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Soft Classification of Diffractive Interactions at the LHC / Kuusela, Mikael ; Malmi, Eric ; Orava, Risto ; Vatanen, Tommi
Multivariate machine learning techniques provide an alternative to the rapidity gap method for event-by-event identification and classification of diffraction in hadron-hadron collisions. Traditionally, such methods assign each event exclusively to a single class producing classification errors in overlap regions of data space. [...]
arXiv:1101.0090.- 2011 - 4 p. - Published in : AIP Conf. Proc. 1350 (2011) 111-114 External link: Preprint
In : International Workshop on Diffraction in High-Energy Physics, Otranto, Lecce, Italy, 10 - 15 Sep 2010, pp.111-114

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Multivariate Techniques for Identifying Diffractive Interactions at the LHC / Kuusela, Mikael (Helsinki Inst. of Phys. ; Helsinki U. of Tech.) ; Lamsa, Jerry W. (Helsinki Inst. of Phys. ; Helsinki U. ; Iowa State U.) ; Malmi, Eric (Helsinki Inst. of Phys. ; Helsinki U. of Tech.) ; Mehtala, Petteri (Helsinki Inst. of Phys. ; Helsinki U.) ; Orava, Risto (Helsinki Inst. of Phys. ; Helsinki U.)
Close to one half of the LHC events are expected to be due to elastic or inelastic diffractive scattering. Still, predictions based on extrapolations of experimental data at lower energies differ by large factors in estimating the relative rate of diffractive event categories at the LHC energies. [...]
arXiv:0909.3039.- 2009 - 32 p. - Published in : Int. J. Mod. Phys. A 25 (2010) 1615-1647 Fulltext: PDF; External link: Preprint

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