広島大学学位請求論文

Physics Impacts of DAQ and Triggers
at Large-Scale Hadron Collider Experiments anda New Detector Control and Monitoring Scheme
to Achieve the Impact at ALICE(大規模ハドロン衝突型加速器実験におけるトリガー・データ収集系の物理への影響とALICE 実験における新規検出器制御監視系)

2022 年

広島大学大学院理学研究科物理科学専攻
山川

皓生

目次
1. 主論文Physics Impacts of DAQ and Triggers at Large-Scale Hadron Collider Experiments and a
New Detector Control and Monitoring Scheme to Achieve the Impact at ALICE(大規模ハドロン衝突型加速器実験におけるトリガー・データ収集系の物理への影響とALICE 実験における新規検出器制御監視系)
山川 皓生

2. 公表論文
Design and implementation of detector control system for muon forward tracker at ALICE
K. Yamakawa, A. Augustinus, G. Batigne, P. Chochula, M. Oya, S. Panebianco, O. Pinazza,
K. Shigaki, R. Tieulent, and Y. Yamaguchi
Journal of Instrumentation 2020 JINST 15 T10002.
3. 参考論文(1) Υ production and nuclear modification at forward rapidity√
in Pb ‒ Pb collisions at sNN = 5.02 TeV
S. Acharya, K. Yamakawa et al.
Physics Letters B Volume 822, 10 November 2021, 136579.

(2) Production of muons from heavy-flavour hadron decays at high transverse momentum√in Pb ‒ Pb collisions at sNN = 5.02 and 2.76 TeV
S. Acharya, K. Yamakawa et al.
Physics Letters B Volume 820, 10 September 2021, 136558.

主論文

Physics impacts of DAQ and trigger systems onlarge-scale hadron collider experiments and a control andmonitoring scheme to achieve the impact
Kosei Yamakawa
3rd March, 2022

Abstract
Particle physics has advanced along with the technological improvements of experimental
equipment, especially the increase of center-of-mass energy provided by accelerators, since
the early 20th century. The large hadron collider (LHC), the world’s largest accelerator ever,has started in 2009. The center-of-mass energy, the proton beam bunch crossing rate, and
the Pb-Pb collision rate are 14 TeV, 40 MHz, and 50 kHz, respectively, in the LHC Run 3
starting from 2022. For the next decade, it is not easy to increase the center-of-mass energy
with a larger circular collider than the LHC mainly due to a ﬁnancial reason. Luminosity
upgrade is only realistic as improvements of accelerators. The LHC will be upgraded to thehigh-luminosity LHC (HL-LHC) providing a factor of ten larger luminosity than the current
value, in 2028.
The following physics missions are addressed with the LHC and the HL-LHC. First, testsof the standard model should be performed by the measurements of Higgs couplings withquarks and leptons as usual as self-coupling of Higgs. The CP violation measurements via
rare heavy ﬂavor hadron decays can also contribute to the standard model tests. In addition,
new physics searches such as supersymmetry (SUSY) particle search are conducted. The
heavy-ion program is another major task with the LHC to explore the QGP properties. A
new trigger and data acquisition is crucial to accomplish the above physics missions withthe beneﬁt of high luminosity.
All collision event collection is ideal in hadron collider experiments. However, computing power and a storage cost prevented the implementation of all collision event collection
until now. Thus, trigger-based readout systems have been commonly used to maximize theexperimental performance with reasonable data size. Recent technical innovations, such as
high-performance CPUs and a large amount of storage with low costs, allow us to introduce
a continuous readout system. Nonetheless, a recording of all collision events is not realistic
even in the current situation. An effective online data reduction must be implemented torealize a continuous readout.
The four LHC experiments, ALICE, LHCb, ATLAS, and CMS upgrade their trigger anddata acquisition systems to achieve their physics goals with the LHC and the HL-LHC. ALICE and LHCb employ continuous readout systems. ALICE makes a lot of efforts to have data
reduction by online data reconstruction and calibration with detector conditions to record
Pb-Pb collision events as much as possible. Similarly, LHCb selects their interested event
candidates with a temporary recording of whole pp collision events by utilizing a characteristic decay topology of heavy ﬂavor hadron decays more efficiently compared to selections of
its high-level hardware trigger which have the trigger rate limitation of 1 MHz technically.
On the other hand, it is more challenging to have continuous readout systems for ATLAS
and CMS, which aim to take data with the higher luminosity of the HL-LHC. Hardware trigger systems are still employed because their trigger systems have room for improvements,
then faster high-level hardware triggers can meet their requirements with reasonable efforts
to pick up the energetic events in which their target particles such as Higgs bosons and
SUSY particles are generated. However, their trigger rates are close to the limitation andcontinuous readout systems can be the best choice for any experiments. Further technology
innovations will allow to record all collision data with continuous readout systems even withmuch higher luminosity.

As discussed above, we should aim to realize continuous readout systems in any hadroncollider experiments. ALICE is one of the frontiers in this ﬁeld. Data reduction must be
done for a continuous readout. Online calibration and reconstruction with considering detector conditions are crucial in the new ALICE readout system. The control and monitoring
system for sub-detectors was separated from the physics data processing system in the previous readout system. However, the detector condition data such as temperature, pressure,inactive regions, and so on are important inputs for calibration and reconstruction. In the
new system, they come along with raw data of sub-detectors in the same data stream so thatthe online calibration and reconstruction is done more efficiently. As a result, the processing
data size can be signiﬁcantly reduced by a factor of seven at the calibration stage and an additional factor of ﬁve at the reconstruction stage. Finally, the reduced data can be stored in adata storage for offline data processing. The continuous readout system increases the physics
performance of ALICE by a signiﬁcant improvement of the data collection capability.
The new system has been demonstrated with the Muon Forward Tracker (MFT), newly
installed in the ALICE detector from the coming runs. The MFT detector control system
is designed and developed from scratch based on the new control and monitoring scheme.
The new control scheme is a model case for a continuous readout system and online data
reductions.

2Contents
Preface6

I Data Acquisition and Physics Impact in the Large-Scale Hadron Collider
Experiments
7
1 Introduction
1.1 Modern particle physics with the evolution of experimental technologies . . .
1.1.1 Particle physics and experimental technologies in the early days . . . .
1.1.2 Quark model and the standard model . . . . . . . . . . . . . . . . . . .
1.1.3 Heavy-ion physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Large hadron collider . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1 HL-LHC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3 Electron-positron collider . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.4 Scope of this thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8
8
9
11
15
15
16
17
17

2 Physics at the LHC
2.1 Standard model and beyond . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.1 Higgs boson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.2 CP violation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.3 Supersymmetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Heavy-ion physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2.1 Quark-gluon plasma . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2.2 Heavy-ion collision experiment . . . . . . . . . . . . . . . . . . . . . . .
2.2.3 Evidence of QGP creation . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2.4 Future researches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19
19
19
21
23
23
23
25
25
31

3 Trigger and data acquisition system
3.1 Experiments with continuous readout systems . . . . . . . . . . . . . . . . . . .
3.1.1 ALICE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1.1 Upgrade of central detectors . . . . . . . . . . . . . . . . . . .
3.1.1.2 Online-offline computing system . . . . . . . . . . . . . . . . .
3.1.1.3 Muon Forward Tracker . . . . . . . . . . . . . . . . . . . . . .
3.1.2 LHCb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.2.1 Detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.2.2 Trigger and data acquisition system in Run 3 . . . . . . . . . .
3.2 Experiments with hardware-trigger based systems . . . . . . . . . . . . . . . .

34
34
35
35
36
36
38
38
39
41

1

3.2.1

3.2.2

ATLAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1.1 Detector upgrade toward Run 4 . . . . . . . . . . . . . . . . .
3.2.1.2 Trigger and Data Acquisition system in Run 4 . . . . . . . . .
CMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2.1 Upgrade toward Run 4 . . . . . . . . . . . . . . . . . . . . . . .
3.2.2.2 Data Acquisition System in Run 4 . . . . . . . . . . . . . . . .

42
42
45
48
48
49

4 Summary and discussion

52

II

54

Detector control system for the muon forward tracker

1 Detector control system at ALICE
1.1 Basics of a detector control system . . . . . . . . . . . . . . . . . . . . . . . . .
1.1.1 New control and monitoring scheme . . . . . . . . . . . . . . . . . . . .
1.2 Scope of this part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

55
55
57
58

2 Muon forward tracker
59
2.1 Muon measurements at ALICE . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
2.2 Detector setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3 Design of the detector control system
3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Power supply system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Cooling system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Control and readout system . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5 Control scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.6 Safety system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

61
61
61
62
63
63
64

4 Conclusion

65

Acknowledgment

67

Acronyms

73

2

List of Figures
1.1
1.2
1.3
1.4
1.5
1.6
1.7

The evolution of the center-of-mass energy of the accelerators. . . . . . . . . .
The schematic view of the cyclotron [1]. . . . . . . . . . . . . . . . . . . . . . .
The phase stability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The spin 1/2 baryon octet (left) and the spin 3/2 baryon decuplet (right) [2]. .
The schematic view of a quadrupole magnet [3]. . . . . . . . . . . . . . . . . .
The CERN accelerator complex [9]. . . . . . . . . . . . . . . . . . . . . . . . . .
The ultimate HL-LHC peak luminosity (red dots) and integrated luminosity(blue line) for pp collisions [11]. . . . . . . . . . . . . . . . . . . . . . . . . . . .

8
10
10
12
12
16
17

2.1
2.2
2.3
2.4
2.5
2.6

The Feynman diagrams of Higgs production from Ref. [12]. . . . . . . . . . . . 20
The interaction strength of Higgs and other particles [13]. . . . . . . . . . . . . 21
The Feynman diagrams of a Higgs boson pair [12]. . . . . . . . . . . . . . . . . 21
The upper limits of the pair production cross-section [14]. . . . . . . . . . . . . 22
The B0 triangle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
The list of the standard model particles and their super-partners predicted bySUSY [18]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.7 The temperature dependence of the energy density and pressure calculatedusing the lattice-QCD [19]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.8 The time evolution of a heavy-ion collision [20]. . . . . . . . . . . . . . . . . . . 25
2.9 The schematics of jet quenching [21]. . . . . . . . . . . . . . . . . . . . . . . . . 26√
2.10 The jet RAA measured by CMS in Pb-Pb collisions at sNN = 2.76 TeV [22]. . . 27
2.11 The comparisons of the experimentally measured jet RAA and calculations [23]. 27
2.12 The Debye screening in a QGP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.13 The temperature-dependent J/ψ spectra QCD calculated by lattice-QCD [24]. 28
2.14 The pT dependent J/ψ suppression measured by ALICE and PHENIX and thetransport models [27]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.15 The schematics of an elliptic ﬂow [28]. . . . . . . . . . . . . . . . . . . . . . . . 30
2.16 The elliptic ﬂow of proton, pion, and Kaon measured by PHENIX [29]. . . . . 30
2.17 The transverse momentum distribution of direct photons at ALICE [30]. . . . . 31
2.18 The comparison of D meson RAA measured by ALICE and the heavy quarktransport models [31]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32√
2.19 The di-electron invariant spectra in 0-10 % central Pb-Pb collisions at sNN =5.5 TeV [34]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.1
3.2
3.3
3.4

The architecture of the ALICE ALICE and trigger system [32]. . . . . . . . . .
The O2 data ﬂow. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Level-0 hardware trigger efficiency vs the instantaneous luminosity [46]. .
The data ﬂow diagrams in Run 2 (left) and Run 3 (right) from Ref. [47]. . . . .
3

35
37
38
39

3.5 The side view of the upgraded LHCb detector [48]. . . . . . . . . . . . . . . . .
3.6 The execution order of track and vertex reconstruction on the HLT ﬁrst step[51]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.7 The reconstructed tracks on the HLT ﬁrst step [51]. . . . . . . . . . . . . . . . .
3.8 The execution order of track and vertex on the HLT second step [51]. . . . . . .
3.9 The schematic view of the ATLAS original detector [53]. . . . . . . . . . . . . .
3.10 The schematic view of the ATLAS Inner Tracker [57]. . . . . . . . . . . . . . . .
3.11 The schematic view of the LAr calorimeter [58]. . . . . . . . . . . . . . . . . . .
3.12 The schematic view of the Tile calorimeter [59]. . . . . . . . . . . . . . . . . . .
3.13 The design of the TDAQ system in Run 4 [61]. . . . . . . . . . . . . . . . . . . .
3.14 The schematic view of the CMS detector in Run 1 [63]. . . . . . . . . . . . . . .
3.15 The architecture of the CMS trigger [72]. . . . . . . . . . . . . . . . . . . . . . .

40
41
41
42
43
43
44
44
46
48
51

4.1 The cross-section and the generation rate vs the jet ET or particle mass with
the LHC luminosity and energy [76]. . . . . . . . . . . . . . . . . . . . . . . . . 53
1.1 The schematic view of the distributed control system. . . . . . . . . . . . . . . 56
1.2 The image of the DCS layers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
1.3 The DCS data ﬂow in the new ALICE DCS framework [78]. . . . . . . . . . . . 57
2.1 The three-dimensional image of the MFT [82]. . . . . . . . . . . . . . . . . . . . 60
2.2 The example of the zones of the half detection plane [82]. . . . . . . . . . . . . 60
3.1
3.2
3.3
3.4
3.5

The schematic view of the MFT devices [82]. . . . . . . . . . . . . . . . . . . . .
The architecture of the MFT power supply system [82]. . . . . . . . . . . . . .
The water cooling system for the MFT detector and the readout units [82]. . .
The tree structure of the MFT control system [82]. . . . . . . . . . . . . . . . .
The DCS data ﬂow for the MFT [82]. . . . . . . . . . . . . . . . . . . . . . . . .

4

62
62
63
64
64

List of Tables
2.1 The branching ratios and the relative uncertainty for a Higgs boson with mH =125 GeV [12]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.2 The dissociating temperature of quarkonia [26] . . . . . . . . . . . . . . . . . . 29
3.1 The representative Level-0 trigger menu in Phase-II experiment [61]. . . . . . 45
3.2 The representative Level-1 trigger menu in the Phase-II experiment based on
Ref. [72]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.1 Comparison between the strategies of the each experiments. . . . . . . . . . . . 53

5

Preface
This thesis is composed of two halves. In Part I, the upgrade strategies of trigger and dataacquisition systems at the large-scale hadron collider experiments and their physics impacts
are described. First chapter explains that the progress of the modern particle physics withthe technical innovations. The physics tasks to be addressed with a hadron collider aredescribed in Chap. 2. Next, it is expressed that the strategies of the large hadron collider
experiments. Chapter 4 summarize the strategies and discuss a trend of trigger and dataacquisition systems.
In Part II, the detector control system for the new detector, following the strategy at
ALICE is described. Chapter 1 is the introduction of the new control scheme to achieve thephysics goals described in Part I. The second chapter explains the concept and setup of new
detector. The design of the control system for the MFT is described in Chap. 3. Finally, theconclusion of the thesis including the contents of Part I is described in Chap. 4.

6

Part I

Data Acquisition and Physics Impact
in the Large-Scale Hadron Collider
Experiments

7

Chapter 1

Introduction
In this chapter, how modern particle physics has been established with the technical improvements of accelerators and detectors are described ﬁrstly.

1.1 Modern particle physics with the evolution of experimental
technologies
Particle physics has progressed with the improvements of experimental technologies, particularly accelerators from the early 20th century. Figure 1.1 shows the growth of the centerof-mass collision energy. Filled markers are ﬁxed-target experiments and round markers arecollider experiments. The standard model, which describes strong, weak, and electromagnetic interactions and includes the quark model, has been establishedwith the experiments√
using the accelerators. Here, the center-of-mass collision energy, s, is deﬁnedq√s = (E1 + E2 )2 − (p1 c + p2 c)2(1.1)
where four-momenta of the colliding particle 1 and the colliding particle 2 are p1 = (E1 ; p1 ) and p2 =(E2 ; p2 ), respectively.

Figure 1.1: The evolution of the center-of-mass energy of the accelerators.

8

1.1.1 Particle physics and experimental technologies in the early days
In the history of detectors, the ﬁrst impact was made by the invention of a cloud chamber byCharles Thomson Rees Wilson. It enabled us to see radiation rays for the ﬁrst time. When acharged particle passes inside supersaturation state gas in a chamber, fog drips are produced
along the particle path. Anderson discovered a theoretically predicted positron, which is anantiparticle of the electron, using a cloud chamber in 1932. He also discovered a muon in
1935. This is an example that a new technology progresses particle physics.
The accelerator developed by Cockcroft and√ Walton was the electrostatic system andaccelerated protons to an energy of 700 keV ( s ∼ 22 keV) in 1932. They made the ﬁrst
nuclear reaction p + 7 Li → 4 He + 4 He with the accelerating protons. Van de Graaff also
developed the accelerator, which was an electrostatic system in the 1930s. The electrostatic
accelerators have a limit of accelerating energy at around O(10) MeV.
The second revolution was the invention of a cyclotron. Figure 1.2 shows the general viewof classical cyclotrons. A cyclotron is composed of an electric magnet and two accelerating
electrodes, called Dees, in a vacuum chamber. The magnet generates a uniform magnetic
ﬁeld, B in units of T, which is perpendicular to the accelerating electrode. A radio frequency
power (RF) is supplied to the Dees. An ion source is located at the center of the chamber andcharged particles are accelerated whenever the particle passes the gap. The particles exit thechamber when a rotation radius, R in units of m, is equal to a radius of the chamber. The
radius R in the uniform ﬁeld, B, is written as
mv 2
= evB
R
R=

γmv
mv
.
= p
eB
eB 1 − (v 2 /c2 )

(1.2)
(1.3)

Here, m, e, and v mean rest mass (in GeV/c 2 ), charge, and velocity of the particle. The radius
R is proportional to the momentum of the particle, therefore, a large magnet is needed toachieve higher energies. Rotation frequency, ω, isω = 2πveB=.
2πR γm

(1.4)

In the non-relativistic case (v << c), ω is ﬁxed because a particle mass is constant. However,a particle’s mass depends on the velocity in the relativistic energy. Hence, ω is not constantand it is difficult to synchronize the radio frequency with the rotation frequency to acceleratecharged particles. The maximum energy of accelerated protons is around 20 MeV in the caseof classical cyclotrons. Transuranium elements including neptunium were synthesized using
the classical cyclotrons in the 1940s.
The synchrotron principle was invented by Veksler and McMillan independently in 1945.
They solved the synchronization of a rotation period and a radio frequency. An accelerated
beam trajectory is ﬁxed and a magnetic ﬁeld is changed stronger according to the accelerated
energies. Electromagnets are small because they are located around the trajectory. Longitudinal oscillations of accelerated particles occur. The phase stability was considered to solve
longitudinal oscillations. Figure 1.3 shows a general view of the phase stability. Here, O andO’ are synchronous particles with a radio frequency and run in a rotation period of Trf . The
particle A coming from behind the particle O is accelerated with a lower accelerating electricﬁeld than the particle O. The particle A places a point A’ closer to the synchronous point O’
9Figure 1.2: The schematic view of the cyclotron [1].
in the next round because the particle A runs a smaller trajectory than that of the particle O.
In contrast, the particle B is accelerated with a higher electric ﬁeld than the particle O. The
particle B reaches a point B’ closer to the synchronous point O’ in the next round because
the particle B runs a larger trajectory than that of the particle O. The ﬁeld B increases andsynchronizes the ﬁeld B following the increase of the beam energy. We can accelerate thecharged particles to a relativistic speed using synchrotrons.

Figure 1.3: The phase stability.
The early synchrotron experiments were conducted using the Cosmotron at the Brookhavennational laboratory (BNL) and the Bevatron at the Lawrence Berkeley National Laboratory(LBNL). The Cosmotron is the ﬁrst synchrotron that could accelerate protons to energies of
the GeV range, in detail 3.3 GeV, starting in 1953. The Bevatron, which could accelerate protons to energies of 6.2 GeV, at LBNL had started in 1954. A lot of hadrons were discoveredby the experiments with them in the 1950s and 1960s. Heavy hadrons, which were initiallycalled V-particles and known in cosmic-ray experiments, were produced and a strangenessparticle was conﬁrmed experimentally associated with the theoretical prediction at the Cosmotron. A positron was already known as the antiparticle of an electron. Antiproton and10

antineutron were discovered in 1955 and 1956 at the Bevalac. The facts represented that all
particle has a corresponding anti-particle. O(100) species of hadrons discovered at the Cosmotron and the Bevatron indicated that hadrons are not elementary, but composite particles
of sub-particles.
In addition to the synchrotron development, the new detector technology had also progressed particle physics. The new detector was a bubble chamber developed by Glaser in
1952. The previous experiments employed cloud chambers. Synchrotrons provided higher
energies than cyclotrons. Hence, high-energy particles did not interact with the gases ofcloud chambers because a gas density is too low to detect high-energy particles. He employed liquids instead of gases for the bubble chamber. A liquid density is around 1000
times larger than that of gases, therefore, the bubble chamber enabled to detect high-energy
particles and to study interactions including a lot of secondary particles.

1.1.2 Quark model and the standard model
The essential progress of theories was made from the mid-1950s to the early 1960s. Kazuhiko
Nishijima and Murray Gell-Mann proposed a new quantum number strangeness (S) independently to understand the properties of V-particles. Strangeness is deﬁned as that it conserves
in strong interactions but does not in weak interactions. Also, they introduced the hypercharge, Y , in the following formula
Q = I3 + (B + S)/2 ≡ I3 + Y /2

(1.5)

where Q is an electric charge (proton charge is unity); I3 is the third component of isospin,
which was introduced to classify a proton and a neutron; B is a baryon number (B = 0:mesons, B = 1: baryons, and B = 1, S , 0: hyperons). All hadrons satisfy the Nishijima-GellMann formula. Ikeda, Ohnuki, and Ogawa introduced SU (3) symmetry based on the Sakata
model, of which the basic particles are proton, neutron, and Λ which has a strangeness. In
1964, Gell-Mann and Zweig proposed the quark model independently to classify the experimentally discovered hadrons. The quark model is based on the SU (3) group and employs
three elementary particles, named quarks: up (u), down (d), and strange (s) quarks. SU(3) isthe set of unitary matrices of 3 × 3 with det U = 1. The basic expression of SU(3) is a triplet.
Eight independent basic vectors make the meson octet. The spin 1/2 baryon octet can be
written using I3 and Y of quarks as shown in the left panel of Fig. 1.4. The SU (3) derives
baryons candidates, which are combinations of qqq as shown in the right panel of Fig. 1.4.
The baryons (∆, Σ, and Ξ) were already known in the experimental results. However, thelast particle in the spin 3/2 baryons composed of sss, namely Ω, was not discovered yet.
Around the same time, there was a technical improvement of synchrotrons to increase
beam intensity. A beam must be focused around an ideal trajectory. The focusing technique
is required at an injection of a beam to an accelerator and extraction of a beam from an accelerator. Livingston et al. invented the alternating-gradient focusing which is also calledstrong focusing. Quadrupole magnets are employed for focusing as shown in Fig. 1.5. A
quadrupole magnet focuses a beam in one direction, e.g. the horizontal direction in the ﬁgure. The beam is diffused perpendicularly to the focusing direction (the vertical direction).
Two 90 degrees rotated magnets are located on opposite sides of the magnet and they canfocus the beam in both directions.
The alternating gradient synchrotron (AGS), which employs the strong focusing as its
name implies, was developed at BNL. The experiment discovered a new particle using the11Figure 1.4: The spin 1/2 baryon octet (left) and the spin 3/2 baryon decuplet (right) [2].

Figure 1.5: The schematic view of a quadrupole magnet [3].
AGS and a bubble chamber [4]. The properties of charge Q, strangeness S, and mass M of
the new particle were Q = −1, S = −3, and M = 1686±12 MeV/c 2 , respectively. They are consistent with the theoretical predictions of Ω baryon.The fact showed that the quark model
was a reasonable theory.
The other valuable experimental result was also discovered in 1964; it was CP violation.
Cronin and Fitch discovered CP violation via neutral K meson decays using the AGS at
BNL. C is charge conjugation which means particle-antiparticle transformation. P is parity
operation which means spatial reﬂective symmetry. Both K 0 and its antiparticle K 0 havedecay channels with two pions and three pions. A two-pion (π0 π0 ) system has positive parity
and a three-pion (π + π− π0 ) system has negative parity. Therefore, a transition between K 0
and K 0 are allowed via pions in a weak interaction K 0 ↔ {2π, 3π} ↔ K 0 . It is called mixing.
Neutral kaons are produced in reactions such as p + n → p + Λ0 + K0 . The produced kaons
are short-lived kaons, KS0 , and long-lived kaons, KL0 . KS0 decays into two pions and KL0 decays
into three pions. In this case, CP is conserved. However, the decay channel of KL0 → π 0 π 0was observed in a small probability and in that case, CP is violated.
The mixing is explained via the Cabibbo angle, θC , introduced by Cabbibo to understandstrange particle decays in weak interactions in 1963. We consider quark bindings of the12quark state as follows!
!
cu, ′ ...,
s
d′

(1.6)

d ′ = d cos θC + s sin θC ,(1.7)

s ′ = s cos θC − d sin θC .

(1.8)

where,

These equations are written in a matrix!
! !
cos θC sin θC dd′=s′− sin θC cos θC s

(1.9)

His idea was extended to three generations by M. Kobayashi and T. Masukawa. The extended
matrix is called Cabbibo-Kobayashi-Masukawa matrix (CKM matrix), VCKM :
 ′
  
 
d d  Vud Vus Vub  d 
 ′     s  = VCKM  s  =  Vcd Vcs Vcb   s (1.10)
   ′   bb
Vtd Vts Vtb b

where Vqi qj is a squared root of a probability of a transition from quark qj to quark qj . The
CKM matrix is unitary and the components are correlated. The CKM matrix has four independent parameters which are three real angles and an imaginary phase. The imaginary
phase causes the CP violation. CP violation was measured in neutral B meson by the Belleexperiment at KEK and by the BaBar at SLAC, respectively. Currently, LHCb at CERN and
the Belle II experiment at KEK study more precisely the CP violation via B meson and also
D meson decay channels. This physics will be described in Sec. 2.1.
The CKM matrix requires six quarks in three generations. Three out of six are newquarks: charm (c), bottom (b), and top (t) quarks. If the quarks were discovered, the CKM
matrix is established.

J/ψ, which is composed of c and c̄ quarks, was discovered by the SPEAR experimentat√
SLAC using the electron-positron collider accelerated energies of around 4 GeV ( s = 8 GeV)
and√ the experiment at BNL using AGS in collisions of 28 GeV protons on a beryllium target( s ∼ 5.3 GeV) in 1974. It meant the discovery of a new quark ﬂavor. The experiment at
SLAC also discovered an excited state of charmonium, ψ ′ . The discovery is called as theNovember revolution. The discovery of the c quark showed the validity of the quark modeland the CKM matrix. Furthermore, the E288 experiment at Fermilab discovered the bottom quark via Upsilon (Υ) meson√ decays in 1977 using injecting protons with the energy of
400 GeV to Cu and Pt targets ( s ∼ 20 GeV) [7]. It was the ﬁrst quark in the third generation.
The quark model and the CKM matrix became the basis of the standard model because of
the new quark discoveries.
In the 1960s, attempts had been made to uniform electromagnetic and weak interactions
in parallel with the theoretical construction of the quark model. Weak interaction was proposed by E. Fermi in 1935 to describe a beta decay process. H. Yukawa introduced π meson
as a propagator of weak interaction at the same time. His attempt proved abortive, however, the thought of exchange particles for fundamental interactions has become basic of13

the standard model. Heavy particles W ± , which must have a spin of 1, were introduced as
exchange particles of weak interaction. Thereafter, a neutral particle Z 0 was employed to
explain neutral reactions by weak interaction. S. Glashow proposed SU (2)L × U (1)Y for uniﬁcation quantum electrodynamics and weak interaction in 1961. The additional character
L explains that weak isospin current interacts with left handed Fermions. S. Weinberg and
A. Salam expanded independently his idea to derive a Lagrangian which are SU(1) × U (1)invariant. The theory proposed by Weinberg and Salam uniﬁes electromagnetic interaction
and weak interaction; they are integrated electroweak interaction. The theory is called the
Glashow-Weinberg-Salam (GWS) theory. The new technologies for accelerators were necessary to discover weak bosons.
Here, two types of accelerator experiments must be marshaled. In ﬁxed-target experiments, accelerated particles are projected onto a target. The target particle momentum iszero (p2 = 0) and the projectile and target particle masses are sufficiently smaller than the
projectile particle energy (m1 , m2 ≪ E1 ), then, the center-of-mass energy in the ﬁxed-target
experiments using Eq. 1.1 can be written as:qp√s = (E1 + m2 c2 )2 − (p1 c)2 ∼ 2E1 m2 c2 .
(1.11)The other important parameter is luminosity. The luminosity L in the ﬁxed-target experiments are deﬁned
L = Nin ρlNA .
(1.12)
Here, Nin is the number of projectile particles (in /sec), ρ is the density of a target (in g/cm3 ),l is the length of the target (cm), and NA is the Avogadro constant.
In collider experiments, momenta of a projectile particle and a target particle are thesame (p1 = p2 ), therefore, the√ center-of-mass energy in the collider experiments is the sameas the sum of beam energy s = E1 + E2 . Thust, colliders can produce larger center-of-massenergies than ﬁxed-target experiments effectively. The luminosity of the collider experiments is written
N N f
L = 1 2
(1.13)
nb A
where N1 and N2 are the numbers of particles in beamlines of an accelerator, f is rotation
frequency, nb ispthe numberof bunches, and A is the beam area at a collision point. A ispdeﬁned as A = ǫx βx ǫy βy by amplitudes β and emittance ǫ in the perpendicular coordinate, x and y, to a beam axis z. The luminosities provided by colliders are lower than those
provided the ﬁxed-target experiments.
C. Rubbia proposed a proton-antiproton collider, a modiﬁcation of the SPS, to search
for the weak bosons. The signiﬁcant improvement to realize a proton-antiproton collider
was brought by S. van der Meer. He invented a new method to increase the luminosity of
antiproton beams in a phase-space, and the method is called stochastic cooling. In a protonantiproton collider, antiprotons are produced by projecting protons to a target. An antiproton production rate per projecting proton is 10−6 and around 1011 antiprotons are produced
in a day. Antiprotons are stored in an antiproton accumulator. Stored antiprotons are notappropriate to be accelerated because they have a disordered momentum distribution which
is analogous to the high-temperature antiprotons. He achieved the cooling and the acceleration of antiprotons by stochastic cooling. The technology enabled them to realize the super14

proton-antiproton synchrotron (Spp̄S) at CERN. It was the world’s ﬁrst proton-antiproton
collider. The experiments led by C. Rubbia discovered the weak bosons using the Spp̄S in
1983. C. Rubbia and S. van der Meer received the Nobel prize in physics. This is a good
example that the new technology progresses physics. Collider experiments have become
mainstream in high-energy particle physics since then.
The last quark, namely top quark, was discovered√ by the experiments, CDF and D0,
using the proton collider, Tevatron, at the energy of s = 1.96 TeV at√Fermilab in 1995. The
large hadron collider (LHC) has started in 2008 in pp collisions at s = 8 TeV. ATLAS andCMS discovered the Higgs boson, which was the last piece of the standard model particles, in2012. Further study for the next physics has been performed at the LHC. They are expressedin Sec. 2.1.

1.1.3 Heavy-ion physics
Strong interaction between quarks is described by quantum chromodynamics (QCD). QCD
requires a gluon which propagates strong interaction. Partons, namely quarks and gluons,
have color charges: red, blue, green, and their anti-colors. Combinations of quarks must
be colorless, such as red+green+blue and red+anti-red. Strong interaction strength between
two quarks is in inverse proportion to a distance between the quarks. It is called asymptotic
freedom. Strength of strong interaction becomes zero in a high-energy limit and partonsbehave as free particles.
Heavy-ion, which is heavier nuclei than a proton, accelerators are powerful tools to test
QCD in high-energy limits. Heavy-ions, such as Ne and Ar, had been accelerated to energies
of 2.1 GeV/A (Ne) and 1.9 GeV/A (Ar) by the Bevalac at LBNL for the ﬁrst time to search forthe theoretically predicted phenomena, e.g. compressed hadronic matter, from 1971. It is theﬁrst heavy-ion accelerator with ﬁxed targets. The QCD calculations√ predicted a hardon deconﬁnement phase and suggested√higher center-of-mass energy, s, of the Bevalac. The AGS
at BNL has accelerated Au ion at s = 5 GeV to search the deconﬁnement
phase from 1986.
√
At the same time, SPS at CERN has accelerated Pb ions at s = 17 GeV. The experimentswith SPS reported several results which imply the creation of a QGP. However, the results
were inconclusive evidence for the creation of a QGP because hadron-cascade calculations
can reproduce the results in a situation without a QGP. From 2000, relativistic heavy ion col√lider (RHIC) at BNL has started and accelerated Au ions to 100 GeV/A ( sNN = 200 GeV) to
produce a QGP and study the properties of a QGP. The experiments, PHENIX and STAR, reported the multiple evidence suggesting the creation of the deconﬁnement phase. The QGP
study has been performed using the LHC at CERN. The LHC can accelerate Pb ions to the√energy of 2.51 TeV ( sNN = 5.02 TeV). In such energy, the properties of a QGP produced by
the LHC are higher-temperature and -density than that of a QGP by RHIC. Today, researches
for the understanding of the QGP properties are performed using the LHC and RHIC. The
detailed physics in the heavy-ion experiments is described in Sec. 2.2.

1.2 Large hadron collider
The large hadron collider (LHC) [8] is the largest hadron accelerator of the European organization for nuclear research (CERN) and is located across the border between Switzerlandand France. Figure 1.6 shows the CERN accelerator complex. Accelerators from a linear ac15

celerator (LINAC) to the super proton synchrotron (SPS) are used as boosters. A ring coloredby dark blue is the LHC and it is the last ring in the accelerator chain.

Figure 1.6: The CERN accelerator complex [9].
The center-of-mass energy of the LHC nominal design is 14√ TeV in pp collisions and
5.5 TeV in Pb-Pb collisions. The LHC provided pp collisions at s = 8 TeV, p-Pb collisions√√
In
at sNN = 5.02 TeV, and Pb-Pb collisions at sNN = 2.75 TeV in Run 1 (2009-2013).
√
Run 2 (2015-2018), the center-of-mass energies provided by the LHC were s = 13 TeV in√√
pp collisions, sNN = 8 TeV in p-Pb collisions, and sNN = 5.02 TeV in Pb-Pb collisions.
The peak luminosities of Lpeak = 2 × 1034 cm−2 s−1 for pp collisions was achieved at ATLAS
and CMS in 2018 due to the bunch space reduction from 50 ns to 25 ns, small emittances,and smaller β∗ of 30 cm than the design value of 50 cm [10]. The peak luminosity is twotimes larger than the design luminosity value. The designed luminosity value of Lpeak =1 × 1027 cm−2 s−1 for Pb-Pb collisions was achieved at ALICE in Run 2. The peak luminosity
for Pb-Pb collisions will be Lpeak = 6.4×1027 cm−2 s−1 at ALICE in Run 3 (2022-2024) thanks
to an increase of a collision rate to 50 kHz [10].

1.2.1 HL-LHC
The center-of-mass energy of 14 TeV provided by the LHC will be the highest at least in thenext decade since we need a larger circular collider than the LHC to generate a larger centerof-mass energy than that of the LHC. However, an increase of luminosity can be achieved.
CERN upgrades the LHC luminosity above the nominal design in the 2020s and the nameis the high-luminosity LHC (HL-LHC) [10]. The Run 3 term is the transition stage from the
LHC to the HL-LHC. The innovative technologies are employed for the HL-LHC, e.g. 11
to 12 T superconducting magnets, RF cavities for beam rotation with ultra-precise phase
control, new technologies, and material for beam collimation, and high-current supercon16

ducting links with almost zero energy dissipation. The technologies will provide focused
beams, that reduce a beam cross-sectional area A in Eq. 1.13.
The peak luminosity of the HL-LHC will be reached Lpeak = 5 × 1034 cm−2 s−1 in Run 4
starting in 2028 with a bunch crossing rate of 40 MHz (ultimately Lpeak = 7.5×1034 cm−2 s−1
in Run 5) for pp collisions as shown in Fig. 1.7. The HL-LHC will provide more data than thewhole LHC data and the data will enable us to observe rare processes and new phenomena.
In such high-luminosity levels, the number of concurrent proton-proton interactions, which
are called pileup events, per bunch crossing reaches as many as 200.

Figure 1.7: The ultimate HL-LHC peak luminosity (red dots) and integrated luminosity (blueline) for pp collisions [11].

1.3 Electron-positron collider
Electron-positron colliders, such as the superKEKB, produce less background comparedto hadron colliders. Less background allows recording pure physics signals. The current
electron-positron colliders are circular colliders. Electrons and positrons lose their energies
due to bremsstrahlung. The cross-section of bremsstrahlung is σbr ∝ Z 2 α 3 /m2e c4 . In thecase of heavier particles than electrons and positrons, the effect of bremsstrahlung can be ignored. Therefore, an acceleration efficiency of a synchrotron electron-positron collider is notas high as that of a hadron collider. The hadron colliders or a linear accelerator, such as theinternational linear collider (ILC), are necessary for physics researches in the high-energy
frontier.

1.4 Scope of this thesis
As described, particle physics has progressed with the evolution of experimental technologies. Even today, innovations of technologies impact on the particle physics. The LHC upgrades will be able to progress the particle physics. At the LHC, the increase of luminosity is
the main upgrade project by higher collision rates or small cross-sectional areas of beams. A

17

data volume will grow with the increase of luminosity. Hence, data acquisition systems willencourage particle physics to process data.
In this thesis, technologies of the data acquisition and processing systems will be described and physics impacts provided by the technologies will be discussed at large-scale
hadron collider experiments in the higher-luminosity era.

18

Chapter 2

Physics at the LHC
In this section, the research topics at the LHC, the standard model, and beyond the standard
model are written in 2.1, and the heavy-ion physics is shown in 2.2.

2.1 Standard model and beyond
All the standard model particles were founded due to the discovery of a Higgs particle in2012. Properties of a Higgs boson are measured precisely.

2.1.1 Higgs boson
P. Higgs proposed a model to explain masses of weak bosons in 1964. The model is called the
Higgs mechanism and needs a new boson which is a spin-parity of 0+ and named a Higgs
boson. Search for a Higgs boson was a high-priority issue of the LHC that started in 2009.
ATLAS and CMS reported discoveries of a new boson, whose mass and spin-parity are 125
GeV/c 2 and 0+, individually in 2012. The parameters were consistent with the prediction
and the fact showed the new boson is a Higgs boson. The research phase has moved fromthe search for a Higgs boson to the study of a Higgs boson. Precise measurements of thecoupling to other particles and to itself are necessary to understand the Higgs mechanism.
Measurements of coupling strength of a Higgs boson to other particles are evaluatedusing combinations of a production process and a Higgs decay channel. Four main processes
are predicted in the standard model and their Feynman diagrams are shown in Fig. 2.1. The
gluon gluon fusion (ggF) produces only a Higgs boson. Decay objects of a Higgs boson aredetected. The vector boson fusion (VBF) produces a Higgs boson and a pair of quarks andeach quark is detected as a jet which is a bunch of high-energy hadrons. The vector boson
associated production (VH) produces a weak boson, W /Z, in addition to a Higgs boson.
Weak bosons have decay channels of Z → νν, W → νℓ, and Z → ℓℓ. These decay modes
are triggered easily because their decay objects have large-pT or large missing energy ETmiss .
The top quark pair associated production (ttH) is a direct probe of a top quark and a Higgs
boson coupling. A top quark decays to a bottom quark and a W boson mainly. Thus, the ttH
production is detected via a b-jet and W decay products.
The standard model also predicts decay channels of a Higgs boson. Table 2.1 shows
the branching ratios and the relative uncertainty of the Higgs decay channels. The Higgs
decaying to a pair of b-quarks, H → bb̄, is the dominant channel in the Higgs decay channel.
19Figure 2.1: The Feynman diagrams of Higgs production from Ref. [12].
Each b-quark is observed as a jet, therefore, a tagging of the jet is needed. The weak boson
decay channels of a Higgs boson are measured via the weak boson decay channels. The twotau decay channel is measured via jets because 64 % of taus decay to hadrons. Therefore, adedicated trigger for tau leptons is necessary to identify tau decay jets and other jets. The
channel H → cc̄ is not observed.
Table 2.1: The branching ratios and the relative uncertainty for a Higgs boson with mH =125 GeV [12].
Decay channel Branching ratio Rel. uncertainty
H → γγ2.27 × 10−3
2.1%
−2
H → ZZ
2.63 × 10±1.5%
H → W +W −2.14 × 10−1
±1.5%
H → τ+τ−
6.27 × 10−2
±1.6%
+1.2%
−1
H → bb̄
5.82 × 10
−1.3%
+5.5%
H → cc̄2.89 × 10−2
−2.0%
H → Zγ1.53 × 10−3
±5.8%
H → µ+ µ−2.18 × 10−4
±1.7%
The measurements of the coupling strength were performed by ATLAS and CMS. Figure
2.2 shows the mass-dependent coupling strength measured by ATLAS in Run 2 [13]. The
blue dotted line is the mass-dependent coupling strength evaluated by the standard model.
The black points are measured strength experimentally. The bottom panel shows the normalized by the calculation. The measured strength to a top and weak bosons are consistent
with the standard model with uncertainties of less than 10 %. The couplings to a bottom
and a tau are corresponding to the standard model with errors of 15 %. The coupling to amuon is in agreement with the calculation with errors of 30 %. The conﬁdence level of thecoupling is 95 % and more amount of statistics are necessary to test the standard model. It is20difficult to measure the coupling to an electron even at the HL-LHC [63]. If there is a difference between a measured strength and the standard model prediction, it will be a signatureof new physics, because the couplings of Higgs bosons to other particles generate masses ofthe particles and the difference needs a mass generation via another Higgs boson which ispredicted in beyond the standard model.

Figure 2.2: The interaction strength of Higgs and other particles [13].
In addition, the self-coupling of a Higgs boson is an important parameter to understandthe Higgs mechanism because its potential can be determined experimentally via the selfcoupling. Measurements of self-coupling strength are performed via pair productions of
Higgs bosons. The main production processes are shown in Fig. 2.3. The cross-section of diHiggs boson productions is around one-thousandth of the cross-section of the single Higgs
production processes. Figure 2.4 shows the upper limits of the pair Higgs productions ineach decay channel in a 95 % conﬁdence level at ATLAS in Run 2.

Figure 2.3: The Feynman diagrams of a Higgs boson pair [12].

2.1.2

CP violation

CP violation measurements provide the standard model test with a different perspective
than the Higgs measurements. CP violation in B meson decays was discovered by the Belle
21

Figure 2.4: The upper limits of the pair production cross-section [14].
experiment at KEK and by the BaBar experiment at SLAC in 2001. In 2019, CP violationin the D meson decays was discovered at LHC. CP violation measurements in heavy quarkmeson systems are powerful ways to test the standard model.
The CKM matrix mentioned in Sec. 1.1 explains the mixing of mesons. The CKM matrix
is unitary. Test for a unitary triangle, which is provided by the CKM matrix, is equal to test
for the CKM matrix. The unitarity of the CKM matrix described in Eq. 1.10 leads to six
relations of the matrix elements. For example, the triangle in a B0 (bd) is written as∗∗∗
Vud Vub+ Vcd Vcb
+ Vtd Vtb
=0

(2.1)

and the triangle in a D 0 (cu) is described as∗∗= 0.
Vud Vcd+ Vus Vcs∗ + Vub Vcb(2.2)

The B0 triangle is drawn in the complex plane as shown in Fig. 2.5 using the unitarity as Eq.
2.1. Here, Eq. 2.1 is normalized as follows:∗∗
Vud Vub
Vtd Vtb∗ +∗ + 1 = 0.
Vcd Vcb
Vcd Vcb(2.3)

The parameters, ρ̄ and η̄, in the B0 triangle are given byρ̄ + i η̄ = −∗Vud Vcb∗ .
Vcd Vcb(2.4)

If the triangle is closed, the standard model is correct. If not, another contribution of new
physics to CP violation is implied.
Parameters in Figure 2.5 are evaluated via rare decays of B and D mesons. For instance,
the angle, γ, is determined via the processes, such as B± → D 0 K ± whose branching ratio is+5.0 ◦) using the LHCb detector [16] .
less than 1.3 × 10−5 . The evaluated value of γ is (74.0−5.8
22Figure 2.5: The B0 triangle.
High-precision measurement of less than 1◦ for γ is necessary to match anticipated theory
improvements [17]. Similarly, the angles (α, β, and γ) and the components of the triangle
sides (Vub , Vcb , and Vtd ) can be determined by measurements of B meson decays. D meson
measurements contribute to the components of the triangle sides (Vcd , and Vcs ).
B and D mesons are reconstructed by their decay products which are leptons and hadrons.
Lifetimes of B mesons, cτB , and D mesons, cτD are approximately 450 µm and 100 µm, respectively. They are longer than other hadrons and have secondary vertices which mean
decay points of B and D mesons. Detection and tracking of all particles are crucial to thedetermination of secondary vertex with identiﬁed decay particles. The LHCb detector is located in the forward region, 2 < η < 5, because particles are boosted in a forward direction
and the detector setup has an advantage for secondary vertex measurement.

2.1.3 Supersymmetry
Supersymmetry (SUSY) is beyond the standard model. SUSY predicts super-partners forevery standard model particle at the TeV scale as shown in Fig. 2.6. The masses of SUSY
particles are above O(1) TeV/c2 . SUSY particles, suc as squarks and gluinos, are searchedmiss because stable SUSY particles interact
with a signiﬁcant missing transverse energy ETvery weakly with detectors.

2.2 Heavy-ion physics
2.2.1 Quark-gluon plasma
The behavior of partons, namely quarks and gluons, is described by QCD. The QCD coupling constant αs is written as
αs =

12π
.
(33 − 2nf ) ln(Q2 /Λ 2 )(2.5)

Here, nf is the number of ﬂavors and Q 2 is momentum transfer. Λ shows the QCD scaleparameter, which is derived from QCD calculation and experiments, and the typical value is23

Figure 2.6: The list of the standard model particles and their super-partners predicted bySUSY [18].
Λ ∼ 250 MeV/c 2 . Q 2 depends on the distance between partons and becomes large when the
distance becomes short. Coupling between partons becomes zero asymptotically in Q2 → ∞.
It is called asymptotic freedom, which is one of the QCD nature. On the other hand, thecoupling between partons is strong when the distance is large. Therefore, each parton isconstrained in hadrons and it is called quark conﬁnement.
The lattice-QCD calculation predicts that a temperature of a system becomes the criticaltemperature, Tc , of around 200 MeV and the energy density and the pressure of the system increase drastically due to the quark deconﬁnement as shown in Fig. 2.7. The quark
deconﬁned state is called the quark-gluon plasma (QGP).

Figure 2.7: The temperature dependence of the energy density and pressure calculatedusing the lattice-QCD [19].

242.2.2 Heavy-ion collision experimentHigh-energy heavy-ion collision is a powerful tool to study the QGP experimentally. A
heavy-ion collision has a drastic space-time evolution including the QGP and subsequent
hadronic matter. Evolution is separated into several stages.
1. Color glass condensate: Saturated state of gluons which are produced by quarks inaccelerated nuclei
2. Initial collision: Partons in colliding nuclei toward each other scatterings in a reaction
region3. Glasma: Intermediate state of the color glass condensate and the QGP phase
4. QGP phase: Thermal equilibrium and partonic state with a high energy density createdby parton scatterings
5. Hadronic phase: Hadronized parton state when the system expands and the temperature becomes below Tc
6. Freeze-out: No more particle production in a chemical freeze-out and then no morechange of momentum in a kinetic freeze-out

Figure 2.8: The time evolution of a heavy-ion collision [20].
Integrated particles produced in a whole history are measured. A study of each stage
means understanding the whole history of a heavy-ion collision. Therefore, the comprehension of the whole history of a heavy-ion collision is crucial to study each stage using particles
sensitive to each stage. It indicates that various measurements are necessary for a study of
the QGP properties. Essential results are described in the next section.

2.2.3 Evidence of QGP creation
A lot of physics data were collected from 2000 at RHIC, where the QGP creation has been
ensured for the ﬁrst time experimentally. Then, the LHC since 2009 is the frontier of the
QGP study as well as RHIC. Here, four signiﬁcant results proving the QGP creation are
described.

25

1. Jet quenching A jet is a bunch that contains a lot of high-energy hadrons. High-energy
initial parton-parton scattering produces a pair of energetic partons. Then, hadrons are produced by the fragmentation of partons. If a high-density medium like the QGP is produced,
partons in jets lose their energy due to interactions with the medium. Therefore, jets arequenched ﬁnally and an amount of energy loss depends on a medium density.
Figure 2.9 shows the schematic view of a jet quenching. It is illustrated that the jetpassing a long-range in a matter loses more energy and is quenched relative to the jet runs ashort-range inside the matter. Jet quenching is one of the most important pieces of evidenceof QGP creation.

Figure 2.9: The schematics of jet quenching [21].
The nuclear modiﬁcation factor, RAA , is introduced to quantify results between AA andpp collisions. RAA is deﬁned as
3NAA
E d dp
3
.
(2.6)
RAA =
d3N
Ncoll E dp3pp
3

d3N

NAA
and E dp3pp are the invariant yields in AA collisions and pp collisions, respecHere, E d dp
3
tively. Ncoll is the number of binary collisions in an AA collision. If RAA is equal to unity, itmeans that a yield in AA collisions results from a superposition of pp collisions. If not, thedifference is induced by a new matter.
√
Figure 2.10 shows the pT dependent jet RAA in Pb-Pb collisions at sNN = 2.76 TeV in
the centrality ranges of 10-30 %, 5-10 %, and 0-5 % measured by CMS [22]. The ﬁlled
circles are measured RAA . The error bars mean the statistical uncertainties. The yellow
boxes represent the pT dependent systematic uncertainties. The gray shaded boxes are an
additional systematic uncertainty from the normalization and the pp integrated luminosity.
The results show that the pT dependent jet yield in Pb-Pb collisions is suppressed. It suggeststhat jets lose their energy in the medium.
An amount of energy loss of partons, ∆E, is proportional to a parton stopping power ofthe matter, q̂. The stopping power is deﬁned as q̂ = m2D /λ. Here, mD is a Debye mass andλ is a mean free path. Figure 2.11 shows the comparisons of experimentally measured RAA

26

√Figure 2.10: The jet RAA measured by CMS in Pb-Pb collisions at sNN = 2.76 TeV [22].
and theoretical calculations. The black points and the blue stars represent the pT depen√
dent jet RAA in the most central Pb-Pb collisions at sNN = 2.76 TeV by CMS and ALICE,
respectively. The magenta dashed lines are the ﬁt to the combined experimental data withq̂ = 1.4, 1.8, 2.6, and 3.0 GeV2 /fm from the top. The red line is the best ﬁt for the combined
experimental data. The ﬁt leads the stopping power of q̂ = 2.2 ± 0.5 GeV2 /fm.

Figure 2.11: The comparisons of the experimentally measured jet RAA and calculations [23].
2. J/ψ suppression J/ψ is a quarkonium composed of charm quarks (cc̄) and is sensitive to
the QGP temperature. J/ψ is produced mainly by gluon fusion in initial collisions and has awhole space-time evolution experience. Hence, we can study matter effects using J/ψ.
J/ψ melts by the Debye screening in the QGP. Quarks of J/ψ are screened by many lightquarks in the QGP as shown in Fig. 2.12. The c quarks bind light quarks and then the numberof J/ψ is decreased. A yield in AA collisions is suppressed compared to a superposition yieldof pp collisions. This is the J/ψ suppression by the Debye screening.
According to the lattice-QCD calculation, a suppression level depends on a temperatureof a QGP. Figure 2.13 shows the lattice-QCD calculations for cc̄ spectral functions. The
horizontal axis and the vertical axis represent a real frequency and the magnitude of spectra.
27

Figure 2.12: The Debye screening in a QGP.
The long dashed-dotted line, the dashed line, and the solid line in Fig 2.13 (a) represent theJ/ψ spectra at the temperatures of 0.78Tc , 1.38Tc , and 1.62Tc . The solid line and the dashedline in Fig 2.13 (b) are also the J/ψ spectra at the temperatures of 1.87Tc and 2.33Tc . The plotsshow that J/ψ melts in the matter temperature of 1.87Tc . Also, the J/ψ production is more
suppressed in the higher temperature. The peaks in ω = 0 in Fig. 2.13 (b) are calculation
errors.

Figure 2.13: The temperature-dependent J/ψ spectra QCD calculated by lattice-QCD [24].
Figure 2.14 shows the pT dependent J/ψ RAA measured by ALICE with the red points
and PHENIX with the black points. Both RAA is suppressed and the ﬁgure shows the temperatures of the QGP at the LHC and RHIC are above 2Tc . In addition to this, the resultspresent that the suppression level at the LHC is smaller than that of RHIC, especially in the
low pT region. It is thought to be due to J/ψ recombination. The recombination is that ascreened c (c̄) quark binds another screened c̄ (c) quark because the number of c c̄ pairs at the28

LHC is larger than that in RHIC.

Figure 2.14: The pT dependent J/ψ suppression measured by ALICE and PHENIX and thetransport models [27].
A suppression is observed for other quarkonia, ψ(2S) (cc̄) and the Upsilon family (b b̄).
The temperatures of quarkonia melting depend on the state as shown in Tab. 2.2. The
quarkonia meltings act as a thermometer of the QGP.
Table 2.2: The dissociating temperature of quarkonia [26] .
State χc
ψ′
J/ψ
Υ′
χb
Υ
Tdis
≤ Tc ≤ Tc 1.2Tc 1.2Tc 1.3Tc 2Tc

3. Elliptic flow An elliptic ﬂow is a corrective motion of particles. The ﬂow is caused
by a high-density matter expansion due to its intrinsic pressure. Figure 2.15 shows theschematic view of an elliptic ﬂow. A shape of a reaction region is rugby-ball shaped when acollision is non-central. A high-dense matter having initial spatial anisotropy is produced in
the reaction region. Spatial anisotropy is made by a shape of a reaction region. A pressure
gradient of the dense matter in the direction of a reaction plane (the x − z plane) is larger
than a gradient in the y-direction. Finally, particles in the matter move and expand in the
direction of the pressure gradient as ﬂuid. It means that momentum anisotropy is produced
because particles are received momentum kick in the direction of the x−z plane by a pressure
gradient.
The anisotropy parameter v2 is written using the azimuthal direction of particles, φ, asdN∝ 1 + 2v2 cos 2(φ − ΦRP ).
dφ

(2.7)

Here, ΦRP represents the direction of a reaction plane in a given collision. Figure 2.16 is the√pT dependent v2 measured by PHENIX at RHIC in Au + Au collisions at sNN = 200 GeV.
29

Figure 2.15: The schematics of an elliptic ﬂow [28].
The triangles, the squares, and the circles are v2 of π± , K ± , and p(p̄). The solid lines are
relativistic hydrodynamics calculations for the elliptic ﬂow of pions, Kaons, and protons.
The hydro-dynamics calculations employ viscosity of zero and thermalization time of τ0 = 0.
If viscosity is large, a ﬂuid ﬂow is disturbed and v2 becomes small due to the viscosity anda calculation cannot replicate the experimental result. The comparisons of the experimental
results and the calculations suggest that ﬂuid extremely small viscosity is produced in thereaction region and becomes a thermal equilibrium state in a short time.

Figure 2.16: The elliptic ﬂow of proton, pion, and Kaon measured by PHENIX [29].

4. Thermal photons The QGP has thermal radiation because the QGP is a thermal equilibrium state. Then, a thermal photon measurement is a direct temperature measurementof the QGP. Thermal photons are components of direct photons. A direct photon is deﬁned
as a non-hadron decay photon. Other components of direct photons are prompt photons,
which are produced in initial scatterings, and photons produced by hadron interactions inhadron gas. A summation of direct photon components is measured experimentally. Thermal photon is the dominant component of the direct photon in the pT range of 1-3 GeV/c.
Figure 2.17 shows the direct photon pT distribution at ALICE in Pb-Pb collisions at
30

√

sNN = 2.76 TeV [30]. The red circles, the green diamond shapes, and the blue cross shapes
represent direct photon spectra for the centrality ranges of 0-20 % scaled by a factor 100,
20-40 % scaled by a factor 10, and 40-80 %, respectively. The solid lines and the shaded
bands are next-to-leading order perturbative-QCD calculations for the direct photon yield
in pp collisions scaled by the number of binary collisions for each centrality range. There areexcesses in the pT of 1-3 GeV/c. A ﬁtting the Boltzmann distribution, e−pT /T , to the excess
component provides an effective temperature of the QGP. The effective temperature at the
LHC is evaluated as 304 ± 11stat ± 40sys MeV. The temperature is high enough to create the
QGP.

Figure 2.17: The transverse momentum distribution of direct photons at ALICE [30].

2.2.4 Future researches
The presence of a QGP has ensured the evidence as shown in Sec. 2.2.3. Our understandingof the nature of the QGP should be improved to explain the QGP and phenomena in a hightemperature matter. The research phase has been moved to high-precise measurements of
the QGP property This sub-section describes the topics that must be addressed in the next
experiments.
1. Heavy quarks Heavy quarks (c and b quarks) are known as good probes for the QGP
study. Their masses are mc ∼ 1.3 GeV/c2 and mb ∼ 4.8 GeV/c2 , respectively. They are muchlarger than the QCD scale. Also, heavy quarks are not produced thermally because a typicaltemperature of the QGP is less than 1 GeV and several hundred MeV at most. Heavy quarks
formation times are calculated as tc ∼ 1/2mc ∼ 0.1 fm/c and tb ∼ 1/2mb ∼ 0.01 fm/c. They
are shorter than the QGP formation time 0.1-1 fm/c. Therefore, we can study the propertiesof the QGP using heavy quarks.
31

Low-pT heavy quarks move randomly (the Brown motion) in the QGP and loss theirenergy due to elastic collisions between them and partons of the medium. Kinematics of alow-pT heavy quark is described by the Langevin equationdp= −ηD (p)p + ξ
dt

(2.8)

where ηD is friction coefficient and ξ is shaking force. The momentum diffusion coefficient,Dp , and spatial diffusion coefficient, Ds , of the medium are written as
Dp = mq T ηD , Ds = T /mq ηD .

(2.9)

Kinematics variation from an initial state to a ﬁnal state includes information of Dp and Ds
of the QGP. High-pT heavy quarks lose their energy due to gluon radiation. Also, amounts ofenergy loss would decrease with increasing mass due to the dead-cone effect. It is consideredthat mass dependence of energy loss is ∆Eg > ∆Eu,d,s > ∆Ec > ∆Eb .
√Figure 2.18 shows the D meson RAA in 0-10 % central Pb-Pb collisions at sNN = 5.02 TeV
at ALICE and the heavy quark transport models. The black points and the orange crossshapes represent the averaged non-strange D meson RAA and the Ds+ RAA . The statisticaland systematic uncertainties are described by the error bars and the boxes. PHSD, TAMU,
and Catania are heavy quark transport models in the medium and coalescence. The Ds+ RAA
is larger than the non-strange D meson RAA for pT < 10 GeV/c as the model predictions.
However, the experimental uncertainties are too large to constrain the models. Therefore,
precise measurements of heavy quarks are essential to estimate the property of the QGP.

Figure 2.18: The comparison of D meson RAA measured by ALICE and the heavy quarktransport models [31].

2. Thermal di-leptons Thermal di-leptons are also produced by a QGP as same as thermal photons. Thermal photons are affected by the blue shift due to the system expansion.
Hence, temperature measurements via thermal photons have large uncertainties. On theother hand, thermal di-leptons do not have the effect of blue shift because thermal di-leptons
32are measured via invariant mass distribution. Therefore, they will provide precise measurements of the QGP temperature. Thermal di-leptons are the only unmeasured electromagnetic probe. Figure 2.19 shows the simulated invariant spectra of di-electrons in 0-10 %√central Pb-Pb collisions at sNN = 5.5 TeV [34]. The orange line represents the contributionof thermal di-electron and the red line is the thermal radiation from the hadronic phase.
The cyan line and the magenta line are decay di-electrons of hadrons and correlated cc̄, respectively. The black line is the summation of the components. The QGP thermal radiation
exceeds the hadronic thermal radiation in the mass range, Mee > 1 GeV/c 2 . Di-electrons
from c c̄ decay are the dominant background in the mass region. Therefore, measurement ofc c̄ decay di-electrons is crucial to extract the thermal di-electron component.

Figure 2.19: The di-electron invariant spectra in 0-10 % central Pb-Pb collisions at
5.5 TeV [34].

√

sNN =

3. Chiral restoration The chiral symmetry breaking is the hadron mass generation mechanism. The symmetry breaking is partially restored in a high-temperature matter, however,
the restoration has not been observed yet. The chiral symmetry restoration appears in modiﬁcation of light vector meson masses, e.g. ρ. A precise measurement of low mass di-lepton
spectrum is the power full way to search the chiral symmetry restoration in AA collisions
experimentally because leptons do not interact with partons in a QGP.

33

Chapter 3

Trigger and data acquisition system
Many missions have been addressed at LHC as described in Chap. 2. The experiments at the
LHC (ALICE, ATLAS, CMS, and LHCb) upgrade their sub-systems to achieve the missions.
The increase of center-of-mass energy is limited by the difficulty of a larger accelerator construction than the LHC. Their upgrade programs are described with focusing on their trigger
and data acquisition systems which are key technologies to make the breakthrough.
Largely, two strategies are proposed depending on their missions: a continuous readout
system and a hardware-trigger-based system. ALICE and LHCb employ continuous readout
systems. Their upgrade programs for Run 3 from 2022 are explained in the sections 3.1.1
and 3.1.2. ATLAS and CMS will upgrade their trigger systems. Their programs for Run 4
with the HL-LHC from 2027 are described in the sections 3.2.1 and 3.2.2.

3.1 Experiments with continuous readout systems
All collision event collection is ideal in large-scale hadron collider experiments. But computing performances and storage costs are not enough to allow any continuous readout systems.
Consequently, we had to select events with trigger systems to reduce data volume so far.
However, advances in technical tools in the last decades allow us to take all collision events.
Saving raw data, which mean directly transferred and not calibrated data from detectors, isimpractical even today. Therefore, an implementation of a continuous readout system withdata reduction is a challenging effort.
ALICE and LHCb can employ continuous readout systems in their experimental situations and their physics requirements need continuous readout systems. While their data
reduction strategies are different. ALICE needs the system to measure a wide range of transverse momentum and increase the amount of statistics for further study of the QGP properties. ALICE collects all tracks for various measurements with online calibration and tracking
using detector monitoring data. LHCb requires it for CP violation study via heavy ﬂavor
hadron decays because LHC pp collisions produce too many heavy quarks to detect with its
trigger system. The increase of trigger rates reached peaks of a few MHz. LHCb saves primary vertex data and tracks coming from heavy ﬂavor hadrons. Heavy ﬂavor hadrons decay
at points distant from a primary vertex.

34

3.1.1 ALICE
ALICE [32] is the experiment focusing on the heavy-ion program at the LHC. The following
measurements are the targets to building a greater understanding of a QGP:• QGP density via c and b quarks dissociated measurements• QGP temperature measurements via thermal di-leptons• Measurements of mass modiﬁcation of low mass vector mesons due to chiral symmetry
restoration.
A wide range of the particle momentum region needs to be covered with particle identiﬁcation for these measurements.
ALICE had collected physics data with the hardware-trigger-based data acquisition system (DAQ) [33] at a rate of 500 Hz in Runs 1 and 2. Figure 3.1 shows the architecture of the
ALICE DAQ for Runs 1 and 2. The system, called the central trigger processor (CTP), selects
the interaction events to meet the physics requirements. Information from triggering detectors is aggregated in the CTP. Then, the processor combines and synchronizes the trigger
information. The maximum readout rate was 500 Hz in minimum bias Pb-Pb collisions.

Figure 3.1: The architecture of the ALICE ALICE and trigger system [32].
The LHC increases its collision rate of Pb-Pb beams up to 50 kHz in Run 3 as described inSec. 1.2. The time projection chamber (TPC) used in Runs 1 and 2 had limited the readout
rate of 500 Hz due to a latency of the gating grid for fewer noise signals. The rate can beincreased up to 3 kHz. The readout rate of the inner tracking system (ITS), which is theinnermost tracking detector, is limited to up to 1 kHz. Hence, the ITS and the TPC must be
upgraded to install the continuous readout system. Minimum bias data in Run 3 will be 50
times larger than the data in Runs 1 and 2 [34]. The typical volume of raw data from the
sub-detectors is expected around 3.5 TB/s in the continuous readout. Storing the amount ofdata is hardly realized; therefore, ALICE implements the new DAQ, named the online-offline
computing system (O2 ) [40], to reduce the volume by online data processing.
3.1.1.1

Upgrade of central detectors

ALICE upgrades the sub-detectors to improve tracking accuracy and readout rate. Especially, replacement of the ITS and implementation of new readout boards for TPC are the35most important upgrades.
Inner Tracking System The ITS used in Runs 1 and 2 was composed of six cylindricallayers of silicon detectors. The ITS is replaced for a new ITS which consists of seven layersof silicon pixel detectors [35]. The CMOS monolithic active pixel sensor (MAPS) technology[36, 37, 38] is employed for the silicon pixel sensors, in order to obtain high spatial resolution
and reduce the material budget. The new ITS will improve the accuracy of primary vertex
and secondary vertex of heavy ﬂavor hadrons. The detection performance of low pT particles
will be also improved.
Time Projection Chamber The TPC [39] is the gas detector used for charged particle tracking and particle identiﬁcation (PID). The original MWPC based signal ampliﬁcation system
limited the trigger rate of up to 3 kHz. The TPC employs the gas electron multiplier (GEM)
technology for the readout electronics to realize the high readout rate at 50 kHz in Pb-Pb
collisions.
3.1.1.2

Online-offline computing system

The O2 is a new data taking and processing system. A data throughput from the ALICE subdetectors will reach 3.5 TB/s. It is not realistic to store the raw data in data storage. Then,the data volume is reduced with the online data process by calibration and tracking. The
online tracking must keep tracking accuracy as well as the offline tracking. It is the featureof the O2 .
Figure 3.2 shows the data ﬂow in the O2 framework. Firstly, raw data including physics
data and detector condition data are sent from the sub-detectors to FLPs which are server
computers. The FLPs perform calibration and masking, which means deletion of noisy data,using the detector condition data. This process reduces the data amount from 3.5 TB/s
to 500 GB/s. Then, the calibrated data are transferred from the FLPs to Event processor
nodes (EPNs) where tracking is performed. The data volume is reduced from 500 GB/s to
100 GB/s. Finally, the tracking data are saved on the data storage permanently.
Here, calibration and reconstruction for the TPC data are described as an example. The
TPC data throughput is evaluated around 3.4 TB/s of 3.5 TB/s [39]. Hence, reduction for
the TPC data is critical in the O2 . A drift velocity and a gain depend on the temperatureand pressure and the conditions are employed for online calibration and reconstruction.
Additionally, front-end electronics conﬁgurations such as inactive regions are important information on the calibration and reconstruction. Firstly, zero suppression, which delete data
below a threshold, and clustering using front-end conﬁgurations is performed in the calibration stage. Data which do not associated to any clusters are removed. The calibrated data
are sent to EPNs and reconstructed using a drift velocity and an effective gain.
3.1.1.3

Muon Forward Tracker

ALICE installs the new silicon tracker covering the forward pseudo-rapidity region of 2.5 <|η| < 3.6. It is the muon forward tracker (MFT) [41, 42]. The MAPS sensors used for the ITS
are employed for the MFT. The MFT physics motivations are measurements of heavy quarks,
thermal di-leptons, and mass modiﬁcation of light vector mesons due to chiral symmetry
restoration in the forward rapidity region. The rapidity dependence QGP study is crucial tounderstand the experimental results and to constrain models.
36

Figure 3.2: The O2 data ﬂow.
ALICE has measured muons in the forward region using the muon spectrometer [43, 44]. The tracking accuracy was not enough to disentangle prompt D mesons and displaced D
mesons due to muon multiple scatterings inside the hadron absorber. The multiple scatterings also prevented thermal di-muon measurement and high-precision measurement of
di-muon invariant mass spectrum in the low mass region. The MFT provides high-precision
measurements of muons with the muon spectrometer as well as the tracking accuracy by thecentral detectors.
The MFT readout system follows the O2 strategy because the MFT is the new detector.
The MFT DCS also follows the upgraded ALICE DCS strategy. The design of the MFT DCS
is my work.

37

3.1.2 LHCb
LHCb [45] is the experiment focusing on precise CP violation measurements via rare decaysof B and D mesons described in Sec. 2.1.2 to test the standard model. A large amount ofstatics is necessary for these kinds of precise measurements.
LHCb had employed the trigger-based readout system in Runs 1 and 2. However, thehardware hadronic triggers, named the Level-0 trigger (L0) trigger, used in Runs 1 and 2
have limited efficiencies in higher luminosity as shown in Fig. 3.3. The vertical axis indicates
the trigger yield and the horizontal axis indicates the luminosity. The black squares, the red
upward triangles, the green downward triangles, and the circles represent the trigger yieldsof ππ, φγ, Ψφ, and Ds K triggers, respectively. The yields of ππ, φγ, and Ds K triggers arelimited by the decision time of the triggers from the higher luminosity of around 3×1032 andthey prevent them to take more amount of statistics. Therefore, LHCb installs the hardware
trigger-less readout system, in order to collect more physics data.

Figure 3.3: The Level-0 hardware trigger efficiency vs the instantaneous luminosity [46].
LHCb employs a continuous readout system to overcome the trigger limitations. Figure
3.4 shows schematic views of the data ﬂow in Run 2 (left) and Run 3 (right). The triggerbased DAQ system was composed of an L0 and a software high-level trigger (HLT). The L0
reduces the event rate from the 40 MHz bunch crossing rate to the 1 MHz readout rate.
The trigger rates of hadrons, single/pair muon, and electron/photon are 450 kHz, 400 kHz,and 150 kHz, respectively. Raw data of triggered events are transferred to the HLT farm.
Partial reconstruction is performed using tracking information of the vertex tracker to remove events including di-muons and displaced tracks and vertices. The surviving events
are buffered to disks and performed calibration and alignment on the disks.
3.1.2.1

Detectors

LHCb upgrades its detectors in order to cope with the increased luminosity and crossing
rate of the LHC. Figure 3.5 describes the side view of the LHCb sub-detectors in Run 3.
Vertex detector The vertex locator (VELO) [49] is the detector surrounding the interaction
point for a primary vertex decision and tracking. The distance between the detector and38

Figure 3.4: The data ﬂow diagrams in Run 2 (left) and Run 3 (right) from Ref. [47].
the interaction point will get close from 5 mm to 3.5 mm. The distance will enable themto improve the interaction point measurements. The VELO employs the new CMOS silicon
pixel sensors to read out data at a rate of 40 MHz. The sensors will allow enhancing the
tracking precision and the reconstruction speed. The size and the number of sensors will be
55µm x 55µm and 41 million, respectively.
Tracking station The LHCb tracking system [48] will be composed of the upstream tracker(UT) and the scintillating ﬁber tracker. The upstream tracker will be installed between the
VELO and the magnet. The tracker consists of four layers of high granularity silicon microstrip planes. The other tracker is installed on the downstream side of the magnet. The
tracker will be composed of 2.5 m long ﬁbers and the readout electronics of silicon photonmultipliers.
PID detectors Two ring-imaging Cherenkov detectors (RICHs) [50] are installed for PID
covering the full momentum range of tracks in LHCb. The RICH 1 is installed between the
VELO and the dipole magnet and identiﬁes low momentum particles of from 10 to 65 GeV/c.
The aerogel radiator installed in the current RICH 1 is removed to improve material budget
and PID performance. The RICH 2 is installed downstream of the tracking stations andidentiﬁes high momentum particles of from 15 to 100 GeV/c. The readout electronics will
be replaced the commercial multianode photomultipliers (MaPMTs) to achieve the readout
rate of 40 MHz.
3.1.2.2

Trigger and data acquisition system in Run 3

The new DAQ system is based on the Run 2 DAQ system. For the Run 3 trigger strategy, theraw data are transferred from the sub-detectors to the HLT directly. Nominal data throughput is estimated at 4 TB/s and the data are processed in the online reconstruction system.

39

Figure 3.5: The side view of the upgraded LHCb detector [48].
Charged particles are reconstructed in the ﬁrst step of the HLT. Six steps are executed on
HLT1 for track and primary vertex reconstructions as sown in Fig. 3.6. Hits in the VELO arematched to form straight lines, which are called VELO tracks, loosely pointing towards thebeamline. Then, the VELO track is extrapolated to the trigger tracker (TT) with a straightline to form a track, called a upstream track. At least three hits in the TT are requiredaround the VELO track extrapolation. The TT can determine particle momentum with arelative resolution of 20 % and the momentum is used to reject low pT tracks. Matching oflong tracks with TT and the three stations (T-stations) reduces the number of fake VELO
tracks. A primary vertex is also reconstructed in the HLT ﬁrst step. Here, primary vertex
means a proton-proton interaction point. The primary vertex, which indicates a protonproton interaction point, is reconstructed by the VELO tracks to select displaced particles inthe HLT1. The data are reduced to 125-250 GB/s at a rate of 0.5-1.5 MHz in the ﬁrst step of
the HLT.
The reconstructed data are archived in the buffer storage. The storage volume is 10 PB
and can archive the processed data for two weeks. Then, the second step of the HLT performs offline quality reconstructions. The second step performs a full event reconstruction
for the data processed. The full event reconstruction has three items: the charged particles
reconstruction, the neutral particles reconstruction, and the particle identiﬁcation. The reconstructed tracks decaying from heavy ﬂavor hadrons and primary vertices are selected using decay topology of heavy ﬂavor hadrons and save in default. In addition to this, some full
event information are stored for further offline processing. The amount of data to 10 GB/s
are recorded in permanent storage.

40

Figure 3.6: The execution order of track and vertex reconstruction on the HLT ﬁrst step [51].

Figure 3.7: The reconstructed tracks on the HLT ﬁrst step [51].

3.2 Experiments with hardware-trigger based systems
Continuous readout systems are also ideal in ATLAS and CMS. However, current computing
performance and storage costs do not match their physics requirements. The estimated data
volume at ATLAS and CMS are too large to process them online with current technologies.
Accordingly, they will upgrade their trigger systems because their current trigger systems
have room for improvement. The trigger rates will become a factor of ten faster than thatof their current trigger systems. The upgraded trigger systems fully utilize the HL-LHC
potential because their physics goals can be accessed only with the HL-LHC bunch crossing
rate and luminosity as described in Sec. 1.2.1.
ATLAS and CMS aim at the same physics targets, the Higgs mechanism and SUSY particle search with higher precision with the HL-LHC, and have a mutually complementary
relationship. The Higgs boson mass is 125 GeV/c2 and the mass range of SUSY particles is
estimated as O(100) GeV/c2 −O(1) TeV/c 2 . Their decay products should have large transverse
momenta and/or large missing transverse energies. Therefore, ATLAS and CMS need various hardware triggers to select events that can produce a Higgs boson or any SUSY particles.
The selected events are saved permanently on storage for offline analysis.
41

Figure 3.8: The execution order of track and vertex on the HLT second step [51].

3.2.1 ATLAS
A toroidal LHC apparatus (ATLAS) [52] is one of the general-purpose detectors for probing
pp and AA collisions. ATLAS needs detectors:• electromagnetic calorimeter for electron and photon identiﬁcation,• hadronic calorimeter for measurements of missing transverse energy and jet,• charged particle tracker for charged leptons and heavy ﬂavor identiﬁcation,• muon tracker for high-precision muon momentum measurement.
ATLAS has a solenoid magnet, which covers the inner detector and provides 2 T, a barrel
toroidal magnet, which provides 0.5 T for the central muon detector, and endcap toroidal
magnets, which provide 1 T for the endcap muon detectors. Figure 3.9 shows the schematic
view of the ATLAS detector.
3.2.1.1

Detector upgrade toward Run 4

The upgrade program of ATLAS [54, 55] focuses on the Run 4 experiment with the HL-LHC.
The upgraded system is called Phase-II.
Inner tracker The current Inner Detector will be replaced by a new Inner Tracker, andthe Inner Tracker will be composed of the silicon Pixel Detector [56] and the silicon Strip
Detector [57] for charged particle tracking. Figure 3.10 shows the layout of the ATLAS Inner
Tracker. The Pixel Detector covering |η| < 4 is shown in red and the Strip Detector covering|η| < 2.7 is shown in blue.
The Pixel Detector is composed of ﬁve barrel layers and ﬁve endcap rings. The conceptof the "Hybrid Pixel Detector" is a base of the Pixel Detector. 3D sensors with a pixel size of
50 µm2 and 25 µm2 for the endcap and the barrel of the innermost layer and planar sensors
42Figure 3.9: The schematic view of the ATLAS original detector [53].
with a pixel size of 50 µm2 for the other layers are employed. The pixel sensors must havean efficiency of over 98.5 %.
The Strip Detector consists of four-barrel layers and six endcaps. Silicon micro-strip
sensors are employed. The maximum readout rate of the Strip Detector for complete eventsis 1 MHz.

Figure 3.10: The schematic view of the ATLAS Inner Tracker [57].

Calorimeter The liquid-argon calorimeter (LAr) [58] and the tile calorimeter [59] consistof the ATLAS calorimeter system. The upgrades for the calorimeters will be replacements ofthe electronics for a 40 MHz readout and will provide full granularity data.
43

The LAr calorimeter consists of the LAr electronic barrel, the LAr electromagnetic endcap, the LAr hadronic endcap, and the LAr forward.
The Tile calorimeter is composed of the central parts called long barrel (LB) and theforward parts called endcap barrel (EB).

Figure 3.11: The schematic view of the LAr calorimeter [58].

Figure 3.12: The schematic view of the Tile calorimeter [59].

Muon system The ATLAS muon system in Phase-II [60] is composed of the three layersof resistive plate chamber (RPC) (|η| < 1.05), the three or four layers of thin gap chambers(TGC) (1.05 ≤ |η| < 2.4), and the new small wheel (NSW) (1.3 < |η| < 2.4).
Hit information of the RPC and the TGC is used for muon trigger information. Also,
muon tracks are measured by the RPC and TGC. The NSW consists of small-strip TGC and44

micro-mesh gaseous structure chambers. The wheel is used for triggering and precision
tracking.
3.2.1.2

Trigger and Data Acquisition system in Run 4

ATLAS employs the upgraded hardware trigger and DAQ, called TDAQ, toward the Phase-II
experiment with the HL-LHC [61] . ATLAS will install a hardware-based Level-0 trigger (L0)to achieve the physics goals.
Table 3.1 shows the representative L0 trigger menu. HT means a scalar sum of jet pT in
the table. The trigger system will be upgraded to achieve the 1 MHz trigger rate with thetrigger menu.
Table 3.1: The representative Level-0 trigger menu in Phase-II experiment [61].
Planned HL-LHC
Offline pT
L0 RateAfter Regional Event Filter
Threshold [GeV][kHz] tracking cuts [kHz]Rate [kHz]Trigger Selection
isolated single e
22
200
40
1.5
isolated single µ
20
45
45
1.5
120
5
5
0.3
single γ
forward e
35
40
8
0.2
di-γ
25,25
20
0.2
10,10
60
10
0.2
di-e
di-µ
10,10
45
10
0.2
10,10
45
10
0.2
e−µ
single τ
150
3
3
0.35
di-τ
40,30
200
40
0.5
single b-jet
180
25
25
0.35
400
25
25
0.25
single jetlarge-R jet
300
40
40
0.5
65(2-tags)
100
20
0.1
four-jet (w/ b-tags)
four-jet
100
100
20
0.2
HT
375
50
10
0.2
miss
210
60
5
0.4
ET
VBF inclusive
2 × 75 w/ (∆η > 253350.5&∆φ < 2.5)
B-physics
50
100.5
Supporting Trigs
100
40
2
Total
1066
338
10.4
Figure 3.13 shows the schematics of the TDAQ in Phase-II. The detectors used for triggering are the calorimeters and the muon system. The event data of the trigger detectors aretransmitted to the L0 system. The L0 system decides the corresponding event data must be
saved permanently or not at a rate of 1 MHz and a maximum latency of 10 µs according to
the trigger menu.
A calorimeter trigger, named L0Calo, is based on the Phase-I calorimeter trigger system.
Both LAr and Tile calorimeters are used as input for the calorimeter trigger. The calorimeter45

Figure 3.13: The design of the TDAQ system in Run 4 [61].
trigger system selects the events producing triggering signals of an electron, photon, tau, jet,and E missT . The trigger signal is transferred to the global trigger system.
The muon trigger works for muon signals with pT > 20 GeV/c for single-lepton trigger
and pT > 10 GeV/c for multi-lepton trigger at a rate smaller than 40 kHz. A momentum
resolution of the muon trigger will be 5 % for 20 GeV/c muons using the muon tracks in the
MDT. The muon trigger system sends a trigger signal to the global trigger and the central
trigger processor.
The accepted event is aggregated at the global trigger. The global trigger complements
the calorimeter trigger menu with high-granularity energy data coming directly from thecalorimeters. Offline-like algorithms. In detail, the following processes are performed: topological clustering, lepton isolation, calorimeter-based pile-up suppression, jet ﬁnding, exotic
object selection, and identiﬁcation of electron, photon, and τ lepton are performed by the
Global Trigger.
The central trigger processor (CTP) makes a ﬁnal decision in the L0 trigger acceptanceor rejection using the inputs from the muon trigger system and the global trigger. An accept
46

signal will be transferred from the CTP to the sub-detectors.
The DAQ works for data aggregate and saves into the storage when the CTP decides thetrigger acceptance. The data from sub-detectors are processed by the DAQ and saved into
permanent storage.
The Event Filter selects the events according to the trigger menu at a rate of 10 kHz.
The Event Filter is composed of the processor farm and the hardware-based tracking for thetrigger (HTT). The HTT performs an initial event selection based on the combined L0 trigger
information.

47

3.2.2 CMS
CMS [62] is the other of the general-purpose detectors at the LHC. The detector conceptsof CMS and ATLAS are different. The CMS detector design and layout aim to precise measurement of the muon momentum. CMS employs a superconducting solenoid magnet which
generates a magnetic ﬁeld of 4 T and a bending power of 12 Tm for high-precision measurements of muons. Figure 3.14 shows the detector schematics in Run 1.

Figure 3.14: The schematic view of the CMS detector in Run 1 [63].

3.2.2.1

Upgrade toward Run 4

CMS has an upgrade program toward the Run 4 experiment with the HL-LHC. The program contains the new detector installation and the upgrade of the detectors and the online
system. The upgraded detector is called the Phase-2 detector.
Tracker The CMS tracker system [64] in Run 4 is composed of an inner tracker (IT) andan outer tracker (OT) and located innermost layer of the detectors. The IT is a silicon pixel
detector and the OT is a silicon strip and macro-pixel detector. The pseudo-rapidity rangeof the tracker is extended to |η| = 3.8.
The tracker is required to have high occupancy below the permille level in the IT and thepercent level in the OT to identify the pile-up events.
Calorimeter CMS has the electromagnetic calorimeter (ECal) and the hadron calorimeter (HCal) [65, 66]. The ECal is composed of a barrel part and two endcaps. The hadroncalorimeter (HCal) is composed of a barrel part, two endcaps, an outer part, and a forward
part.

48

The barrel calorimeter indicates the barrel parts of both calorimeters and the endcap
calorimeter means the endcap parts of both calorimeters. The ECal is composed of 75,848
lead tungsten scintillating crystals. For the HCal, the HCal barrel and the endcap are composed of a brass absorber and plastic scintillator. The HCal forward is a Cherenkov calorimeter.
MIP Timing Detector The ability to reconstruct the timing of most of the ﬁnal state particle provides further discrimination of the interaction vertices beyond spatial tracking algorithms. A 30 ps timing resolution offsets the performance degradation due to the event
pileup experienced in several observables. Global event timing can be achieved by a newtiming detector sensitive to minimum ionizing particles (MIPs). The new detector installed
in long shutdown 3 (2025 - mid-2027) is named the MIP timing detector [67, 68] and locatedbetween the tracker and the ECal. The MIP timing detector is composed of the barrel partand the endcap part. The MIP timing detector provides timing for individual tracks crossingit.
Muon System The muon detector [69] is the main detector in CMS. The current muon system is composed of the drift tube (DT) chambers, the cathode strip chamber (CSC), resistive
plate chamber (RPC). The current muon detectors are upgraded toward Phase-II, furthermore, the new RPC detector called improved resistive plate chamber (iRPC) and the gas
electron multiplier (GEM) detector will be installed in the pseudo-rapidity range of 1.8 <|η| < 2.4 and 1.6 < |η| < 2.3 respectively.
The muon system is also composed of the barrel region and the endcap regions. The
barrel drift tube chambers cover the pseudo-rapidity range of |η| < 1.2 and the endcap
cathode strip chambers cover the pseudo-rapidity range of 0.9 < |η| < 1.2.
3.2.2.2

Data Acquisition System in Run 4

CMS employs Level-1 trigger (L1) trigger [71, 72] and high-level trigger (HLT) [73, 74] trigger toward Run 4. Table 3.2 shows the representative trigger menu for the CMS Phase-II
experiment. HT means a scalar sum of jet pT in the table. CMS develops the trigger system
for the trigger menu.
Figure 3.15 shows the architecture of the L1 trigger of CMS.
The trigger input detectors are the calorimeters, the muons system, and the tracking
system. The estimated rates of the L1 trigger and the HLT are estimated 500 - 750 kHz.
Calorimeter Trigger The calorimeter trigger uses the combined information coming fromthe barrels of the ECAL and the HCAL, the endcap high-granularity calorimeter (HGCAL),
and the hadron forward calorimeter (HF) to produce similar trigger performance. In Fig. 3.15,
the barrels of the ECAL and the HCAL are named as the barrel calorimeter (BC). Electrons,
photons, jets, hadronically decaying taus, and various energy sums are calorimeter trigger
objects. The barrel calorimeter trigger (BCT) combines the information of the ECAL and the
HCAL. The trigger information of the BCT and HF are transferred to the global calorimeter
trigger (GCT). The GCT sends the HF and the BCT information to the correlator trigger (CT).
And then it combines the BC, the HF, and HGCAL information to calculate the trigger objects and send them to the global trigger. Data transfer from the GCT to the CT is performed49

Table 3.2: The representative Level-1 trigger menu in the Phase-II experiment based on
Ref. [72].
L1 Trigger seeds

Single TkMuon
Double TkMuon
Single TkElectron
Single TkIsoElectron
Double TkElectron
Single TkIsoPhoton
Double TkIsoPhoton
Single CaloTau
Double CaloTau
Single Jet
Double Jet
HTETmissOfflineThreshold(s)at 90% or 95%(50%)
[GeV]
22
15,7
36
28
25,12
36
22,12
150(119)
90,90(69,69)
180
112,112450(377)200(128)

Rate< PU >= 200

Additional
Requirement(s)

[kHz]
12
1
24
28
4
42
50
21
25
70
71
11
18

[cm, GeV]|η| < 2.4
|η| < 2.4, ∆z < 1|η| < 2.4
|η| < 2.4, ∆z < 1|η| < 2.4
|η| < 2.4
|η| < 2.4
|η| < 2.1
|η| < 2.1, ∆R > 0.5|η| < 2.4
|η| < 2.4, |η| < 1.6
jets: |η| < 2.4, pT > 30

Objects
plateau
efficiency
[%]
95
95
93
93
93
97
97
99
99
100
100
100
100

within 5 µs and transfer from the GCT to the global trigger is performed within 9 µs to keep
the bunch crossing rate.
Muon Trigger The muon trigger is employed to identify muon tracks. The trigger uses theinformation of standalone muon tracks reconstructed in the muon detector and matchingmuons from the L1 track ﬁnder. The trigger uses all muon detectors of the drift tube (DT),the resistive plate chamber (RPC) including the improved resistive plate chamber (iRPC),
cathode strip chamber (CSC), and the gas electron multiplier (GEM) detector.
The muon trigger system has three track ﬁnders each pseudo-rapidity regions: the barrel
muon track ﬁnder (BMTF) (|η| < 0.8), the overlap muon track ﬁnder (OMTF) (0.8 < |η| <1.2), and the endcap muon track ﬁnder (EMTF) (1.2 < |η| < 2.4) because the detector technologies and conditions are different. Then, the outputs of the track ﬁnders are transmitted
to the global muon trigger which reconstructs global muons and tracker muons. The global
muon trigger also receives signals from the barrel layer-1.
Global Track Trigger The global track trigger is a newly installed trigger system in the L1.
It builds high-level objects out of the tracks within the full outer silicon tracker volume. The
inputs of the global track ﬁnder come from the track ﬁnders. The Global Track Trigger plays
a role to build high-level objects out of the tracks.
Correlator Trigger The object of the correlator trigger system is to aggregate inputs fromall upstream systems and optimally combine the information from the various sub-systems
to achieve the best possible trigger performance for the most challenging physics topologies.
The correlator trigger is composed of two particle-ﬂow layers as shown in Fig. 3.15. The
50

Figure 3.15: The architecture of the CMS trigger [72].
ﬁrst layer creates particle-ﬂow candidates, which the PUPPI [75] algorithm deﬁnes, and thecreated candidates are transferred to the second layer. The second layer reconstructs physics
objects, such as electrons, jets, and ETmiss .
Global Trigger The trigger menu is implemented on the global trigger. The global trigger
processes the inputs from the upstream trigger systems and decides the trigger type basedon the trigger algorithms. The outputs of the global trigger are transmitted to the Phase-II
Timing and Control Distribution.

51

Chapter 4

Summary and discussion
The modern particle physics has progressed with the advancements of technologies, especially accelerators. However, it is very hard to make a signiﬁcant increase of center-of-massenergy by making an accelerator larger. The only achievable accelerator improvement is anincrease of a luminosity for the next decade.
New trigger and data acquisition systems are mandatory to follow the increase of theluminosity at the LHC. ALICE and LHCb employ continuous readout systems. A continuous readout system takes all collision events without any hardware triggers. Technologicaladvances in the last decade enable us to realize continuous readout systems. Although, raw
data recording is unattainable with the current technologies. For that reason, data reduction
by calibration and reconstruction is a key factor in a continuous readout system. ALICE
requires all information in Pb-Pb collisions at 50 kHz for the QGP property study. The
amount of raw data from sub-detectors is estimated as 3.5 TB/s. ALICE reduces the dataamount from 3.5 TB/s to 100 GB/s by online calibration and reconstruction using detector
conditions. While, the hardware trigger rate of LHCb used in Runs 1 and 2 was 1 MHz
by the decision time of the hardware trigger and great improvements of the trigger system
could not be expected technically. Therefore, LHCb need the continuous readout system tocollect all collision events in pp collisions at a rate of 40 MHz CP violation measurements
via rare decays of heavy ﬂavor hadrons. In the situation, the data volume is estimated as
4 TB/s. LHCb reduces the data volume by online calibration, reconstruction, and selection.
The system records primary vertices and tracks of heavy ﬂavor decay products using decay
topology of heavy ﬂavor hadrons. Thereby, the amount of data are reduced from 4 TB/s
to 10 GB/s by the processes. On the other hand, ATLAS and CMS improve their hardware
trigger systems. Their upgrades concentrate on the study of the Higgs mechanism and newparticle searches with the HL-LHC. The data volumes of ATLAS and LHCb with the HL-LHC
are estimated as 200 TB/s and 336 TB/s, respectively if they employ continuous readouts.
Their data amounts are too large for to employ continuous readout systems with moderate
efforts. Additionally, their trigger system have room for improvement and the rates of the
upgraded trigger systems will be larger by a factor of ten than that of their current systems
with maximum efforts. Therefore, the trigger system upgrades are the reasonable solutions.
However, their trigger rates are getting close to the limit. All collision event recording isideal in any hadron collider experiments even ATLAS and CMS like experiments. Further
technological innovations in future will allow us to employ continuous readout systems inany collider experiments and ATLAS and CMS will move from the trigger systems to continuous readout systems. The features of the new trigger and DAQ are summarized as shown52

on Tab. 4.1.
Table 4.1: Comparison between the strategies of the each experiments.
ALICE
ATLAS
CMS
LHCb

Hardware trigger
×""×

Software trigger
×"""

Online tracking"
××"

Other features
All information recording
1 MHz trigger
750 kHz trigger
Online event selection

We should aim for continuous readout systems and ALICE is one of the frontiers in thisﬁeld. The O2 requires the new control and monitoring scheme to realize the online calibration and reconstruction using detector condition data. The new control and monitoring
scheme is demonstrated in the control system for the muon forward tracker (MFT) newly
installed in the forward rapidity region. It is a model case for the O2 and the new scheme.

Figure 4.1: The cross-section and the generation rate vs the jet ET or particle mass with the
LHC luminosity and energy [76].

53Part II

Detector control system for the muon
forward tracker

54

Chapter 1

Detector control system at ALICE
Dada reductions by online calibration and reconstruction with data conditions are crucial in
the ALICE O2 project. Raw data which are composed of physics data and detector conditions
are transferred in the same data segments from the sub-detectors to the processors for effective calibration. Raw data of 3.5 TB/s are reduced by a factor of seven in the calibration step.
Previously, the DAQ and the control system were completely different systems and physics
data and detector conditions were transferred separately because calibration and reconstruction were performed offline. However, the DAQ and the control system become one ﬂesh in
the O2 . Therefore, a new detector control and monitoring scheme is required to achieve thephysics goals with the O2 .

1.1 Basics of a detector control system
The detector control system (DCS) is responsible for detector operation, monitoring, safety,
and reliable experiment. A new control and monitoring scheme is necessary to implement
the continuous readout system with data reduction. The basic concept of a DCS and the new
DCS scheme are described in this section.
A DCS is based on a distributed control system. Distributed control systems are commonly used in detector control systems and accelerator control systems because the distributed system has some advantages. For instance, simpliﬁed hard-wiring, scalability, andﬂexibility. In the distributed system, computers assigned to constituent devices, are connected via Ethernet as shown in Fig. 1.1. We can add and exclude devices easily connecting
and disconnecting Ethernet cables. In case of some failures, the distributed system allows
experts to separate the failure devices from the entire system.
A DCS is composed of three layers: a supervision layer, a process management layer,
and a ﬁled management layer. Figure 1.2 shows the DCS layers. The supervision layer iscomposed of software components, e.g. supervisory control and data acquisition (SCADA),
algorithms for control, and a graphical user interface (GUI). A SCADA provides tools for a
GUI which shows operation panels and parameters on displays. Some algorithms run ona SCADA system. Operators work their tasks using a SCADA. The process management
layer is comprised of computers and hardware elements. programmable logic controller(PLC) and power supply systems are in the process management layer. Detector front-end
electronics and sensors are the elements of the ﬁeld management layer.
SCADAs play an important role in the DCS. The SCADA visualizes control commands ofthe system detector status collected via the network. Operators and detector experts han55

Figure 1.1: The schematic view of the distributed control system.

Figure 1.2: The image of the DCS layers.
dle the detectors with the SCADA installed in the supervision layer. Ethernet connects the
SCADA in the supervision layer and the SCADAs in the process management layer as the distributed system. The SCADA commonly used at CERN is WinCC open architecture (WinCC
OA) [77] produced by SIEMENS.
A ﬁnite state machine (FSM), also called an automaton, is an abstract machine. The FSM
deﬁnitions are as follows:• It must have some states;• It transits the states in response to inputs;• It may output upon its state and input.
The FSM is designed based on detector behaviors in the DCS. The sub-detectors are operated
by commands corresponding to a state implemented on the FSM. The commands can prevent
unexpected operations by operators.
A safety system is also managed by the DCS. The safety system consists of a softwareinterlock and a hardware interlock. The software interlock is triggered with minor issues
such as power supply system channel trip. The software interlock is based on an FSM. When56

an element state is an error, the software interlock turns off relevant elements. The hardwareinterlock is caused by major issues, for instance, signiﬁcant overheat of the detector andcooling system failure The hardware interlock is based on PLCs, on which alarm handlingand automated actions are programmed detector by detector. When a major issue happens,
the hardware interlock stops all ALICE sub-detectors and data taking.

1.1.1 New control and monitoring scheme
The ALICE DCS also plays an important role in the O2 strategy, because online calibration
and reconstruction require the DCS data such as detector temperatures and voltages. The
ALICE DCS needs to introduce a new control and monitoring scheme to achieve the physics
goals with the O2 .
In the system used in Runs 1 and 2, physics data and detector conditions were transferred
separately in different lines because calibration and reconstruction were performed offlinefor physics data saved on the permanent storage using detector conditions. However, the O2
executes calibration and reconstruction online to reduce the amount of continuously read
physics data before physics data are saved on permanent storage. Especially, calibration iscarried out on the FLPs right after data taking. Detector conditions need to be delivered withphysics data simultaneously for online calibration. The ALICE low-level front-end (ALF),
the front-end device (FRED), and the ALICE datapoint service (ADAPOS) are developed as
the new ALICE DCS scheme to follow the O2 strategy [78, 79].
Figure 1.3 shows the schematic view of the ALICE DCS data ﬂow. The raw data, including physics data and the DCS data, are transferred in the same data paths, for which giga-bit
transceiver (GBT) developed by CERN is employed, from the detectors to the FLPs. Calibration is performed on the FLPs and then the raw data are divided into the physics data
and the DCS data on the FLPs. Then, the physics data are transferred to the EPNs and the
DCS data are transferred to the SCADA via the FRED. The DCS data are stored on the DCS
database. The ADAPOS publishes the corresponding DCS data from the DCS database to
the EPNs and the EPNs perform reconstruction using received DCS data.

Figure 1.3: The DCS data ﬂow in the new ALICE DCS framework [78].

ALF-FRED architecture The FRED is a computing server installed between the FLPs andthe SCADA communicating with Ethernet. Operation commands written in a high-level57

language are translated into command sequences written in a low-level language for the
GBT slow control adaptor (GBT-SCA).
Also, monitoring data written in hexadecimal sentences are converted into numericalvalues. The ALF is software for data exchange between the FLP and the FRED and installedon the FLP.
ADAPOS ALICE datapoint service (ADAPOS) is a new data transfer system in the DCS
data facility. The EPNs need the detector condition parameters collected by the DCS to perform track reconstruction. The ADAPOS publishes the conditions from the DCS database to
the EPNs, when the detector conditions are updated.
The new DCS for the sub-detectors must be designed and developed based on the newcontrol and monitoring scheme to realize the continuous readout system with online calibration and reconstruction and achieve the physics impact.

1.2 Scope of this part
The ALICE DCS upgrades its scheme as a part of the O2 to achieve the ALICE physics goals
because he new ALICE DCS is a crucial scheme to realize online calibration and reconstruction using detector conditions. The MFT is the new detector and the DCS for the MFT isﬁrstly developed based on the new ALICE DCS scheme.

58Chapter 2

Muon forward tracker
ALICE measured muon tracks with the muon spectrometer in the forward region. The results in Run 1 showed that more precise measurements in low-pT down to 0.5 GeV/c anddisentanglement of heavy ﬂavor hadrons are needed for further study of the QGP properties. The MFT is the new silicon pixel detector to improve the tracking accuracy of muons.

2.1 Muon measurements at ALICE
Muon measurements were performed with the ALICE muon spectrometer in the forward
rapidity region (2.5 < |η| < 4) and many brilliant results were reported. However, the resultsfrom Run 1 data also showed that we need more precise measurements of low-pT heavy
quarkonia, heavy ﬂavor hadrons, and low invariant mass di-muons for the understanding of
the QGP properties.
The hadron absorber is set between an interaction point and the muon spectrometer toreduce background signals, such as electrons and hadrons. The absorber has a length of
4.13 m and is composed of carbon and concrete (~10 λint , ~60 X0 ). Muon multiple scatterings in the hadron absorber prevented high accuracy muon tracking.
To improve the accuracy, the new silicon detector, named the MFT, is installed between
an interaction point and the hadron absorber. The MFT covers the forward pseudo-rapidity
range of 2.5 < |η| < 3.6 The MFT tracks muons before traversing the absorber and matching of muon tracks reconstructed by the MFT and the muon spectrometer respectively will
improve the accuracy of primary vertex reconstruction.

2.2 Detector setup
The MAPS technology [36] silicon pixel sensors, named ALPIDE [37, 38], are employed for
the MFT because the MAPS technology have a lot of advantages, in terms of power consumption, readout speed, and radiation tolerance. In addition, noise-less signals are collected because the readout and analog-to-digital conversion are performed in parallel. The ALPIDEs
realize a spatial resolution of 5 µm. The size of an ALPIDE chip is 1.5 × 3 cm2 and the pixel
pitch is 27 × 27 µm2 . 936 chips are implemented on the MFT.
Figure 2.1 shows the three-dimensional image of the MFT. The MFT consists of two halfcones, called the top and the bottom. The half cones have the same structure. Five half
discs, which is composed of two detection planes, constitute the half cone. The discs are59

Figure 2.1: The three-dimensional image of the MFT [82].
numbered zero to four from the side close to the interaction point. One detection plane isplaced on the vertex point side and the other is placed on the absorber side. A detection
plane contains 12 to 17 ladders, which are ﬂexible printed circuit boards with two to ﬁve
ALPIDE chips. A set of two to ﬁve ladders consists of a zone, which is a minimum unit forreadout, to save connection lines as shown in Fig. 2.2. The line from the readout unit (RU)
links up to a single zone. A power supply unit (PSU) and PSU mezzanine cards are placed
between half-disc 3 and disc 4. The PSU houses DC-DC converters to provide stable power
and to prevent voltage drops. There are the GBT-SCA on the mezzanine cards for the DCS
data exchange.

Figure 2.2: The example of the zones of the half detection plane [82].
The MFT frontend electronics (FEE) cards are based on a ﬁeld programmable gate array(FPGA) system, calling RU. The RUs enable to read raw data including physics data and
DCS data. One RU is assigned to one zone and reads the raw data from the zone. The RU
conﬁgures the ALPIDE chips on the corresponding zone. A GBT-SCA is used for the RU
control and conﬁguration.

60

Chapter 3

Design of the detector control system
The architecture of MFT DCS is based on the new ALICE control and monitoring scheme toemploy the O2 . The control system is composed of a power supply system, a cooling system,
and a control & readout system. Modules produced by CAEN are employed as the power
supply system for the MFT. For the cooling system, a water cooling system is employed.
In addition to this, a ventilation system is used as the detector cooling system. The watercooling and ventilation systems are managed by the CERN cooling and ventilation group.
The MFT is operated and monitored via the FSM which has a tree structure based on thedetector structure including the RUs, the power supply system, and the cooling system. The
FSM also contains a software interlock system which handles minor issues such as excess ofa temperature. Moreover, the hard-wired safety system, named a detector safety system, isemployed to handle major issues e.g. a failure of the cooling system.

3.1 Overview
The DCS for MFT is designed based on the upgraded ALICE DCS strategy and framework.
WinCC open architecture (WinCC OA) and a joint control project (JCOP) framework [80],are applied for the MFT DCS software because they are provided by CERN and officially
supported tools. The MFT DCS has a distributed structure composed of three systems: apower supply system, a cooling system, and a control & readout system as shown in Fig. 3.1.
Two steps interlock systems, namely the software interlock and the hardware interlock, areimplemented as the safety system.

3.2 Power supply system
The power supply system provides low-voltage power of a few volts to the MFT and the
RUs. The ALPIDE needs two lines of 1.8 V for analog and digital parts and a bias voltageof -3 V for the silicon sensor via the PSUs, which house several DC-DC converters, in orderto prevent voltage drop. The distance between the detector and the power supply system isaround 40 m. The PSU also provides 1.8 V power to the GBT-SCA and readout unit (RU).
The system manufactured by CAEN [81] is employed for the MFT power supply system
as shown in Fig. 3.2. An SY4527 is a mainframe to house two branch controllers, numbered
A1676A, and allows the entire power supply system from WinCC OA via Ethernet. The
controllers are needed for the embedded assembly system (EASY), which is the magnetic
61

Figure 3.1: The schematic view of the MFT devices [82].
ﬁeld and radiation tolerant power supply system. Two EASY systems are implemented in
the MFT DCS. One supplies power to the PSUs and the other supplies power to the RUs. FourEASY3000 crates powered by four A3486 house twelve A3009 boards and two A3006 boards.
A3486 is a 3-phase 400 Vac to 48 Vdc converter designed for the EASY implementation.

Figure 3.2: The architecture of the MFT power supply system [82].

3.3 Cooling system
A leak-less water cooling and an air ventilation system are employed for the MFT detector.
The RUs are cooled by the water cooling system. Figure 3.3 shows the setup of the watercooling system for the MFT. The pressure value of the water cooling system is 0.3 bar since
the pressure is lower than the atmospheric pressure so as to avoid water leaks. The nominal
62

temperature ranges of inlet water to the MFT and the RUs are 18–20 degrees Celsius and
18–23 degrees Celsius, respectively.
The air cooling system guarantees the temperature and humidity inside the detector volume with the ﬂow of dry and cool air. The air temperature is 20 degrees Celsius and thehumidity is 35 %. The parameters of both cooling systems are monitored by the DCS andused for inputs of the interlock system. The CERN ventilation group manages the coolingsystems.

Figure 3.3: The water cooling system for the MFT detector and the readout units [82].

3.4 Control and readout system
The MFT components are operated and monitored via the ALF-FRED and FLP. One FRED
and 40 FLPs with two CRUs each are implemented in the system for raw data process and
DCS data transfer. The components are 80 RUs, four mezzanine boards, four PSUs, and 936
ALPIDEs in total. The RUs and the mezzanine boards house the GBT-SCA chips for conﬁguration and monitoring of the RUs and of the ALPIDEs Temperature sensors are mounted on
the ALPIDEs, GBT-SCAs, the mezzanines, the half-planes, the RUs, and the FPGAs on the
RUs.

3.5 Control scheme
The MFT is operated via the FSM. The FSM has a tree structure based on the MFT hardware
structure as shown in Fig. 3.4. A control unit is a conceptual classiﬁcation to control andmonitor smaller structures of the detector effectively. A detector unit is an actual device andmust have some states even if states can be OK and ERROR only. We can control and monitor
the whole detector equipment from the top node, named MFT. Commands are transferredfrom the upper nodes to the lower nodes. States of the device units are referred by thecontrol units just above the device units.

63

Figure 3.4: The tree structure of the MFT control system [82].

3.6 Safety system
A software interlock system and a hardware interlock system are employed as the safetysystem for MFT. Minor issues are handled by the software interlock and problems, which
the software interlock cannot take care of.
The software interlock is implemented on the FSM. FSM outputs stop the relevant power
supply channels when a detector element parameter overs a threshold. Temperatures of the
GBT-SCAs, the half-planes, the RUs, the FPGAs on the RUs, the mezzanine boards, and the
ALPIDEs are monitored. FSM turns all channels of the power supply system if one of theﬂows or the humidity of the ventilation air or temperature of a half-disc shows an abnormal value. In addition to interlock triggering the temperature and the air aberrations, thesoftware interlock system triggers communication loss between WinCC OA and the FRED
and/or the FLP and between WinCC OA and the power supply modules.
The hardware interlock design for MFT triggers communication loss between WinCC OA
and the CAEN mainframes and excessive over the temperature of the detector. Any troubles
with the water cooling system are handled by the hardware interlock.

Figure 3.5: The DCS data ﬂow for the MFT [82].

64Chapter 4

Conclusion
Recording of all collision events is ideal in collider experiments. Recent technological improvements allow us to take all collision events, nonetheless, saving of data without any
modiﬁcation is unrealistic. For that reason, data reduction by calibration and reconstruction
is crucial in case of a continuous readout system employment.
ALICE and LHCb employ continuous readout systems. The online computing system
of ALICE reduces the data amount by online calibration and reconstruction using detector
condition data. It records tracks as much as possible in Pb-Pb collision events. The LHCb
system selects tracks by the decay topology of heavy ﬂavor hadrons in a whole pp collisions.
On the other hand, ATLAS and CMS, whose programs concentrate on data taking with thehigher luminosity, improve their hardware trigger systems, expressly the trigger rates, because it is more challenging for them to have continuous readout systems. Additionally, thefaster hardware triggers match their physics requirements with reasonable efforts to record
their interested events. The extremely larger data volumes taken by ATLAS and CMS thanthat of ALICE and LHCb prevent them to take a whole of pp collisions. However, the trigger
rates of their upgraded trigger systems approach the technical limitation continuous readout systems can be the best choice for any experiments. Further technology innovations willallow to record all collision data with continuous readout systems even with much higher
luminosity.
A continuous readout system is the future direction for hadron collider experiments.
ALICE leads the ﬁeld of continuous readout systems. ALICE reduces the data volume bycalibration and reconstruction with detector conditions. The control and monitoring system for sub-detectors and the physics data processing system were separated. However, raw
data including physics data and detector conditions need to be transferred in the same data
stream from sub-detectors to processors for effective data reduction. Physics data calibration is performed using the detector conditions e.g. temperatures and voltages and front-end
electronics conﬁgurations such as inactive regions on the processors. Accordingly, the calibration and the reconstruction reduce the data volume by a factor of seven a factor of ﬁve,
respectively. The new detector control and monitoring scheme is required to realize theonline data reduction.
The new detector control system is implemented and demonstrated for the MFT, which
is newly installed in the forward pseudo-rapidity region, from scratch. The control system iscomposed of the power supply system, the cooling system, and the communication system
which is the new scheme. It is the ﬁrst control system following the new control and monitoring scheme. The new control scheme is a model case for a continuous readout system and65online data reductions.
The control system is made a ﬁnal adjustment toward the next Run and a pilot run isperformed in 2021. A pilot run is a performance test with proton beams without accelerating
at a 600 Hz trigger rate. It is conformed that the MFT and the new readout system including
the new control and monitoring scheme work correctly. The ALICE Run 3 experiment will
start in this year. The new ALICE will progress particle physics.

66

Acknowledgment
First of all, I express my sincere appreciation to my supervisor, Prof. K. Shigaki providing
support for my research activities in Hiroshima and at CERN. I could join the MFT groupand enjoyed the activities with his guidance. I express my gratitude to Assoc. Prof. Y. Yamaguchi. He had a lot of helpful advice and support for my thesis work. I greatly thankcolleagues of the MFT group. I am grateful to especially Dr. G. Batigne, Dr. S. Panebianco,
Dr. G. Martinez, and Dr. R. Tieulent for their support of my research activities, also ﬁnancially, at CERN. I appreciate colleagues of the ALICE DCS group, especially Dr. P. Chochulaand Dr. O. Pinazza. I learned the basics of the ALICE detector control system from themand could not develop the control system for the MFT without their great support. Also, I
grateful thank to Mr. M. Oya who completed the MFT control system based on my design.
I deeply acknowledge Assis. Prof. S. Yano and Specially Appointed Assistant Prof. D. Sekihata for useful discussions and joyful life with them in Hiroshima and CERN. I am gratefulto Prof. T. Sugitate, Assoc. Prof. K. Homma, Assis. Prof. T. Miyoshi, and Mr. M. Ogino. Theygave me valuable comments and suggestions to progress my research. I would like to thankthe Quark Physics laboratory members. Finally, I wish to appreciate my family for theircontinuing support.

67

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73

Acronyms
ADAPOS
AGS
ALF
ALICE
ALPIDEATLAS

ALICE datapoint service
alternating gradient synchrotron
ALICE low-level front-end
a large ion collider experiment
ALICE pixel detectora toroidal LHC apparatus

BC
BCT
BMTF
BNL

barrel calorimeterbarrel calorimeter trigger
barrel muon track ﬁnder
Brookhaven national laboratory

CMS
CRU
CSC
CT
CTP

compact muon solenoid
common readout unit
cathode strip chambercorrelator trigger
central trigger processor

DAQ
DCS
DT

data acquisition system
detector control system
drift tube

EASY
EB
ECAL
ECal
EMTF
EPN

embedded assembly system
endcap barrel
electromagnetic calorimeterelectromagnetic calorimeterendcap muon track ﬁnder
event processor node

FEE
FLP
FPGA
FRED
FSM

frontend electronics
ﬁrst level processor
ﬁeld programmable gate arrayfront-end deviceﬁnite state machine

GBT
GBT-SCA
GCT
GEM

giga-bit transceiver
GBT slow control adaptor
global calorimeter trigger
gas electron multiplier

74

GUI

graphical user interface

HCAL
HCal
HF
HGCAL
HL-LHC
HLT
HTT

hadron calorimeter
hadron calorimeter
hadron forward calorimeterhigh-granularity calorimeterhigh-luminosity LHC
high-level trigger
hardware-based tracking for the trigger

iRPC
IT
ITS

improved resistive plate chamber
inner tracker
inner tracking system

JCOP

joint control project

L0
L1
LAr
LB
LBNL
LHC
LHCb
LINAC

Level-0 trigger
Level-1 trigger
liquid-argon calorimeterlong barrel
Lawrence Berkeley National Laboratory
large hadron collider
large hadron collider beauty
linear accelerator

MAPS
MDT
MFT
MIP

CMOS monolithic active pixel sensor
monitor drift tube
muon forward tracker
minimum ionizing particle

NSW

new small wheel

O2
OMTF
OT

online-offline computing systemoverlap muon track ﬁnder
outer tracker

PHENIX
PID
PLC
PSU

pioneering high-energy nuclear interaction
experimentparticle identiﬁcation
programmable logic controller
power supply unit

QCD
QGP

quantum chromodynamics
quark-gluon plasma

RHIC

relativistic heavy ion collider

75

RICH
RPC
RU

ring-imaging Cherenkov detector
resistive plate chamber
readout unit

SCADA
SPS
STAR
SUSY

supervisory control and data acquisition
super proton synchrotron
solenoid tracker at RHIC
supersymmetry

TGC
TPC
TT

thin gap chambers
time projection chamber
trigger tracker

VELO

vertex locator

WinCC OAWinCC open architecture

76

公表論文
Design and implementation of detector control system for muon forward tracker at ALICE
K. Yamakawa, A. Augustinus, G. Batigne, P. Chochula, M. Oya, S. Panebianco, O. Pinazza,
K. Shigaki, R. Tieulent, and Y. Yamaguchi
Journal of Instrumentation 2020 JINST 15 T10002.

参考論文(1) Υ production and nuclear modification at forward rapidity√
in Pb ‒ Pb collisions at sNN = 5.02 TeV
S. Acharya, K. Yamakawa et al.
Physics Letters B Volume 822, 10 November 2021, 136579.
(2) Production of muons from heavy-flavour hadron decays at high transverse momentum in Pb√‒ Pb collisions at sNN = 5.02 and 2.76 TeV
S. Acharya, K. Yamakawa et al.
Physics Letters B Volume 820, 10 September 2021, 136558.