Presenter: Brianna Stamas
Faculty Mentor: Stephanie Majewski, Geraldine Richmond
Presentation Type: Oral
Primary Research Area: Science
Major: Physics
Funding Source: Presidential Undergraduate Research Scholars Program, UO Undergraduate Research Opportunity Program, $5,000
A basic question about our universe remains unanswered: what is everything fundamentally made of? Everything we know of only makes up 4% of the universe; a significant fraction of the remaining 96% is made of an unknown fundamental particle referred to as dark matter. In an attempt to identify the dark particle, the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland is recreating the conditions of the Big Bang. The ATLAS Experiment is one of two general purpose detectors at the LHC. In anticipation of discovering new physics, the ATLAS detector will undergo numerous hardware upgrades in the coming years, one of which will be an improvement to the existing trigger system which is a 3-level hardware and software based system. This study focuses on the upgrades to the level-1 trigger. The LHC collides bunches of protons every 25 ns, which amounts to a lot of data in an extremely short period of time. Specifically, the missing transverse energy (ETmiss) trigger is crucial in being able to detect a previously undetectable particle. Therefore, we propose implementing a topological clustering inspired algorithm on the level-1 ETmiss trigger. The algorithm will be employed on the gFEX (global feature extractor) with 0.2×0.2 eta-phi granularity to be installed in 2019. This study analyzes the performance the algorithm for future implementation.