Detection of clustering instabilities for sequential recombination algorithms

C. S. Cowden; I. Volobouev

doi:10.1088/1742-6596/404/1/012054

Detection of clustering instabilities for sequential recombination algorithms

C. S. Cowden, I. Volobouev

Physics

Research output: Contribution to journal › Conference article › peer-review

Abstract

We explore clustering stability of sequential recombination jet reconstruction algorithms. Events are reconstructed many times, using random variations of kinematic properties of the jet fragmentation process. Sensitivity of different algorithms to initial conditions are quantified by introducing probabilistic assignment of initial particles to jets (fuzzy clustering). A criterion detecting unstable configurations (bifurcation points) is proposed, based on the overall fuzziness of the event.

Original language	English
Article number	012054
Journal	Journal of Physics: Conference Series
Volume	404
Issue number	1
DOIs	https://doi.org/10.1088/1742-6596/404/1/012054
State	Published - 2012
Event	15th International Conference on Calorimetry in High Energy Physics, CALOR 2012 - Santa Fe, NM, United States Duration: Jun 4 2012 → Jun 8 2012

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10.1088/1742-6596/404/1/012054

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title = "Detection of clustering instabilities for sequential recombination algorithms",

abstract = "We explore clustering stability of sequential recombination jet reconstruction algorithms. Events are reconstructed many times, using random variations of kinematic properties of the jet fragmentation process. Sensitivity of different algorithms to initial conditions are quantified by introducing probabilistic assignment of initial particles to jets (fuzzy clustering). A criterion detecting unstable configurations (bifurcation points) is proposed, based on the overall fuzziness of the event.",

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AB - We explore clustering stability of sequential recombination jet reconstruction algorithms. Events are reconstructed many times, using random variations of kinematic properties of the jet fragmentation process. Sensitivity of different algorithms to initial conditions are quantified by introducing probabilistic assignment of initial particles to jets (fuzzy clustering). A criterion detecting unstable configurations (bifurcation points) is proposed, based on the overall fuzziness of the event.

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DO - 10.1088/1742-6596/404/1/012054

M3 - Conference article

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JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

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Y2 - 4 June 2012 through 8 June 2012

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