From capturing collisions to avoiding them

With about one billion proton–proton collisions per second at the Large Hadron Collider (LHC), the LHC experiments need to sift quickly through the wealth of data to choose which collisions to analyse. To cope with an even higher number of collisions per second in the future, scientists are investigating computing methods such as machine-learning techniques. A new collaboration is now looking at how these techniques deployed on chips known as field-programmable gate arrays (FPGAs) could apply to autonomous driving, so that the fast decision-making used for particle collisions could help prevent collisions on the road. FPGAs have been used at CERN for many years and for many applications. Unlike the central processing unit of a laptop, these chips follow simple instructions and process many parallel tasks at once.