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| Trigger and Data Acquisition System | |
|---|---|
| Name | Trigger and Data Acquisition System |
| Type | Experimental instrumentation |
| Fields | Particle physics, Nuclear physics, Astrophysics |
| Components | Trigger logic, Front-end electronics, Readout, Event builder, Storage |
Trigger and Data Acquisition System
A Trigger and Data Acquisition System coordinates detection, selection, digitization, transport, and storage of signals from large-scale detectors in experiments such as Large Hadron Collider, Super-Kamiokande, IceCube Neutrino Observatory and LIGO Scientific Collaboration. It integrates hardware and software from collaborations like ATLAS, CMS, ALICE, LHCb and institutions such as CERN, Fermilab, SLAC National Accelerator Laboratory, Brookhaven National Laboratory to reduce raw channel rates to manageable datasets for analysis by teams including Belle II, DUNE collaboration and Hyper-Kamiokande. Systems draw on technologies developed at Los Alamos National Laboratory, Lawrence Berkeley National Laboratory, Deutsches Elektronen-Synchrotron, Rutherford Appleton Laboratory and companies including NVIDIA, Intel, Xilinx.
A Trigger and Data Acquisition System is a layered infrastructure used in experiments at facilities like European Organization for Nuclear Research and National Aeronautics and Space Administration testbeds to select events of interest from backgrounds produced in accelerators such as Tevatron or observatories like Pierre Auger Observatory. It serves collaborations including ATLAS experiment, CMS experiment, IceCube Collaboration and NOvA by combining fast decision logic, front-end electronics, high-speed networks and persistent storage provided by centers like GridKa, NERSC and CERN Data Centre. Historical advances trace through projects like UA1 experiment, CDF II and ALEPH, influencing modern designs used by Square Kilometre Array and James Webb Space Telescope instrumentation teams.
Architectures follow modular patterns adopted by ATLAS, CMS, BaBar, ZEUS and HERA-B, partitioning into front-end, readout, event-building and storage layers. Front-end electronics interface to sensors developed by groups at Max Planck Society, Lawrence Livermore National Laboratory, KEK, and TRIUMF; they feed into trigger processors influenced by designs from IBM, Cray Research and HP. Readout uses standards like Ethernet (network), PCI Express, SFP+ optics and protocols inspired by TCP/IP, while control and configuration harness frameworks from EPICS, MIDAS and XDAQ. Integration demands coordination with computing grids such as Worldwide LHC Computing Grid and cloud providers like Google Cloud Platform and Amazon Web Services for long-term archiving.
Trigger tiers—commonly Level-1, High-Level Trigger and software triggers—derive lineage from implementations at SLC, LEP, RHIC and Tevatron. Hardware triggers exploit field-programmable gate arrays from Xilinx and Altera (Intel) and custom ASICs modeled on FASTBUS and VMEbus designs; they borrow algorithms used in ImageNet-style pattern recognition and techniques advanced by Bell Labs and MIT Lincoln Laboratory. High-level triggers run distributed reconstruction on farms using frameworks from ROOT, Gaudi and middleware from HTCondor and Kubernetes, with machine-learning modules influenced by TensorFlow, PyTorch and research from Stanford University and MIT. Trigger menus balance physics priorities set by collaborations such as ALICE Collaboration and LHCb Collaboration with detector constraints defined by groups at FNAL.
DAQ hardware includes preamplifiers, digitizers, ADCs, TDCs and mezzanine cards designed at institutions like CERN, DESY, IN2P3 and J-PARC. Modules communicate via crates standardized by VME, MicroTCA, AdvancedTCA and custom backplanes used in experiments such as NA62 and COMPASS. Signal integrity and grounding practices trace to engineering groups at General Electric and Siemens, while radiation-hard components derive from programs at ESA and NASA Jet Propulsion Laboratory. Cooling and power distribution follow standards developed for projects like ISS subsystems and ITER testbeds.
Data flows from sensors through links using optical transceivers by Finisar and Avago Technologies into switches by Cisco Systems and routers used in grids at CERN. Bandwidth planning references traffic studies from ATLAS Collaboration and storage models from European Grid Infrastructure, with tape archives managed by CERN OpenStack integrations and custodial centers including FZJ and KIT. Long-term preservation adopts formats supported by DPHEP and policies set by agencies like NSF and European Research Council. Compression and calibration pipelines implement algorithms researched at Los Alamos and Argonne National Laboratory.
Precise timing uses GPS timing systems, White Rabbit technology developed at CERN and timing protocols inspired by IEEE 1588 and systems from NIST and BIPM. Synchronization across detector subsystems references efforts by LHCb, ATLAS Tile Calorimeter and BaBar timing groups; control systems use SCADA patterns implemented with EPICS and runbooks maintained by collaborations such as CMS Collaboration. Trigger latency budgets and clock distribution networks are designed in concert with electronics teams at RAL and INFN.
Performance metrics—efficiency, purity, deadtime—are evaluated using software from ROOT, GEANT4 simulations developed at CERN and validation suites from IHEP and KEK. Calibration systems integrate laser calibration used by CMS ECAL, radioactive source systems from SNO and alignment surveys like those at ALICE ITS. Monitoring dashboards rely on visualization tools from Grafana, Kibana and telemetry systems developed at LHCb and DUNE operations centers. Quality assurance follows practices codified by ISO standards and detector groups at Fermilab.
Trigger and data acquisition designs enable discoveries at Large Hadron Collider such as the Higgs boson observation by ATLAS and CMS, neutrino oscillation measurements by Super-Kamiokande and T2K, and gravitational-wave detections by LIGO Scientific Collaboration and Virgo Collaboration. Smaller-scale implementations support projects like CUORE, GERDA, EXO, radio arrays such as LOFAR and astronomical instruments like ALMA, demonstrating cross-disciplinary impact spanning particle physics, astrophysics and nuclear science.
Category:Data acquisition