In this project, I investigate the performance of the ProtoDUNE Far Detector by detector response between real and simulated data, with a particular focus on the Horizontal Drift (PDHD) prototype detector. Through this work, I have developed a deeper understanding of the detection principles of Liquid Argon Time Projection Chambers (LArTPCs).My study focuses on cosmic rays, which are expected to be the leading high-energy background activity in the Far Detector of the DUNE experiment. In particular, I compare cosmic ray data from the PDHD in both simulation and real data, examining how the properties of Trigger Primitives (TPs) depend on the track angle. By quantifying these variations, the goal is to provide insights that could inform the development of future online trigger strategies for more efficient data storage of the most physically interesting events.My analysis aims to demonstrate the feasibility of using collection plane TP properties to accurately identify track angles, though estimation of out-of-plane angles may require additional information from induction planes. The report addresses noise characterization and clustering challenges associated with high-multiplicity, noisy real data. Although computational efficiency may be improved, the findings contribute valuable insights for future online trigger strategies and data acquisition workflows in next-generation neutrino detectors

Julia Favaro's project as part of the Member States Summer Student Programme 2025 at the EP-NU group @CERN.