Speaker
Zoë Rechav
(University of Wisconsin at Madison)
Description
The atmospheric neutrino self-veto plays a critical role in characterizing the atmospheric neutrino background, not only for IceCube but for neutrino telescopes in general. I would like to present recent updates to the modeling of the downgoing atmospheric neutrino self-veto in IceCube using gradient boosted decision trees. The GNN meeting is ideal for this contribution, as this work directly aligns with GNN’s goals of fostering collaboration, enabling comparisons across detectors with different systematics and contributing to a more unified treatment of atmospheric neutrino backgrounds across neutrino telescopes.
Primary author
Zoë Rechav
(University of Wisconsin at Madison)
