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A new jet algorithm based on the k-means clustering for the reconstruction of heavy states from jets

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Abstract

A jet algorithm based on the k-means clustering procedure is proposed which can be used for the invariant-mass reconstruction of heavy states decaying to hadronic jets. The proposed algorithm was tested by reconstructing e+e-→tt̄→6 jets and e+e-→W+W-→4 jets processes at \(\sqrt{s}=500\,\mathrm{GeV}\) using a Monte Carlo simulation. It was shown that the algorithm has a reconstruction efficiency similar to traditional jet-finding algorithms, and leads to 25% and 40% improvement of the top-quark and W mass resolution, respectively, compared to the kT (Durham) algorithm. In addition, it is expected that the peak positions measured with the new algorithm have smaller systematical uncertainty.

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Authors and Affiliations

  1. HEP division, Argonne National Laboratory, 9700 S.Cass Avenue, Argonne, IL, 60439, USA

    S. Chekanov

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  1. S. Chekanov
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Correspondence to S. Chekanov.

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Chekanov, S. A new jet algorithm based on the k-means clustering for the reconstruction of heavy states from jets. Eur. Phys. J. C 47, 611–616 (2006). https://doi.org/10.1140/epjc/s2006-02618-3

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  • DOI: https://doi.org/10.1140/epjc/s2006-02618-3

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