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LHC DATA CLASSIFICATION USING A NEW MORPHOLOGICAL BOUNDARY DETECTION

MOSTAFA MJAHED

Ecole Royale de l'Air, Maths and Systems Dept, 40000 Marrakech, Morocco

LPTN, Faculty of Sciences Semlalia, 40000 Marrakech, Morocco

https://doi.org/10.1142/S0217751X07039249Cited by:0 (Source: Crossref)

Abstract

A new morphological boundary detection approach is used to separate the signal from the background in the Standard Model Higgs boson search at LHC. Based on mathematical concepts, this method consists of a fast computation of probabilistic density functions of events and a smoothing using a combination of dilatation and erosion operators. In a binary search approach, the performances are improved and the results compare favourably with other multivariate analysis.

Keywords:

PACS: 11.25.Hf, 123.1K

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Vol. 22, No. 31

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LHC DATA CLASSIFICATION USING A NEW MORPHOLOGICAL BOUNDARY DETECTION

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