Jet substructure has emerged to play a central role at the Large Hadron
Collider, where it has provided numerous innovative ways to search for new
physics and to probe the Standard Model, particularly in extreme regions of
phase space. In this article we focus on a review of the development and use of
state-of-the-art jet substructure techniques by the ATLAS and CMS experiments.

本综述回顾了 ATLAS 和 CMS 实验使用最先进的喷注子结构技术的发展历程，为在大型强子对撞机中寻找新物理、探索标准模型特别是相空间极端区域提供了许多创新方法。

大型强子对撞机上的喷注次级结构：实验述评

Jet Substructure at the Large Hadron Collider: Experimental Review

Many measurements and searches for physics beyond the standard model at the
LHC rely on the efficient identification of heavy-flavour jets, i.e. jets
originating from bottom or charm quarks. In this paper, the discriminating
variables and the algorithms used for heavy-flavour jet identification during
the first years of operation of the CMS experiment in proton-proton collisions
at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet
identification algorithms have been improved compared to those used previously
at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in
the range expected in simulated $\mathrm{t}\overline{\mathrm{t}}$ events, these
new developments result in an efficiency of 68% for the correct identification
of a b jet for a probability of 1% of misidentifying a light-flavour jet. The
improvement in relative efficiency at this misidentification probability is
about 15%, compared to previous CMS algorithms. In addition, for the first time
algorithms have been developed to identify jets containing two b hadrons in
Lorentz-boosted event topologies, as well as to tag c jets. The large data
sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed
the development of new methods to measure the efficiency and misidentification
probability of heavy-flavour jet identification algorithms. The heavy-flavour
jet identification efficiency is measured with a precision of a few per cent at
moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the
highest jet transverse momenta (between 500 and 1000 GeV).

本文介绍了 CMS 实验在质心能量为 13TeV 的质子 - 质子碰撞中，用于识别重味喷注的鉴别变量和算法，并开发出新的算法以提高重味喷注鉴别的效率和精确度，同时还实现了对包含两个 $b$ 强子的喷注和 $c$ 喷注的鉴别，目前以 15% 左右的提高在 1% 误识率下正确识别 $b$ 喷注的效率，同时在适中的喷注横向动量下准确性高可达几个百分点，而在高喷注横向动量下也可达到约 5%。

CMS 探测器在 13 TeV pp 碰撞中重味道喷注的辨识

Identification of heavy-flavour jets with the CMS detector in pp  collisions at 13 TeV

The CMS apparatus was identified, a few years before the start of the LHC
operation at CERN, to feature properties well suited to particle-flow (PF)
reconstruction: a highly-segmented tracker, a fine-grained electromagnetic
calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an
excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned
to the CMS detector was therefore developed and has been consistently used in
physics analyses for the first time at a hadron collider. For each collision,
the comprehensive list of final-state particles identified and reconstructed by
the algorithm provides a global event description that leads to unprecedented
CMS performance for jet and hadronic tau decay reconstruction, missing
transverse momentum determination, and electron and muon identification. This
approach also allows particles from pileup interactions to be identified and
enables efficient pileup mitigation methods. The data collected by CMS at a
centre-of-mass energy of 8 TeV show excellent agreement with the simulation and
confirm the superior PF performance at least up to an average of 20 pileup
interactions.

该论文介绍了针对 CMS 探测器开发的全面的局域流重建算法，该算法已成功应用于首个强子对撞机物理分析，并且在堆积衰减、能量分辨率等方面具有优越的性能表现。

CMS 探测器中的粒子流重建和全局事件描述

Particle-flow reconstruction and global event description with the CMS  detector

At the Large Hadron Collider, the identification of jets originating from b
quarks is important for searches for new physics and for measurements of
standard model processes. A variety of algorithms has been developed by CMS to
select b-quark jets based on variables such as the impact parameters of
charged-particle tracks, the properties of reconstructed decay vertices, and
the presence or absence of a lepton, or combinations thereof. The performance
of these algorithms has been measured using data from proton-proton collisions
at the LHC and compared with expectations based on simulation. The data used in
this study were recorded in 2011 at sqrt(s) = 7 TeV for a total integrated
luminosity of 5.0 inverse femtobarns. The efficiency for tagging b-quark jets
has been measured in events from multijet and t-quark pair production. CMS has
achieved a b-jet tagging efficiency of 85% for a light-parton misidentification
probability of 10% in multijet events. For analyses requiring higher purity, a
misidentification probability of only 1.5% has been achieved, for a 70% b-jet
tagging efficiency.

本文讨论了 CMS 在大型强子对撞机上使用多种算法通过诸如荷电粒子轨迹的冲击参数、重构衰变顶点的属性和存在或不存在只有电子，或两者结合的变量来选择起源于 b 夸克的喷注。