Erlangen 2026 – scientific programme

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T: Fachverband Teilchenphysik

T 59: Neutrino Astronomy III

T 59.6: Talk

Wednesday, March 18, 2026, 17:30–17:45, KS H C

The Pacific-Ocean Neutrino Experiment Design Optimization with Machine-Learning — •Kristian Tchiorniy and Lukas Heinrich for the P-ONE collaboration — Technische Universität München, Physik-Department, James-Frank-Str. 1, Garching bei München, D-85748, Germany

The geometrical layout of any experiment or detector can have a large impact on its ability to produce meaningful outcomes for physics. Oftentimes we see that optimal geometries can be unintuitive. Studying and optimizing this is therefore essential. This has become a relevant topic for the optimization of cubic-kilometer-scale neutrino telescopes, in particular, the Pacific Ocean Neutrino Experiment (P-ONE), which is planned to be constructed in the coming years. With more than 70 lines across multiple kilometers of seafloor, the P-ONE geometry is yet to be finalized and studies on how to place these lines can inform crucial design decisions. In this presentation, the possible geometric optimization of such an experiment will be discussed, in particular, how it will employ machine-learning techniques to apply end-to-end optimization.

Keywords: Machine learning; End-to-end optimization; Neutrino astronomy; Experiment design