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arXiv 1008.4355hep-ph
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用有效场论研究阈强子事件

Threshold Hadronic Event Shapes with Effective Field Theory

Randall Kelley, Matthew D. Schwartz

摘要:

强子事件形状,即强子对撞机上的事件形状,可以提供一个测试标准和非标准理论模型的好方法。然而,它们比e+e-对撞机上的事件形状复杂得多,涉及多个硬方向,多个通道和多个颜色结构。本文利用软共线有效理论(SCET),通过在双射极限附近展开,研究了强子事例的形状。定义了一个简单的事件形状--临界推力。这个观测值是全局的,没有自由参数,这使得它非常适合于澄清如何在SCET中重新描述强子事件形状。阈值推力在SCET中以次领先固定阶(NLO)计算,并以次领先对数精度(NNLL)表示。软函数的尺度依赖部分与一般观测结果一致,并且因子分解公式明确地表明是重整化群对1-圈不变的.虽然阈值推力本身并不被认为是现象学上有趣的,但它可以被修改为相关的可观察值,从而允许计算喷流pT分布并以NNLL+NLO精度进行图示。与其他过程一样,由于动力学阈值的增强,即使对于中等的喷流动量,人们也期望再确认是重要的。阈值增强和强子事件形状的非全局日志的一般性讨论也包括在内。

英文摘要:

Hadronic event shapes, that is, event shapes at hadron colliders, could provide a great way to test both standard and non-standard theoretical models. However, they are significantly more complicated than event shapes at e+e- colliders, involving multiple hard directions, multiple channels and multiple color structures. In this paper, hadronic event shapes are examined with Soft-Collinear Effective Theory (SCET) by expanding around the dijet limit. A simple event shape, threshold thrust, is defined. This observable is global and has no free parameters, making it ideal for clarifying how resummation of hadronic event shapes can be done in SCET. Threshold thrust is calculated at next-to-leading fixed order (NLO) in SCET and resummed to next-to-next-to-leading logarithmic accuracy (NNLL). The scale-dependent parts of the soft function are shown to agree with what is expected from general observations, and the factorization formula is explicitly shown to be renormalization group invariant to 1-loop. Although threshold thrust is not itself expected to be phenomenologically interesting, it can be modified into a related observable which allows the jet pT distribution to be calculated and resummed to NNLL+NLO accuracy. As in other processes, one expects resummation to be important even for moderate jet momenta due to dynamical threshold enhancement. A general discussion of threshold enhancement and non-global logs in hadronic event shapes is also included.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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