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Development and tests of JUNO electronics readout system and study of JUNO performance for core collapse supernova model discrimination: From JUNO back-end card hardware tests to statistical methods for supernova studies with JUNO

par Petitjean, Pierre-Alexandre
Président du jury Vanlaer, Pascal
Promoteur Pauly, Nicolas
Co-Promoteur Clerbaux, Barbara
Publication Non publié, 2024-10-18

Thèse de doctorat

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• Statistiques

Résumé :

Neutrinos are very elusive particles as they only interact with matter trough weak interaction. Many uncertainties remain such as their mass ordering. The Jiangmen Underground Neutrino Observatory (JUNO), currently under construction in China, aims to determine the neutrino mass hierarchy and to measure oscillation parameters with sub-percent precision. The detector consists of 20 kilotons of liquid scintillator equipped with 17,612 20-inch photomultiplier tubes and 25,600 3-inch small photomultiplier tubes, providing a photocathode coverage of 77%. The electronics system is divided into two main parts: the front-end system, located underwater, which handles analog signal processing, and the back-end system, located outside water, which includes the data acquisition system and the trigger.This thesis presents two main contributions to the JUNO experiment: the development of the Back-End Card for the photomultiplier tube readout system and the analysis of supernova model discrimination using neutrino detected with JUNO. The development of the Back-End Card addresses challenges such as signal integrity, mitigation of crosstalk, power distribution, and installation complexity. Through multiple design iterations and rigorous testing, the final design was optimized for mass production. By 2023, 180 Back-End Cards were produced, tested, and successfully installed as part of the JUNO detector, ensuring the system's reliable operation.Supernovae are among the most significant cosmic events, producing essential elements and leaving behind remnants like neutron stars and black holes. Despite their importance, the mechanisms behind these stellar explosions are still not fully understood while neutrinos are playing a important role in the core collapse. By studying the neutrino production during the core collapse, one can learn valuable insights about the physics phenomena inside the star. Two likelihood methods—binned and unbinned—were employed to distinguish between different core-collapse supernova models. The unbinned method, particularly using the inverse beta decay channel, proved more effective by capturing fine details in time and energy distributions, crucial for model discrimination. The study showcases that 300 inverse-beta decay neutrino events in JUNO-corresponding to a supernova at a distance of at least 21 kpc—are sufficient to distinguish between these models with high accuracy.These contributions illustrate JUNO's capacity to address key questions in neutrino physics. The first data taking runs are foreseen for Summer 2025.