Knowhow and experience derived from early adoption of neural network techniques by particle physics community.

CERN's Know-How:

  • Particle physicists were among the first to use machine learning (ML) in software for analysis & simulations
  • First AI HENP seminar in 1990
  • Already in 2010, the CMS and LHCb experiments successfully introduced machine learning algorithms to its trigger system
  • Higgs boson discovery earlier than expected (2012), also with help of ML

Facts & Figures:

  • <10 μsec: ML applied for extremely fast decision making in CERN detector trigger systems
  • AUC> 90%: High true positive / low false positive rates achieved even in sparse images with little datapoints
  • >1000 times faster: Convolutional neural networks have dramatically decreased computing time in physics (vs traditional computing)
  • ~100% efficient: Highly reliable trace reconstruction algorithms using tailored neural network techniques, even with multiple tracks in one sensor

Value Proposition:

Read more about Machine Learning and Deep Learning here

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