A NEW ROBUST FITTING ALGORITHM FOR VERTEX RECONSTRUCTION IN THE CERESEXPERIMENT

In this paper we report on the application of a robust approach based on a reweighted least squares method for the vertex reconstruction of the CERES/NA45 experiment at the CERN SPS for the case of 160 GeV/u Pb +Au collisions and compare its performance with the presently used alg orithm based on the minimization of summed Gaussian weights. In the CE RES/NA45 experiment a doublet of cylindrical silicon drift detectors ( SDD) is used for vertex reconstruction and tracking. The vertex recons truction algorithm has to cope with a background-contaminated environm ent. Furthermore, in the case of ultrarelativistic heavy-ion collision s where high event multiplicities occur (dn(ch)/d eta similar or equal to 500), the probability of confusing hits from close or intersecting tracks is high. The algorithm needs to provide the precise vertex loc ation even at high occupancies, at a reasonable speed. Our findings ar e that the robust iterative procedure presented here is about an order of magnitude faster than approaches using standard minimization packa ges, at a comparable or slightly better accuracy.