Dec 8 – 10, 2019
Monona Terrace Convention Center
America/Chicago timezone

Ideas for real-time analysis for HL-LHC using the CMS DAQ system

Dec 9, 2019, 2:20 PM
25m
Hall of Ideas H (Monona Terrace Convention Center)

Hall of Ideas H

Monona Terrace Convention Center

Madison, Wisconsin
Talk Machine Learning, Trigger and DAQ Machine Learning, Trigger and DAQ

Speaker

Remi Mommsen (Fermilab)

Description

The CMS experiment will be upgraded for operation at the High-Luminosity LHC to maintain and extend its optimal physics performance under extreme pileup conditions. Upgrades will include an entirely new tracking system, supplemented by a track trigger processor capable of providing tracks at Level-1, as well as a high-granularity calorimeter in the endcap region. New front-end and back-end electronics will also provide the level-1 trigger with high-resolution information from the barrel calorimeter and the muon systems. We will discuss the feasibility to capture and use this information to perform real-time analysis. Such a system would provide virtually unlimited statistics to study otherwise inaccessible signatures, either too common to fit in the L1 accept budget, or with requirements which are orthogonal to “mainstream” physics, such as long-lived particles. Another interesting possibility could be offered by relatively low-price large 3D XPoint memory, which could be used to increase the buffer space between the event building and the High-Level Trigger (HLT). This would open the opportunity to perform measurements using the full detector information, but which addresses physics channels which do not fit into bandwidth or storage capacity available for offline analysis.

Primary author

Remi Mommsen (Fermilab)

Co-authors

Emilio Meschi (CERN) Hannes Sakulin (CERN)

Presentation materials