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arXiv 2007.12187hep-ph
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射流能降

Jet energy drop

Pedro Cal, Kyle Lee, Felix Ringer, Wouter J. Waalewijn

摘要:

我们研究了射流能量的下降,这是疏导和未疏导的射流能量或横向动量之间的相对差异。它是表征梳理对高能碰撞产生的喷流影响的基本量之一。我们考虑三种不同的梳理算法i)软丢弃,ii)迭代软丢弃,和iii)修剪。我们进行了重新计算的射流能量下降,射流半径以及相关的疏导参数在次领先的对数(NLL $'$)的精度大的平方。此外,我们考虑到非全局和集群的算法,并确定下一个领先的顺序校正。对于软降,我们进行联合remmation的射流能量下降和疏导射流半径,这是必要的,以实现正确的所有阶结构的横截面,特别是对于Sudakov安全的情况下,软降与$β=0$。我们提出了数值计算结果的LHC能量和比较Pythia模拟以及CMS数据。我们的因式分解框架预测的发病非微扰效应的射流能量分布,符合我们在皮提亚发现。喷流能降观测站脱颖而出,因为他们只探测软辐射,使他们成为理想的候选人,调整部分子簇射蒙特卡罗事件发生器和探测介质效应的重离子碰撞。

英文摘要:

We study the jet energy drop, which is the relative difference between the groomed and ungroomed jet energy or transverse momentum. It is one of the fundamental quantities that characterizes the impact of grooming on jets produced in high energy collisions. We consider three different grooming algorithms i) soft drop, ii) iterated soft drop, and iii) trimming. We carry out the resummation of large logarithms of the jet energy drop, the jet radius as well as relevant grooming parameters at next-to-leading logarithmic (NLL$'$) accuracy. In addition, we account for non-global and clustering logarithms, and determine the next-to-leading order corrections. For soft drop we perform a joint resummation of the jet energy drop and the groomed jet radius, which is necessary to achieve the correct all-order structure of the cross section, in particular for the Sudakov-safe case of soft drop with $β=0$. We present numerical results for LHC energies and compare to Pythia simulations as well as CMS data. Our factorization framework predicts the onset of nonperturbative effects in the jet energy distribution, in line with what we find in Pythia. The jet energy drop observables stand out because they only probe soft radiation, making them ideal candidates for the tuning of parton shower Monte Carlo event generators and for probing medium effects in heavy-ion collisions.

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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