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Abstract:
The discovery of neutrinoless double beta decay (0νββ) would shed light on the persistent puzzle surrounding the origin of neutrino mass and help explain the matter-dominated universe. As one of the leading experiments searching for 0νββ, the KamLAND-Zen experiment has provided a stringent constraint on the neutrinoless double-beta(0νββ) decay half-life in 136Xe using a xenon-loaded liquid scintillator. We report an improved search using an upgraded detector with almost double the amount of xenon and an ultra-low radioactivity container, corresponding to an exposure of 979kg·yr of 136Xe. We have not observed 0νββ yet, but this search makes use of novel algorithms to perform beta-gamma separation using machine learning and tag spallation products on order day time scales. As a result, we obtain a lower limit for the 0νββ decay half-life of T > 2.29×10^26 yr at 90% C.L., corresponding to upper limits on the effective Majorana neutrino mass of 36 – 156 meV using commonly adopted nuclear matrix element calculations. Our improved sensitivity provides a limit that reaches below 50 meV for the first time and is the first search for 0νββ in the inverted mass ordering region.
Bio:
Dr. Aobo Li is a postdoctoral researcher and CoSMS fellow at the University of North Carolina at Chapel Hill. He earned his bachelor's degree from the University of Washington, Seattle, and his Ph.D. from Boston University. His research interest is interpretable, general artificial intelligence algorithms and their marriage to fundamental physics. He is the machine learning group leader of three world-class neutrinoless double beta decay experiments: KamLAND-Zen, MAJORANA DEMONSTRATOR, and LEGEND. His work has helped his advisors and close collaborators earn two U.S. National Science Foundation and one U.S. Department of Energy grant.