arXiv 1607.080102016-07hep-ph

强子-强子碰撞中双喷流截面的因式分解

Factorization of the dijet cross section in hadron-hadron collisions

Junegone Chay, Taewook Ha, Taehyun Kwon

备注：: 31 pages, 5 figures. Change of one author. Major rewriting on the radiative corrections including rapidity divergence. The renormalization group evolution of the factorized parts added

摘要：

利用锥型喷流算法，给出了强子-强子碰撞中双喷流截面的因式分解定理。我们还将束流否决权应用于由初始辐射组成的束流射流。软共线有效理论被用来透明地看到分解结构时，有四个不同的光锥方向参与。有各种类型的发散，如紫外和红外发散。而当对相空间进行划分以探测共线和软相时，又出现了一个称为快度发散的发散。这些发散被整理出来，我们将表明，所有的红外和快度发散取消，只有紫外发散仍然存在。证明因子分解的合理性是关键的一步。在众多的部分子过程中，我们以$q\overline{q} \rightarrow gg$作为一个具体的例子来考虑双射截面。硬函数和软函数具有非平凡的颜色结构，而喷流和束流函数在算子基上是对角的。软反常维数对喷流算法和束否决的依赖在算子空间中是对角的，并被喷流和束函数的依赖所抵消。我们还计算了因式分解分量的反常维数，并通过求解重整化群方程，将大的维数恢复到仅次于领先的对数精度。

英文摘要：

The factorization theorem for the dijet cross section is presented in hadron-hadron collisions with a cone-type jet algorithm. We also apply the beam veto to the beam jets consisting of the initial radiation. The soft-collinear effective theory is employed to see the factorization structure transparently when there are four distinct lightcone directions involved. There are various types of divergences such as the ultraviolet and infrared divergences. And when the phase space is divided to probe the collinear and the soft parts, there appears an additional divergence called rapidity divergence. These divergences are sorted out and we will show that all the infrared and rapidity divergences cancel, and only the ultraviolet divergence remains. It is a vital step to justify the factorization. Among many partonic processes, we take $q\overline{q} \rightarrow gg$ as a specific example to consider the dijet cross section. The hard and the soft functions have nontrivial color structure, while the jet and the beam functions are diagonal in operator basis. The dependence of the soft anomalous dimension on the jet algorithm and the beam veto is diagonal in operator space, and is cancelled by that of the jet and beam functions. We also compute the anomalous dimensions of the factorized components, and resum the large logarithms to next-to-leading logarithmic accuracy by solving the renormalization group equation.

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摘要：

英文摘要：

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