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

Research output: Article

8 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)526-533
Number of pages8
JournalNuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Volume621
Issue number1-3
DOIs
Publication statusPublished - máj. 13 2010

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Instrumentation

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