Würzburg 2018 – scientific programme

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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz

AKPIK 1: Arbeitskreis Physik, IT & KI (AKPIK) I

AKPIK 1.7: Talk

Monday, March 19, 2018, 18:15–18:30, 70 - HS 00.107

e + /e - Discrimination with Deep Learning Method — •Yu Xu^1,2, Yaping Cheng¹, Christoph Genster^1,2, Philipp Kampmann^1,2, Livia Ludhova^1,2, Michaela Schever^1,2, Rikhav Shah^1,2, Achim Stahl^1,2, and Christopher Wiebusch^1,2 for the JUNO collaboration — ¹IKP-2 Forschungszentrum Jülich — ²III. Physikalisches Institut B, RWTH Aachen University

The Jiangman Underground Neutrino Observation (JUNO) is a multipur- pose neutrino experiment, including the determination of neutrino mass hier- archy, the observation of supernova neutrino and diffuse supernova neutrino background (DSNB), the study of solar neutrino and geo-neutrino, etc. In these studies, it is very helpful and even neccessary to have a good particle discrim- ination. To improve the performance, we are trying to solve this problem with deep learning method, which is really popular nowadays. Deep learning is a ma- chine learning algorithm which learns intrinsic representations of complex data by multi-layer abstractions of information. Recently, this method has been ap- plied in different fields including visual object recognition and detection, speech recognition and many other artificial intelligence computing tasks. We will show our result here.