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Directorate for Mathematical and Physical SciencesNSF · NSFNSF

Probing the Majorana Nature of Neutrinos with KamLAND-Zen

Christopher Grant·Trustees of Boston University, MA·2023–2026·ACTIVE
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INSTITUTION

Trustees of Boston University, MA

PRINCIPAL INVESTIGATOR

Christopher Grant

FUNDING

$480K

YEAR

2023

MOONBASE SCORE

1/100

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Abstract

Neutrinos are electrically neutral, weakly interacting, subatomic particles and are one of the most abundant particles in the universe. Our understanding of the fundamental nature of neutrinos has rapidly progressed in recent decades, yet we are still unable to some very basic questions. What is the absolute mass of the neutrino? Why are neutrino masses so small compared to other elementary particles? How did the neutrino obtain a mass? The answers to these questions could be intimately related to the neutrino being its own antiparticle, known as a Majorana particle, and might also explain the absence of anti-matter in the universe. The PI will shed light on these questions by searching for a hypothetical nuclear process called neutrinoless double beta decay. An observation of this process would provide direct proof that neutrinos are Majorana particles; however, it will be extremely difficult to observe due to the vast number of very similar processes constantly taking place inside experiments. A competitive search requires a large quantity of double beta decay isotope and exquisite suppression of backgrounds. Therefore, the PI will upgrade the world-leading neutrinoless double beta decay experiment, KamLAND-Zen, with state-of-the-art data acquisition electronics and novel machine learning algorithms. This exciting area of experimental research will provide an excellent platform for training students and postdocs in advanced technical skills that are highly sought-after in in academia, industry, and national laboratories. In the last year, KamLAND-Zen (a liquid scintillator detector in Japan loaded with Xe-136) began searching for neutrinoless double beta decay in new regions of phase space for the first time. The PI is implementing major enhancements to KamLAND-Zen while continuing to collect and analyze new data. The first enhancement involves a state-of-the-art deep learning algorithm recently developed by the PI, called KamNET, which will be used to search for the elusive two-neutrino double beta decays of Xe-136 excited states. The PI will also use KamNET to perform a combined analysis over all present and past KamLAND-Zen data to maximize its sensitivity to neutrinoless double beta decay. The second enhancement involves the installation and commissioning of zero dead-time waveform digitizer electronics with online event tagging logic, known as MoGURA2. MoGURA2 will be used to reduce the leading backgrounds in the search for neutrinoless double beta decay on KamLAND-Zen. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Directorate for Mathematical and Physical SciencesArtificial Intelligence (AI)NUCLEAR PRECISION MEASUREMENTSworthypresentreflectsaftercouldrecentonlinequestionsisotopemajoranaMachine learningNeutrinosMajorana particlesNeutrinoless double beta decayKamLAND-ZenDeep learning algorithmsNuclear physicsXenon-136Waveform digitizer electronicsExperimental research.

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