Abstract

The CMS experiment uses a two-level triggering system consisting of the Level-1, instrumented by custom-design hardware boards, and the High Level Trigger, a streamlined version of the offline reconstruction software running on a computer farm. The upgrade of the collider to the “High-Luminosity LHC”, which will deliver a luminosity of 5−7.5 × 1034 cm−2s−1, corresponding to 140–200 pileup events, also necessitates a complete upgrade of the trigger system to make optimal use of the data. An important difference from the present system will be the fact that after the upgrade, information from the silicon strip tracker will be available already for the Level-1 Trigger. This will allow CMS to use so-called “particle flow” objects, i.e. signals seen not only in one subdetector but put together from all available subdetectors, resulting in much sharper efficiency turn-on curves for trigger objects. Also, trigger rates will rise both at Level-1 (from 100 kHz to 750 kHz) and at the High-Level Trigger (from 1 kHz to 7.5 kHz). At the same time, more sophisticated algorithms will be available at Level-1. To make this possible, the latency—the processing time available for arriving at the Level-1 trigger decision—will increase significantly. Machine-learning techniques such as Boosted Decision Trees have already started to be implemented in the trigger electronics and will occupy a more important place in the future. The use of High-Level Synthesis (HLS) tools will allow physicists to formulate trigger requirements in a language closer to that of data analysis. To avoid missing unexpected signatures from New Physics, studies are underway to employ anomaly detection using autoencoders.

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