Speaker
Description
At the forefront of investigating neutrinoless double beta decay (0νββ) using 76Ge-enriched detectors, the LEGEND experiment is driven by the quest to unravel the mysteries of neutrinos and explore physics beyond the Standard Model. In its initial phase, LEGEND-200 deploys 200 kg of germanium at INFN Gran Sasso National Laboratory, aiming for a discovery half-life sensitivity surpassing 10$^{27}$ years. The subsequent phase envisions the operation of 1000 kg of germanium, pushing the sensitivity threshold beyond 10^${28}$ years.
An integral component of the LEGEND experiment is the meticulous analysis of acquired waveforms, leveraging Pulse Shape Discrimination (PSD) to identify Single-Site Events (SSE) and Multi-Site Events (MSE), essential for isolating potential 0$\nu\beta\beta$ candidates. SSE, characterized by energy deposition at a specific point, contrast with MSE, where energy is distributed across multiple locations within a single Ge detector, leading to complex waveforms with overlapping rising edges and distinctive features. Each of these locations contributes to the overall waveform, resulting in a nuanced signal pattern.
In addition to PSD, this study introduces deep learning, specifically transformers, to enhance event discrimination. Abundant training data, derived from weekly calibration runs of LEGEND-200, facilitates the transformer model's ability to learn from sequential data. By optimizing event discrimination, especially in the low-energy range, this innovative approach contributes significantly to the precision of the LEGEND experiment. The combination of standard analysis tools and deep learning techniques positions LEGEND at the forefront of experimental endeavours, promising a deeper understanding of neutrino physics and the potential for breakthroughs in the search for exotic physics beyond the Standard Model.
| Type of contribution | Talk: 30 minutes. |
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