Erlangen 2026 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 71: Data, AI, Computing, Electronics VII
T 71.3: Vortrag
Donnerstag, 19. März 2026, 16:45–17:00, KH 00.024
Investigating Robustness of Newtonian Noise Mitigation using Deep Learning at the Einstein Telescope — •Jan Kelleter1, Markus Bachlechner2, David Bertram2, Johannes Erdmann1, Patrick Schillings1, and Achim Stahl2 — 1III. Physikalisches Institut A, RWTH Aachen — 2III. Physikalisches Institut B, RWTH Aachen
The Einstein Telescope is a proposed gravitational wave detector of the third generation. It aims to improve sensitivity by at least an order of magnitude compared to current detectors. The dominant noise source in the region of 1 to 10 Hz is expected to be Newtonian Noise (NN) from seismic activity in the surrounding rock. In order to reach the desired sensitivity, NN must be actively mitigated. Seismometers will be installed in boreholes around the mirrors to measure the seismic activity. In this talk, we investigate the robustness of neural networks designed for Newtonian Noise mitigation against different instrumental failures.
Keywords: Newtonian Noise; Einstein Telescope; Seismometer; Deep Learning; Gravitational Wave