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Search for standard model Higgs boson production in association with a W boson using a neural network discriminant at CDF

机译:使用CDF的神经网络判别式搜索与 W 玻色子相关的标准模型希格斯玻色子生产

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摘要

We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions (pp→W±H→ℓνbb) at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9  fb−1. We select events consistent with a signature of a single charged lepton (e±/μ±), missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to 150  GeV/c2, respectively.
机译:我们提出在质量能中心1.96 TeV的质子-反质子碰撞(pp→W±H→ℓνbb)中与W玻色子关联的标准希格斯玻色子生产的搜索。搜索使用CDF II检测器收集的数据,该数据对应于大约1.9 fb-1的综合亮度。我们选择与单个带电轻子(e±/μ±)的特征,缺少横向能量和两个射流一致的事件。通过二次顶点标记方法,喷射概率标记方法和神经网络过滤器来识别与底部夸克相对应的喷射。与以前的分析相比,我们在人工神经网络中使用运动学信息来改善信号和背景之间的区别。观察到的事件数量和神经网络输出分布与标准模型背景期望值一致,并且我们在生产横截面乘以分支分数的95%置信水平上限,范围是标准的1.2到1.1 pb或7.5到102倍希格斯玻色子质量的模型期望分别为110至150VGeV / c2。

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