Speaker
Description
LHC experiments rely on highly complex detector geometries that support multiple phases of the experiment's lifecycle, including engineering design, manufacturing, installation, physics analyses, and outreach. Although the underlying detector components are the same across these tasks, the requirements differ significantly. For example, engineering integration typically needs only the external boundary surfaces, without detailed material information, whereas physics analyses require full internal descriptions along with accurate representations of overall mass, volumes, and materials. Consequently, the methods, techniques, and tools used to create these geometries also differ, resulting in a wide variety of geometry descriptions. Moreover, because LHC experiments involve enormous international collaborations, different partners often adopt different approaches and tools. This diversity has led to the proliferation of numerous heterogeneous geometry descriptions, so-called silo geometries. These siloed geometries introduce several challenges: 1. Complex and error-prone geometry migration between platforms 2. Difficulty implementing upgrades 3. Data-versus-Monte-Carlo discrepancies in physics analyses 4. Reduced clarity and interpretability in outreach visualizations This study is based on the ATLAS experiment. It examines the impact of isolated geometry descriptions on engineering design, simulation accuracy, data synchronization, version control, and cross-platform interoperability.