Abstract
Abstract
We introduce a new pattern recognition algorithm for track finding in High Energy Physics
Experiments based on an extension of the Hough Transform to multiple dimensions. A remarkable
property of this algorithm is that the execution time is simply proportional to the total number
of the hits to be processed, making it particularly attractive for high occupancy situations. The
algorithm needs to be trained using a sufficiently large set of simulated tracks. The same
track finding algorithm can be used for very different detector geometries and only the set of
simulated tracks used for training needs to be changed. The particular structure of the algorithm
also lends itself naturally to parallel hardware implementations which, combined with its
intrinsic flexibility, should provide a most powerful tool for triggering at future colliders.