Algorithm, Data, and Hardware: The Three AI Thrusts That Accelerate Neutrinoless Double-Beta Decay Searches

The discovery of Majorana neutrinos would fundamentally revise our understanding of physics and the cosmos. Currently, the most effective experimental probe of the Majorana neutrinos is neutrinoless double-beta decay(0vββ). Meanwhile, the explosive growth of artificial intelligence over the last decade has brought new opportunities to 0vββ experiments. Efficient AI algorithms are now poised to streamline various analysis processes as well as help delivering the most sensitive search for 0νββ decays to date. This presentation will begin with an overview of the application of AI algorithms in both current- and next-generation 0νββ experiments, highlighting their importance in advancing the experimental capabilities. While the algorithmic aspect of AI often takes center stage, it is not the sole avenue of AI. The latter part of this talk will delve into two new AI research frontiers that have not garnered sufficient attention from the nuclear physics community: data-centric AI, which focuses on enhancing the preprocessing and cleaning of datasets, and hardware-AI co-design, which aims to embed AI algorithms directly onto data acquisition boards to obtain real-time physics information. By converging the strengths of algorithm, data, and hardware, we aim to maximize the velocity at which AI can propel the discovery of 0νββ decays thereby unravel the mysteries of Majorana neutrinos.