Speaker
Description
Long-lived particles (LLPs) are very challenging to search for with current detectors and computing requirements, due to their very displaced vertices. This study evaluates the ability of the trigger algorithms used in the Large Hadron Collider beauty (LHCb) experiment to detect long-lived particles and attempts to adapt them to enhance the sensitivity of this experiment to undiscovered long-lived particles. One of the challenges in the track reconstruction is to deal with the large amount of combinatorics of hits. A dedicated algorithm has been developed to cope with the large data output. When fully implemented, this algorithm would greatly increase the available statistics for any long-lived particle search in the forward region, for the Standard Model of particle physics and beyond.
| Which session do you think it fits best? | Trigger Algorithms, ML / AI applications |
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