SNAGGING THE TOP QUARK WITH A NEURAL NET

被引：5

作者：

BAER, H

KARATAS, DD

GIUDICE, GF

机构：

[1] UNIV TEXAS,CTR PARTICLE PHYS,AUSTIN,TX 78712

[2] UNIV TEXAS,DEPT PHYS,THEORY GRP,AUSTIN,TX 78712

来源：

PHYSICAL REVIEW D | 1992年 / 46卷 / 11期

关键词：

D O I：

10.1103/PhysRevD.46.4901

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

The search for the top quark at ppBAR colliders in the one-lepton-plus-jets channel is plagued by an irremovable background from W-boson-plus-multijet production. In this paper, we show how the top-quark signal can be distinguished from background in the distribution of neural network output. By making a cut on the network output, we maximize the ratio of signal to background in a final event sample, and compare our results with those obtained by making kinematical cuts on the data sample. We also demonstrate the robustness of the neural network method by training the neural network on signal events of one top mass and testing upon another.

引用

页码：4901 / 4906

页数：6

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