Machine learning to reveal more about LHC particle collisions
The CMS Collaboration demonstrates that machine learning can outperform traditional methods in the full reconstruction of particle collisions at the LHC
Following the approval of a CERN-wide artificial intelligence (AI) strategy, these general principles are designed to promote the responsible and ethical use, development and deployment of AI at CERN
I first encountered artificial intelligence (AI) almost thirty years ago. Now, I’m surprised by the broad applications and ideas across CERN, which feed into and benefit from a CERN AI strategy
CERN technology showcased in the context of UN Plastic Treaty discussions
AI data analysis techniques developed at CERN were showcased during a side event of INC-5.2 – the United Nations intergovernmental negotiating committee meeting in Geneva to develop an international legally binding instrument on plastic pollution
During LHC Run 3, researchers at the experiment have deployed an innovative machine learning technique that will improve the data quality of one of the detector’s most crucial components
How can physicists make particle accelerators more efficient?
Using AI, machine learning and automation, the Efficient Particle Accelerator (EPA) project aims to boost the efficiency of CERN’s accelerators for the high luminosity era and beyond
How can AI help physicists search for new particles?
The ATLAS and CMS collaborations are using state-of-the-art machine learning techniques to search for exotic-looking collisions that could indicate new physics