论文标题
重粒子射流识别
Heavy Particle Jet Identification with Zest
论文作者
论文摘要
我们引入了一个新的JET可观察的{\ em Zest}，该{\ em zest}在独家构造的喷气机上定义，并研究了其歧视喷气机的潜力，源自标准模型重颗粒，例如$ w，〜z $ bosons和Gluon启动喷气机的顶级夸克。热情表现出诸如Partons之间的增强不变性，针对全球色交换的稳定性以及射流中的一些软颗粒的包含或排除。我们还观察到，对于Gluon喷气机，热皮分布主要对射流质量不敏感。这些特性使热皮成为否决对山口处的Gluon喷气机的合适候选者。当与其他与之不相关的子结构结合使用时，Zest可以进一步改善Gluon Jet否决。我们概括了皮并表明，在一个极限中，它是粒子多样性的代名词，在另一个限制中，它仅投射领先的粒子。对广义热的参数进行优化进一步提高了可观察到的歧视能力。我们发现，对于顶级夸克引起的喷气式飞机，广义热水提供的歧视与一类基于机器学习的顶级标签者的歧视是密切的。我们建议研究其他非线性红外线和线性不安全可观察物可能有助于揭示基于机器学习的可观察物的隐藏物理。
We introduce a new jet observable {\em zest} defined on exclusively constructed jets and study its potential to discriminate jets originated from Standard Model heavy particles like $W,~Z$ bosons and top quark from gluon initiated jets. Zest exhibits properties such as boost invariance, stability against global color exchange among partons, and inclusion or exclusion of a few soft particles in the jet. We also observe that for gluon jets, zest distribution is mostly insensitive to the jet mass. These properties make zest a suitable candidate for vetoing gluon jets at the colliders. Zest when used in conjunction with other substructure observables that are uncorrelated to it can further improve gluon jet veto. We generalize zest and show that in one limit it is synonymous to particle multiplicity and in the other limit, it projects only the leading particle. Optimization on the parameter of generalized zest further improves the discrimination ability of the observable. We find that for the top quark-initiated jets, the discrimination provided by generalized zest is in close comparison with a class of machine learning-based top taggers. We propose that studying other non-linear infrared and collinear unsafe observables may help in unveiling the hidden physics of machine learning-based observables.
