High energy physics applications of neural networks

Summary form only given, as follows. Neural networks implemented in silicon have been shown to solve certain pattern recognition problems on a time scale of hundreds of nanoseconds. Fast pattern recognition is at a premium in high-energy physics research at particle accelerators because (a) the ability to recognize interesting events in a high-rate background requires fast recognition of characteristic patterns, and (b) the detailed off-line pattern recognition of millions of events requires exorbitant amounts of CPU time on conventional computers. Neural networks may thus be an ideal technology for application to high-energy physics data analysis.<>