Visualizing Topocluster Algorithms for the Global Trigger

Presenter(s): Sylvia Mason—Physics

Faculty Mentor(s): Stephanie Majewski

Session 5: To the Moon and Back—Relativity Matters

There is a Standard Model of particles and forces that explain the fundamental components of matter . However, this model is incomplete, seeing as we currently understand only about 5% of our universe . The Large Hadron Collider (LHC) is a particle accelerator that collides protons in the hopes of discovering new particles or forces, so that we can learn more about the other 95% of the universe . The LHC will undergo an upgrade in 2026 that will increase its luminosity, meaning there will be an increased number of collisions per second (up to 200 collisions every 25 nanoseconds) . After this upgrade, the ATLAS trigger system will need to reduce the data by a factor of 40 within 10 microseconds, so we will need to sort out the interesting events very fast . Our group is designing an algorithm for implementation in firmware in the “Global Trigger” system for ATLAS to help select these interesting events . My research focuses on creating accurate 3-D visualizations of potential algorithms that cluster energies from particle showers in the ATLAS Calorimeters, and investigation splitting criteria for these clusters . These visualizations will help us understand the details of the performance of these algorithms, which can significantly help us reject background .

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