Study of clustering methods to improve primary vertex finding for collider detectors

Primary vertex finding for collider experiments is studied with the aim to detect all primary interactions. The efficiency and precision of finding interaction vertices can be improved by advanced clustering and classification methods, such as agglomerative clustering with fast pairwise nearest neighbor search, followed by Gaussian mixture model or k-means clustering. The results have been obtained with simplified simulation and Gaussian smearing, but insights on sensitivity to backgrounds are also given.