Boosted Decision Trees in the CMS Level-1 Endcap Muon Trigger

The first implementation of Boosted Decision Trees (BDTs) inside a Level-1 trigger system at the LHC is presented. The Endcap Muon Track Finder (EMTF) at CMS uses BDTs to infer the momentum of muons in the forward region of the detector, based on 25 different variables. Combinations of these variables are evaluated offline using regression BDTs, whose output is stored in 1.2 GB look-up tables (LUTs) in the EMTF hardware. These BDTs take advantage of complex correlations between variables, the inhomogeneous magnetic field, and non-linear effects such as inelastic scattering to distinguish high-momentum signal muons from the overwhelming low-momentum background. The LUTs are used to turn the complex BDT evaluation into a simple look-up operation in fixed low latency. The new momentum assignment algorithm has reduced the trigger rate by a factor of 3 at the 25 GeV trigger threshold with respect to the legacy system, with further improvements foreseen in the coming year.