work describes the operation and results of a cryogenic SiPM characterization test stand built at the University of Washington. We report that two SiPMs exhibit a nearly 20% drop in their PDE at liquid nitrogen temperature relative to their room temperature values. This drop was measured for the green wavelengths (562 nm) of light that match the optical emission spectra of light collection technology for LEGEND-1000. This drop in the PDE represents an important input for forecasting the background index for LEGEND-1000 in order to guarantee that it reaches its discovery sensitivity goal. | |
| dc.embargo.terms | Open Access | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | Borden_washington_0250E_29158.pdf | |
| dc.identifier.uri | https://hdl.handle.net/1773/55294 | |
| dc.language.iso | en_US | |
| dc.rights | none | |
| dc.subject | Frequentist Statistics | |
| dc.subject | Neutrino Physics | |
| dc.subject | Neutrinoless Double-Beta Decay | |
| dc.subject | Nuclear physics and radiation | |
| dc.subject | Semiconductor Physics | |
| dc.subject | Silicon Photomultipliers | |
| dc.subject | Physics | |
| dc.subject.other | Physics | |
| dc.title | Quasi-Background-Free Neutrinoless Double-Beta Decay Searches with LEGEND: Statistical Methods and Cryogenic SiPM Characterization | |
| dc.type | Thesis |
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