ENHANCING THE TOP-QUARK SIGNAL AT FERMILAB-TEVATRON USING NEURAL NETS

被引:2
作者
AMETLLER, LI
GARRIDO, LI
TALAVERA, P
机构
[1] UNIV BARCELONA, DEPT ESTRUCTURA & CONSTITUENTS MAT, E-08028 BARCELONA, SPAIN
[2] UNIV AUTONOMA BARCELONA, INST FIS ALTES ENERGIES, E-08193 BARCELONA, SPAIN
关键词
D O I
10.1103/PhysRevD.50.R5473
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
We show, in agreement with previous studies, that neural nets can be useful for top-quark analysis at the Fermilab Tevatron. The main features of t ($) over bar t and background events in a mixed sample are projected on a single output, which controls the efficiency, purity, and statistical significance of the t ($) over bar t signal. We consider a feedforward multilayer neural net for the CDF reported top-quark mass, using six kinematical variables as inputs. Our main results are based on the exhaustive comparison of the neural net performances with those obtainable from the standard experimental analysis, by imposing different sets of linear cuts over the same variables, showing how the neural net approach improves the standard analysis results.
引用
收藏
页码:R5473 / R5477
页数:5
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