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Abstract:
The IceCube Neutrino Observatory, located deep beneath the surface of the geographic South Pole, instruments over one cubic kilometer of Antarctic ice with 5,610 digital optical modules (DOMs) to detect neutrino interactions via Cherenkov light. While the main detector is designed to detect PeV astrophysical neutrinos, the subdetector IceCube-DeepCore, equipped with denser and higher quantum efficiency DOMs, is visible to GeV-scale neutrinos. Time and charge information from detected and calibrated photons are utilized to reconstruct neutrino interactions within the IceCube detectors. Machine learning techniques have been developed and applied to enhance event reconstruction, yielding significant improvements in both runtime speed and reconstruction resolution compared to traditional algorithms. In this seminar, I will discuss the application of Convolutional Neural Networks (CNNs) in reconstructing atmospheric neutrinos in the DeepCore subdetector, as well as the latest neutrino oscillation measurements benefited by using the CNN-reconstructed and selected sample.
About the Speaker:
Dr. Yu is a research assistant professor at the University of Utah working on the IceCube experiment. Dr. Yu now serves as one of the 2 conveners of IceCube reconstruction working group and she is on the IceCube speaker committee. She is also one of the 2 representatives of early career scientists for IceCube. She did her PhD at Argonne National Lab working on the NOvA experiment, where she used CNN to reconstruct electron neutrino energy and applied it to nue appearance measurement. She graduated and joined IceCube at the end of 2020 and started working on low-energy atmospheric neutrino reconstruction using machine learning techniques and later applied the developed ML tools to select the DeepCore sample for oscillation analyses. She also works on searching for astrophysical neutrinos from AGNs.
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Meeting ID 会议号: 96472179513
Begin Time 开始时间: 2024-04-25T15:30:00
Duration 持续时长: 120
Meeting URL 会议链接:: https://zoom.us/j/96472179513?pwd=djVFYUd6eThRRkt4UTh3MWltVHFUdz09
HostKey 主持人密钥: 068014
Password 会议密码: 637159