Drift chamber tracking with neural networks

Abstract

Drift chamber tracking with a commercial analog VLSI neural network chip is discussed. Voltages proportional to the drift time in a four-layer drift chamber are presented to the Intel Electrically Trained Analog Neural Network chip. The network is trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs are recorded and compared offline to conventional track fits. Two types of network architectures are studied. Application of neural network tracking to high energy physics detector triggers is discussed. >