Knowhow and experience derived from early adoption of neural network techniques by particle physics community.
- 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
Read more about Machine Learning and Deep Learning here.