Speaker
Description
The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino program designed to address fundamental questions in neutrino and astroparticle physics. ProtoDUNE, operating at the CERN Neutrino Platform, serves as a full-scale prototype for the DUNE Far Detector. In particular, the ProtoDUNE Vertical Drift (ProtoDUNE-VD) detector provides a powerful testbed for validating reconstruction and event selection techniques for future DUNE operations. In addition to detector R&D, ProtoDUNE enables a novel parasitic beam-dump search for beyond-the-Standard-Model (BSM) particles. Operating on the surface, the ProtoDUNE-VD modules are exposed to an intense flux of cosmic rays, thus requiring a dedicated trigger. Furthermore, neutrinos produced in the T2 target area from meson decays constitute a relevant background that must be characterized a priori and well understood. In this poster, we present the first studies based on a trigger designed to identify neutrino candidates at ProtoDUNE-VD. ProtoDUNE-VD’s high-resolution LArTPC imaging enables detailed reconstruction of decay and scattering signatures. This work demonstrates the complementarity of traditional tools, such as Pandora, and modern machine-learning approaches, providing key input for atmospheric neutrino and rare-event searches in the future DUNE Vertical Drift program.