Speakers
Description
The KM3NeT Collaboration is currently constructing two large-scale underwater neutrino detectors in the Mediterranean Sea: ARCA, optimized for high-energy astrophysical neutrino detection, and ORCA, designed to determine the neutrino mass ordering through atmospheric neutrino oscillation studies. As the detector configurations grow, the increasing volume of recorded data demands sophisticated processing and management strategies to ensure accuracy of physics results. To maintain the required precision for oscillation physics and astrophysical searches, data reconstruction and Monte Carlo simulations are conducted separately for each data-taking period. Specifically, Run-by-Run approaches are adopted to account for time-dependent variations of deep-sea conditions. This presentation provides an overview of the KM3NeT data processing workflow, focusing on how the transition from raw data to physically reliable datasets is handled. The presentation will address the challenges of managing large-scale Monte Carlo productions that reflect real-time environmental variations, with particular emphasis on atmospheric temperature changes and their impact on Data/Monte Carlo simulation agreement. The current status of computing models and data handling will also be highlighted.