MULTIVARIATE TECHNIQUES FOR IDENTIFYING DIFFRACTIVE INTERACTIONS AT THE LHC
نویسندگان
چکیده
منابع مشابه
Soft Classification of Diffractive Interactions at the LHC
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. As an alternative to this so called hard classification approach, w...
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We present a model of high energy soft pp interactions that has multi sand t-channel components, which has been tuned to describe all the available data. The t-channel components allow matching of the soft to the hard (QCD) Pomeron. Absorptive effects are found to be large, and, for example, suppress the prediction of the total pp cross section to about 90 mb at the LHC. We use the model to cal...
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ژورنال
عنوان ژورنال: International Journal of Modern Physics A
سال: 2010
ISSN: 0217-751X,1793-656X
DOI: 10.1142/s0217751x10047920