CERN

DARKJETS

Coordinating university: Lund University, www.lu.se

© CERN

© CERN

Project description

For experiments at the Large Hadron Collider (LHC) at CERN, proton-proton collisions occur up to 30 million times per second. One cannot record all information related to each of these collisions, since the size of each “event” can surpass 1 MB. Experiment therefore select only a subset of these collision events, record them to storage and then analyze them afterwards.

Novel techniques are needed in order to make the most of data that is not selected and would otherwise be discarded. The DARKJETS project delivers such a technique for the ATLAS experiment, called Trigger-object Level Analysis (TLA). In this technique, higher-level insight is obtained from a fast data analysis done in milliseconds, so that only a small subset of the information can be stored for each event. This greatly reduces the event size and allows for a much larger dataset to be recorded for e.g. searches for new physics phenomena. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innova- tion programme (grant agreement No GA679305)”

Team

Lund University, Faculty of Sciences:

  • Caterina Doglioni, Associate Senior Lecturer, specialist in data selection and data analysis, particle physics

  • William Kalderon, Postdoc, specialist in data selection and data analysis, particle physics

  • Oxana Smirnova, Associate Senior Lecture, specialist in scientific computing and data processing

  • Florido Paganelli, Researcher, computer scientist, system expert

  • Eva Hansen, Eric Corrigan, PhD students

Core deliverables

Novel technique for the ATLAS detector to record

Commissioning of FPGA-based board for event selection in the upcoming LHC Run

Scientific and technical peer-reviewed publications

Year
2016–2021

Total budget
EUR 1,27 million

Collaboration

  • Lund University

  • Ohio State University

  • Heidelberg University

  • University of Oregon

  • University of Geneva

  • CERN

Hyperlink
http://www.hep.lu.se/staff/doglioni/darkjets.html

Procurement code
Information technology