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T: Fachverband Teilchenphysik

T 37: Neutrino physics without accelerators IV

T 37.5: Vortrag

Dienstag, 31. März 2020, 18:00–18:15, L-2.017

Accidental background reduction using artificial neural networks in the Double Chooz experiment — •Markus Bachlechner, Christopher Wiebusch, Achim Stahl, and Philipp Soldin — III. Physikalisches Institut B, RWTH Aachen University

Double Chooz is a reactor anti-neutrino disappearance experiment, which took data from 2011 until the end of 2017. The main purpose is a precise measurement of the neutrino mixing angle θ₁₃ with two identical liquid scintillator detectors. Neutrinos are detected via the signature of the inverse beta decay (IBD), which is characterized by a prompt signal from a positron and a delayed signal from neutron capture. A major background is the random association of uncorrelated events that pass the selection criteria individually. The current separation is done in a multivariate analysis, performed by a multi-layer perceptron. In this talk a method to improve the current reduction by deep learning techniques is presented.