CMS High Level Trigger

CMS High Level Trigger
Name	CMS High Level Trigger
Classification	Data acquisition and real-time event selection
Inventor	CERN
Manufacturer	European Organization for Nuclear Research
Introdate	2008

CMS High Level Trigger

The CMS High Level Trigger is the real-time software selection system used in the Compact Muon Solenoid experiment at CERN to reduce raw event rates for storage and offline analysis. It operates downstream of the Level-1 trigger stage and interfaces with the CMS Detector Control System, Worldwide LHC Computing Grid, and detector subsystems to enable physics programs pursued by collaborations such as ATLAS Collaboration, LHCb Collaboration, and ALICE Collaboration. The system has been developed and commissioned in coordination with projects like the Large Hadron Collider accelerator, HL-LHC upgrade planning, and global computing initiatives.

Overview and Purpose

The primary purpose of the CMS High Level Trigger is to perform rapid reconstruction and selection of collision events produced by the Large Hadron Collider to reduce input rates from the Level-1 Trigger to a sustainable data flow for the Computing Grid and offline experiments like CMS Physics Analysis. It filters physics signatures relevant to searches for phenomena such as the Higgs boson, supersymmetry, dark matter, and precision measurements of processes related to the Standard Model including top quark and electroweak interaction studies. The design balances constraints imposed by hardware such as the CMS silicon tracker, ECAL, HCAL, and muon system while integrating with software frameworks derived from CMSSW and aligning with commissioning efforts for the High Luminosity Large Hadron Collider.

Architecture and Components

The architecture comprises a farm of multi-core compute nodes known as the HLT farm, connected through a high-bandwidth network to the Event Filter Farm and the Data Acquisition System. Core components include the HLT supervisor software, event building modules, online databases, and the trigger menu configuration managed through the Run Control and Condition Database infrastructure. Key interfaces connect to subdetector readout electronics such as the Pixel detector FEDs, Strip tracker readout, Electromagnetic Calorimeter front-end, and Hadron Calorimeter digitizers. Supporting services rely on projects and institutions like the Worldwide LHC Computing Grid, CERN openlab, Fermi National Accelerator Laboratory, DESY, INFN, KIT, and computing centers in national laboratories and universities.

Trigger Algorithms and Event Selection

Algorithms implemented in the HLT stem from reconstruction modules originally developed in CMSSW and adapted for low-latency execution. They include fast tracking algorithms for the silicon tracker, clustering algorithms for the ECAL and HCAL, muon reconstruction linking to the Drift Tubes, Cathode Strip Chambers, and Resistive Plate Chambers, and particle-flow techniques combining inputs from multiple subsystems. Selection paths target final states such as isolated leptons (electrons, muons), photons, jets, and heavy-flavor signatures including b-tagging and displaced vertices relevant to B physics and exotic searches. The trigger menu is optimized using datasets and simulations produced with tools like GEANT4, PYTHIA, MADGRAPH, and reconstruction tuning with inputs from the Particle Data Group.

Performance and Commissioning

Commissioning of the HLT involved staged integration tests, cosmic-ray runs with the Magnet Test and Cosmic Challenge, and collision data during early LHC running periods. Performance metrics include algorithm latency, selection efficiency for benchmark processes like Z boson and W boson production, output rate stability, and CPU utilization across the HLT farm. Validation used benchmark comparisons to offline reconstruction from analyses by groups such as the CMS Collaboration, coordinated reviews with the LHC Machine Committee, and studies with detector alignment and calibration produced by teams at institutions including CERN, Brookhaven National Laboratory, SLAC National Accelerator Laboratory, and KEK. Monitoring of physics performance leverages luminosity information from LHC beam instrumentation and pileup conditions estimated with models from Tune Z2 and other generator tunes.

Operation and Data Quality Monitoring

Operation is performed by shift personnel from the CMS Collaboration using the Run Control and Data Quality Monitoring frameworks to ensure integrity of selected datasets. Online data quality monitoring inspects physics histograms, trigger rates, and subdetector status to detect issues with subsystems like the pixel detector, muon chambers, calorimeters, and readout electronics. Alarms and shifters coordinate with groups such as the Detector Safety System and operations teams at CERN and regional centers including Tier-0 and Tier-1 facilities. Data streams created by the HLT are cataloged for prompt reconstruction at Tier-0 and distributed through the Worldwide LHC Computing Grid for collaboration-wide analysis.

Upgrades and Future Developments

Planned upgrades align with the High-Luminosity LHC program and include enhancements to cope with increased event pileup and luminosity. Developments encompass porting algorithms to heterogeneous architectures including GPUs, FPGAs, and many-core CPUs, integration with machine learning models trained with frameworks such as TensorFlow and PyTorch, and revisions to trigger menus to support searches for rare signals predicted by theories like Supersymmetry and Extra Dimensions. Hardware and software efforts coordinate with projects and institutions including CERN openlab, ATLAS Collaboration cross-exchange, national labs like Fermilab, DESY, and computing initiatives such as the Open Science Grid to ensure scalable, maintainable operation into the HL-LHC era.

Category:Compact Muon Solenoid