Speaker
Description
In this work we present the adaptation of the popular clustering algorithm DBSCAN to reconstruct the primary vertex (PV) at the hardware trigger level in collisions at the High-Luminosity LHC. Nominally, PV reconstruction is performed by a simple histogram-based algorithm. The main challenge in PV reconstruction is that the particle tracks need to be processed in a low-latency environment
Significance
In general the DBSCAN clustering algorithm is one of the most flexibility and accurate clustering algorithms available. This work demonstrates that DBSCAN can be utilized in a low-latency environment by using FPGA acceleration. The accelerated algorithm was used to reconstruct primary vertices in collisions at the LHC, however it can be generalized to any clustering application.
Experiment context, if any | CMS |
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