Top Quark and Higgs Physics, and Two-Loop Calculations

顶夸克和希格斯物理，以及两环计算

• 批准号: 0555372
• 负责人: Nikolaos Kidonakis
• 金额: $ 10.09万
• 依托单位: Kennesaw State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0555372&HistoricalAwards=false
• 关键词: Top; Quark; Higgs; Physics; Two

This proposal requests support for a program of research on the phenomenological aspects of QCD applied to Tevatron and LHC collisions. The aim is to calculate cross-sections and differential distributions that are needed for the study of the top quark, and searches for the Higgs boson and supesymmetric particles. Corrections to leading order calculations in QCD can be as large as 50% or more and so, for the discovery of new particles and new physics beyond the standard model, it is essential to calculate higher order corrections in order to obtain the most precise theoretical predictions of the standard model. Deviations from these predictions can then be viewed with confidence as evidence for new physics. This type of phenomenology is an essential ingredient in the effort to maximise the physics return on the large investment by the U.S. in the LHC and its associated detectors. The broader impacts of this proposal involve the close interaction between theorists and experimentalists in the preparation of experiments and the analysis of the data obtained. There are also strong educational links since the PI will involve undergraduate students in the research, especially those areas that require large scale computing. The university has established a mentoring program for supporting students involved in research, and this proposal matches very well with that program.

这项提议要求支持一项研究项目，研究适用于Tevatron和LHC碰撞的QCD现象学方面。其目的是计算研究顶夸克所需的截面和微分分布，并搜索希格斯玻色子和超对称粒子。QCD中前级计算的修正可以高达50%或更多，因此，对于发现标准模型以外的新粒子和新物理，计算高阶修正是必不可少的，以便获得标准模型最精确的理论预测。然后，偏离这些预测就可以有把握地被视为新物理学的证据。这类现象学是使美国在大型强子对撞机及其相关探测器上的大量投资获得最大物理回报的努力的重要组成部分。这一提议的更广泛的影响涉及理论家和实验者在准备实验和分析所获得的数据方面的密切互动。由于PI将让本科生参与研究，特别是那些需要大规模计算的领域，因此也有很强的教育联系。该大学已经建立了一个指导计划，以支持参与研究的学生，这一提议与该计划非常匹配。