Commissioning and first data analysis of the JUNO detector

Neutrinos are among the most abundant yet elusive particles in the Standard Model. The observation of neutrino oscillations demonstrates that they have mass and that flavor states are superpositions of mass eigenstates. This mixing is characterized by three angles, two mass-squared differences, and a CP-violating phase. One of the major open questions in neutrino physics is the ordering of the mass eigenstates: whether it follows the normal ordering, with \(m_1 < m_2 < m_3\), or the inverted ordering, with \(m_3 < m_1 < m_2\). JUNO is a multipurpose neutrino experiment designed to determine the neutrino mass ordering with high precision, as well as to explore other fundamental properties of neutrinos. Located in southern China, JUNO features a 20-kiloton liquid scintillator detector enclosed in a 35-meter acrylic sphere, instrumented with 17,612 20-inch PMTs and submerged in ultrapure water for shielding and muon veto. The detector is situated 53 km from two nuclear power plants and is optimized for detecting reactor antineutrinos via the inverse beta decay (IBD) reaction: $\bar{\nu}_e + p \to e^+ + n$. The correlated coincidence between the prompt positron signal and the delayed neutron capture provides a clean experimental signature. In December 2024, JUNO has entered the commissioning phase and begun filling the CD—initially with water, which is gradually being replaced with LS. To achieve its ambitious physics goals, JUNO requires both sufficient statistics and unprecedented energy resolution. The first requirement is intrinsically linked to the ability to effectively select IBD candidate events. This thesis focuses on the development of an event selection algorithm capable of identifying temporally and spatially correlated events of various types with high efficiency and purity. The algorithm has been validated and used to conduct two parallel analyses: one on the radiopurity of the LS, and another on spallation neutrons. The monitor of radiopurity is crucial during the filling phase: a fast coincidence, experimentally and topologically very similar to an IBD event, between the \(\beta\)-decay of \(^{214}\)Bi and the subsequent \(\alpha\)-decay of \(^{214}\)Po was tagged using the developed algorithm, enabling hourly monitoring of \(^{222}\)Rn contamination and extraction of the \(^{238}\)U contamination level, which was found to be compatible with the collaboration’s requirements - namely, the concentration of U has to be below \(1 \cdot 10^{-15}\) g/g. The second crucial requirement for JUNO is achieving an unprecedented energy resolution of 3% at 1 MeV, which strongly depends on the detector’s spatial response uniformity. This thesis addresses the study of such non-uniformity by using spallation neutrons as a stable, uniform calibration source. A vertex reconstruction algorithm based on the timing response of the 17,612 large-PMTs was developed. The timing behavior of the detector and the synchronization of the readout electronics were analyzed, and a numerical time-of-flight map was created to account for optical path distortions due to refraction in the hybrid water–LS setup. These elements allowed building a time-based likelihood method for precise vertex estimation. Applying this algorithm, together with neutron tagging, enabled the production of a non-uniformity correction map, improving the energy resolution by about 40%.