Doctoral Dissertation
博士論文

Highly granular scintillator-strip electromagnetic calorimeterfor precision physics at future Higgs factories(次世代ヒッグスファクトリーにおける精密物理研究のための高精細シンチレータストリップ電磁カロリメータ)

A Dissertation Submitted for the Degree of Doctor of Philosophy
December 2021
令和 3 年 12 月博士（理学）申請

Department of Physics, Graduate School of Science,
The University of Tokyo東京大学大学院理学系研究科物理学専攻

Naoki Tsuji
辻 直希

Abstract
Several future Higgs factories based on the electron-positron collider are planned for precision Higgs physics
to search for the new physics beyond the Standard Model. The calorimeters play a crucial role on the precision
Higgs measurement, and especially an electromagnetic calorimeter with a quite high granularity is required. The
Scintillator Electromagnetic CALorimeter (Sc-ECAL) is one of the technology options for the ECAL at the future
Higgs factories. In order to demonstrate the performance of the Sc-ECAL and the scalability to the full-scaledetector, the technological prototype has been developed with the full 30 layers. The performances of the ScECAL such as the stability, position resolution, and the shower properties are demonstrated using the prototype.
In addition, a new method to measure the saturation of the SiPM by the scintillation light excited by the UV lightis developed. Finally, using the current conﬁguration of the Sc-ECAL, it is demonstrated by the simulation that anexcellent jet energy resolution is achievable. In conclusion, the Sc-ECAL is found to be a promising and maturetechnology for the highly granular calorimeter to achieve the precision physics at the future Higgs factories.

iii

Contents
Preface
Chapter 1

1Introduction

3

1.1

Standard Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3

1.2

Higgs factories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8

1.3

Physics at Higgs factories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9International Linear Collider (ILC)

17

Chapter 2

2.1

Accelerator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.2

Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.3

Particle Flow Algorithm (PFA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Chapter 3

Scintillator Electromagnetic CALorimeter (Sc-ECAL)

33

3.1

Calorimeter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

3.2

Scintillator ECAL (Sc-ECAL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

3.3

Physics prototype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Chapter 4

Large technological prototype

43

4.1

Technological prototype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

4.2

Strip Splitting Algorithm (SSA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

4.3

Prototype design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

4.4

Scintillator strip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

4.5

Silicon PhotoMultiplier (SiPM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

4.6

ECAL Base Unit (EBU) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

4.7

Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

4.8

Commissioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Chapter 5

Commissioning and Reconstruction

67

5.1

Calibration and commissioning test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

5.2

Reconstruction for straight track . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

5.3

Reconstruction for shower event . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Chapter 6

Calibration

77

6.1

Gain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

6.2

Inter-calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

Contentsiv
6.3

Cross-talk and after-pulse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

6.4

Pedestal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

6.5

MIP calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

6.6

Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Chapter 7

Performance

93

7.1

Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

7.2

Simulation of cosmic-ray . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

7.3

Performance evaluation using the cosmic-ray straight track . . . . . . . . . . . . . . . . . . 101

7.4

Performance evaluation using the cosmic-ray shower . . . . . . . . . . . . . . . . . . . . . . 104

Chapter 8

New method for the saturation correction

119

8.1

Saturation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

8.2

Saturation measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

8.3

Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

8.4

Comparison between measurement and model . . . . . . . . . . . . . . . . . . . . . . . . . 133

Chapter 9

Evaluation of jet energy resolution

139

9.1

iLCSoft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139

9.2

Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141

Chapter 10

Conclusion

147

Appendix149

A

SiPM double-side readout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149

Acknowledgements

155

Bibliography

157

1

Preface
BackgroundThe discovery of the Higgs boson has opened a new era in high energy physics. The precision measurementsof the properties of the Higgs boson is quite important to search for the new physics beyond the Standard Model.
Several future Higgs factories based on the electron-positron collider are planned for precision Higgs physics. The
precision Higgs measurement demands the precise measurement of the hadron jet with the jet energy resolutionof 3–4%. The calorimeters play a crucial role to achieve this requirement. Especially an ECAL with the highgranularity of the 5 mm × 5 mm cell size is required. The scintillator electromagnetic calorimeter (Sc-ECAL)
is one of the technology options at the future Higgs factories. It is based on a scintillator strip readout by asilicon photomultiplier (SiPM), and realizes the 5 mm × 5 mm cell size by aligning the strips orthogonally in x-y
conﬁguration.

Structure of this thesis
This thesis focuses on a highly granular Scintillator Electromagnetic CALorimeter (Sc-ECAL) for the precision
physics at future Higgs factories. Chapter 1 gives a physics background for the Higgs factories. Chapter 2 explains
the International Linear Collider (ILC) on behalf of the Higgs factories. The concept of the Particle Flow Algorithm(PFA) and physics contribution of the ECAL is also introduced. Chapter 3 gives a detail of the Sc-ECAL and thepreliminary study. Chapter 4 gives a detail of a new technological prototype for the Sc-ECAL. Chapter 5 explainsa status of commissioning tests of the prototype, and Chapter 6 and 7 show the results of the tests. Chapter 6 shows
results of the calibrations of key parameters, and Chapter 7 shows the results of the performance evaluation andthe comparison with the Monte Carlo simulation. Chapter 8 gives a development of a new method for a saturation
correction. Finally, Chapter 9 shows an evaluation of the jet energy resolution. This thesis is concluded in Chapter
10

Author’s contribution
The Sc-ECAL involving the technological prototype has been developed in the ILC-ILD group and the CEPCECAL group. The prototype is developed as a joint eﬀort of the these groups. Although the author was notable to participate directly in the construction due to the COVID-19, but jointly checked the data quality of thecommissioning tests. The schemes of the calibration and reconstruction written in Chapter 5 are mainly developedby the author. The calibration and performance evaluation written in Chapter 6 and 7 are done by the author. In
addition, the new method of the saturation correction written in Chapter 8 is developed by the author, and theevaluation of the jet energy resolution written in Chapter 9 is also done by the author.

3

Chapter 1

Introduction
1.1 Standard Model
The Standard Model is a widely accepted framework in the particle physics. In July 2012, the ATLAS and CMS
experiments at the Large Hadron Collider (LHC) discovered the Higgs boson [1][2], the only particle predictedby the Standard Model but not found. Although the Higgs boson completes the Standard Model, there are many
physics phenomena that cannot be explained by the Standard Model, such as the existence of dark matter. In order
to comprehensively understand these physics phenomena, a new theory beyond the Standard Model is required.
Many new theories beyond the Standard Model have been proposed, and among them, the super-symmetry theory
and extra-dimensional theory are considered to be the most promising. It is expected that the new phenomena
predicted by the new theories can be searched for by observing the Higgs boson. In addition, the Higgs boson
itself has not yet been studied in details, and this is also one of the most important issues. The Higgs factories areplanned to make precise measurements of the Higgs boson and to search for the new physics.
This chapter gives the outline of the Higgs factories.

1.1.1 Elementary particles
The Standard Model has been established as the fundamental theory of the particle physics, and experimental
results on the properties and interactions of elementary particles are explained by the Standard Model. Fig. 1.1
shows the list of elementary particles included in the Standard Model. The Standard Model in particle physics
consists of a group of particles called quarks and leptons, which are the smallest elements of matter, gauge bosons,which mediate the interactions between quarks and leptons, and the Higgs boson, which is associated with the
Higgs ﬁeld.
Quarks are the spin-1/2 particles with the strong interaction, and leptons are spin-1/2 particles with the weakinteraction. Quarks are classiﬁed into six types according to their charge and generation: up, charm, and top, withcharge +2/3; down, strange, and bottom, with charge −1/3. Leptons are also classiﬁed into six types: electron,
muon, and tau, with charge −1; electron neutrino, muon neutrino, and tau neutrino, with no charge. The main
diﬀerences between generations are mass, but the reason for the existence of generations and whether there are
more than three generations is still unknown. Each quark also has three degrees of freedom depending on thequantum number called the color charge. The asymptotic freedom is associated with strong interactions, andquarks can only exist in combinations which is colorless, i.e., in bound states such as mesons and baryons.
Gauge bosons are spin-1 boson particles, which are exchanged between elementary particles. For example,

Chapter 1 Introduction

4

Figure1.1 Elementary particles of the Standard Model [3]charged particles undergo the electroweak interaction by exchanging photons, particles with color charge undergo
the strong interaction by exchanging gluons, and particles with weak charge undergo the weak interaction byexchanging Z bosons and W ± bosons. The strength of the interaction is expressed by the magnitude of thecoupling constant with the gauge boson, and there is a correspondence between the lifetime of the gauge bosonand the distance reached by the interaction.
In the Standard Model, the mass term of the gauge boson is forbidden under the SU(2)L ⊗U(1)Y gauge symmetry,
and the large mass of Z and W ± bosons cannot be explained. In order to explain this, the Higgs mechanism was
proposed in 1964 [4]. Under the Higgs mechanism, the spontaneous breaking of the gauge symmetry is achievedby requesting the Higgs ﬁeld, and the mass term of the gauge boson appears. In 2012, the Higgs boson was
discovered by the Large Hadron Collider (LHC) at CERN [1][2], and the Standard Model is completed.

1.1.2

Gauge theory

The interactions between elementary particles are explained by the gauge theory. In the quantum ﬁeld theory, aquantum ﬁeld ϕ is associated with each fundamental particle, and its properties are described by the LagrangianL(∂µ ϕµ , ϕµ ). By solving the Euler equation for the Lagrangian, the equation of the quantum ﬁeld can be derived.

Assuming the Lagrangian is invariant under the local gauge symmetry of the quantum ﬁeld, the vector ﬁeld
called the gauge ﬁeld appears. The product of the gauge ﬁeld and the quantum ﬁeld represents the interaction
and deﬁnes the form of the Lagrangian. The idea that the local gauge symmetry determines the Lagrangian anddescribes the interaction is called the gauge theory.
Among the four types of interactions, the electromagnetic interaction is described by the quantum electrodynamics, the strong interaction is described by the quantum chromodynamics, and the weak interaction is uniﬁedwith the electromagnetic interaction by the Glashow-Weinberg-Salam theory (GWS theory) [5][6][7]. The gravitational interaction is extremely weak compared to the other interactions, so it does not have observable eﬀects at
sub-atomic scales and is not described in the Standard Model.

1.1.3

Higgs mechanism

The creation of the mass is explained by the Higgs mechanism in the Standard Model. According to the GWS
theory, the electroweak interaction is derived by SU(2)L ⊗U(1)Y , but the mass term of the gauge boson is forbidden
which cannot explain the large masses of Z and W ± . In order to explain the gauge boson mass while preserving thegauge symmetry of the Lagrangian, the spontaneous symmetry breaking is adopted. The scalar ﬁeld that interacts

1.1 Standard Model5with the gauge boson, the complex two-dimensional Higgs ﬁeld: Φ, is introduced, and the potential of the Higgs
ﬁeld is written by:

V (Φ) = µ2 Φ† Φ + λ(Φ† Φ)2

where,
1
V (Φ) = √
2

(

ϕ+
ϕ0

)

1
=√
2

(

ϕ1 + iϕ2
ϕ3 + iϕ4

(1.1)
)

(1.2)

The point where the potential is minimized is considered to be the stable point of the vacuum. Here, λ ≥ 0 is
required to prevent the negative divergence of the potential. In the early universe, µ2 ≥ 0, the stable point of thevacuum is Φ = 0. However, as the universe cools down, µ2 < 0, the shape of the potential changes as shown in
Fig. 1.2.

Figure1.2 The symmetry-breaking Higgs potential[8]There are countless stable points in the vacuum, and the phase rotation symmetry of the Higgs ﬁeld is broken
at the moment when one point is chosen. The minimum point of the potential V (Φ) is moved from the origin(ϕ1 = ϕ2 = ϕ3 = ϕ4 = 0) to the point that satisﬁes:Φ† Φ =µ2
1 2(ϕ1 + ϕ22 + ϕ23 + ϕ24 ) = −
2
2λ

(1.3)

In this point, the vacuum has a ﬁnite expectation value of the Higgs ﬁeld ⟨Φ⟩, and this can be interpreted as thecondensation of the Higgs ﬁeld in the vacuum.
V (Φ) = µ2 Φ† Φ + λ(Φ† Φ)2(1.4)

The ﬁeld is expanded as ϕ0 (x) = v + h(x) around this point. The gauge is chosen so that h is real. On theother hand, the interaction between the Higgs ﬁeld and the gauge boson is determined by the gauge principle andis derived from the Lagrangian of the scalar particle, where ∂µ is replaced by Dµ :LHiggs = (Dµ Φ)† (Dµ Φ) − V (Φ)(1.5)

where Dµ = ∂µ + igσ a Wµa /2 + ig ′ Y Bµ /2, Wµ and Bµ are the gauge ﬁelds associated with the SU (2)L and U (1)Ysymmetry with g and g ′ couplings, σ a with a = 1, 2, 3 are the Pauli matrices and Y = 1/2 is the hyper-charge ofthe Higgs doublet. It allows Z and W ± bosons to acquire the masses written by:√g
g 2 + g ′2mW = v, mZ =
v
2
2

(1.6)

Chapter 1 Introduction

6

Since the Higgs ﬁeld is deﬁned as the complex scalar doublet, it has four degrees of freedom. Three of these
degrees of freedom are consumed by the phase rotation at the stable point of the vacuum, and the remaining degrees
of freedom become the Higgs boson with mass. The mass of the Higgs boson can be written by:√√
mh = 2λv 2 = 2|µ2 |(1.7)

The mass of the Higgs boson is one of the most important parameters in the Standard Model. The mass of the√
Higgs boson is mh = 2λv 2 , where v is the vacuum expectation value, and λ is the Higgs self-coupling parameter.
√
While v is determined by one parameter, the Fermi coupling as v = ( 2GF )1/2 , λ is unknown. Therefore, theHiggs boson mass is a degree of freedom in the Standard Model. After the discovery of the Higgs boson at the
ATLAS and CMS experiments in 2012, the ATLAS and CMS experiments continued the combined measurementsof the Higgs boson mass. It results in 125.09±0.21±0.11 GeV [9]. It is said that the ATLAS and CMS experiments
can be able to determine the Higgs boson mass with an uncertainty of about 0.1 GeV.
The coupling of the Higgs boson to the other elementary particles of the Standard Model can be proportional tothe mass of the particle and the vacuum expectation value. The couplings are written by:
Mf
v
2MV2
gHV V =v
2MV2
gHHV V =v2
23MH
gHHH =
v
2
3MH
gHHHH =
v2
gHf f¯ =(1.8)

where Mf is the mass of the fermion, V means the vector bosons (Z , W ± ) and MV is the mass of the vector boson.
The Higgs couplings to fermions and bosons are linearly proportional to the masses of the fermions and bosons,so more massive particles have larger Higgs branching ratio. The branching ratio is largest for the bottom quarks,
BR(H → bb̄) = 57.8%. However, this channel has a poor signal-to-noise ratio and poor resolution due to the bb̄

pair production backgrounds via the strong interaction at the hadron colliders like the LHC, so this channel can
not be useful for precise measurement of the Higgs boson mass and coupling.
Over the years, there have been many attempts to estimate the ultimate sensitivity of the LHC experiments to the
Higgs boson couplings. The results are shown in Fig. 1.3. The LHC experiments will be able to simultaneously
determine the Higgs couplings to the Standard Model particle in a way that, if not completely model independent,
at least depends only on minimal theoretical assumptions. These determinations should be accurate enough to
conﬁrm or disprove the hypothesis that the recently observed particle has the proﬁle of the Higgs boson.

1.1.4

Motivation of precision Higgs measurements

Many parameters of the Standard Model have been measured in a number of experiments. Since there arecorrelations between the parameters, it is possible to predict the values of other parameters based on some of themeasurements. In other words, precise measurements of the observables of the Standard Model are very importantbecause they can verify the self-consistency of the Standard Model itself, and they can also provide informationthat indirectly suggests the existence of new physics beyond the Standard Model.

1.1 Standard Model

7

Figure1.3 Estimate of the sensitivity of the LHC experiments to Higgs boson couplings in a model-independent
analysis. The plot shows the 1 σ intervals for LHC at 14 TeV with 300 fb−1 . [10]The properties of the Higgs boson that we need to investigate is the mass, the decay width, the spin/parity/charge
conjugate (JPC), and its gauge and Yukawa couplings. The key is the mass-coupling constant relation. If the Higgs
boson is the only source of mass for all Standard Model particles, then the coupling constant should be proportional
to the mass, as shown in Fig. 1.4. Therefore, any deviation from the straight line is a signal of physics beyond thestandard theory. In other words, the Higgs boson would open a new window to for new physics.

Figure1.4 mass-coupling constant relation[11]Chapter 1 Introduction

8
The magnitude of the deviation generally follows the decoupling theorem:∆gv2= O( 2 )
g
M

(1.9)

Here, M is the mass scale of the new physics. Since there is no sign of new physics at the LHC so far, M is
considered to be quite large. This means that the deviation from the Standard Model is a few percent to at most
10%. In order to detect these small deviations from the Standard Model and to match new physics beyond theStandard Model by the pattern of deviations, accuracy at the % level is necessary. To achieve this accuracy, thefuture Higgs factories and a high performance instrument to maximize physics opportunities at the Higgs factories
are necessary.
The lepton colliders realize a clean environment because the kinematics of the initial state is clear. The H → bb̄
channel can be used for precise measurements of the Higgs boson mass, and realize the model-independentmeasurements of the Higgs couplings decaying to the other elementary particles. Nevertheless, there are inherent
complexities in measuring hadronic ﬁnal states.

1.2 Higgs factories
The Higgs factories are the colliders that produces large quantities of the Higgs bosons. The purpose of the
Higgs factories is to investigate the nature of the Higgs bosons, which still remains a mystery, and to verify physics
beyond the Standard Model. The Higgs factories basically uses electron-positron collisions because the kinematicsof the initial state must be clear in order to precisely measure the cross section and total decay width of the Higgs
bosons through the Higgs-associated production process. There are two types of accelerators: a linear accelerator
and a circular accelerator. The center of mass energy of the linear accelerator can be extended to a TeV scaleby extending the linear part of the accelerator and/or by improving the performance of the accelerating gradientthrough technological development. On the other hand, the circular accelerator can be operated as a Z/W factories,
and the tunnel can be reused to expand to a hadron collider with a beam energy of several tens of TeV. An overview
of the two Higgs factories that are currently planned for construction around the world will be introduced.

1.2.1

International Linear Collider (ILC)

The International Linear Collider (ILC) project[12] is a future energy-frontier electron-positron linear collider.
The project is being considered for construction in the Kitakami Mountains in Japan, stretching from Iwate to√
Miyagi prefectures. Fig. 1.5 shows the schematic diagram of the ILC accelerator. The operation at s = 250 GeV
is planned, and upgrades are planned for 350 GeV, 500 GeV, and 1 TeV. The superconducting RF is used for theaccelerator, and the linear accelerator part can be extended and/or upgraded to update the center-of-mass energy.
The linearity of the accelerator makes it easy to control the polarization of electrons and positrons to promote or
inhibit speciﬁc reactions.

1.2.2

Circular Electron Positron Collider (CEPC)The Circular Electron Positron Collider (CEPC) [13] is the electron-positron circular collider with the circumference of 100 km that is planned to be built in China. After the operation of the CEPC, the proton-proton collider(Super Proton Proton Collider, SppC) will replace the accelerator in the tunnel. The conﬁguration of the CEPC
accelerator is shown in Fig. 1.6. The accelerator consists of the linear accelerator section, the booster, the main1.3 Physics at Higgs factories

9

Figure1.5 Schematic layout of the ILC at√

s = 250 GeV. ©Rey.Hori/KEK

ring, and two collision sites, each of which is equipped with the detector. The main ring is a double ring consistingof an electron ring and a positron ring.

Figure1.6 Conﬁguration for the CEPC accerelator [13]1.3 Physics at Higgs factories
In the Higgs factories, the Higgs bosons are produced in large quantities, and the Higgs coupling constant ismeasured to verify the deviation from the Standard Model with very high accuracy. The key is to measure the crosssection and decay width of the Higgs boson independent of the physics model. It is also possible to search for newparticles by taking advantage of the clean environment of electron-positron collisions, and the search range can beextended by upgrading the center-of-mass energy. The following is a list of typical targets for each center-of-massenergy.

Chapter 1 Introduction

10

1.3.1

√

s = 250 GeV

In the Higgs factories, the key is to operate the collider at the center-of-mass energy around 250 GeV. This isbecause the Higgs production cross section by the Higgs-associated production process (e− e+ → Zh: Fig. 1.7left) is the largest at 250 GeV (see Fig. 1.8). The mass and production cross section of the Higgs boson can bemeasured precisely without depending on the decay mode of the Higgs boson, taking advantage of the ﬁxed energyof the initial state due to electron-positron collisions and the simplicity of the reaction.

Figure1.7 Feynman diagrams for the three major Higgs production processes at the ILC[10]Figure1.8 Production cross section for the process[10]Higgs couplings
The goal of the ILC program at√

s = 250 GeV is to determine the various Higgs couplings with high precisionin model-independent way. In the Standard Model, all Higgs boson couplings are predicted by the value of the
Higgs boson mass, which is known at the LHC to an accuracy of 0.2% [9]. Any deviation from these predictions
would imply new physics beyond the Standard Model. The expected value of the deviations is small in a typical1.3 Physics at Higgs factories

11

BSM scenario. Therefore, one of the main goals of future e+ e− colliders is to achieve an accuracy of O(1%) in
the measurement of the Higgs boson coupling.
The clean environment of the ILC allows us to measure the major decay modes in a high accuracy such as
h → bb̄, h → W W ∗ (W (∗) → q q̄), and so on. In addition, with the use of high performance detectors, we can see
h → cc̄ and h → gg , decays. This is very diﬃcult at the LHC. Fig. 1.9 shows Lego plots of the distributions of theb-like and c-like variables against Monte Carlo data, various Higgs decays, and a template of the Standard Modelbackground for the ﬁt. The diﬀerent decay modes and backgrounds of the Higgs boson show distinct distributions
and can be separated from each other. It should be noted that in the σ × BR measurement, the main decay modes,
Z → q q̄ and Z → ν ν̄ decays, can be used to increase the statistics. This is also realized by the clean environmentof the ILC.

Figure1.9 Two-dimensional images of the three-dimensional template samples as a function of b-likeness v.s.
c-likeness. The bottom row shows Higgs decays, left to right, to bb̄, bb̄, and gg . The top row shows, left
to right, the full Monte Carlo Higgs sample, the Higgs decays to non-2-jet modes, and the Standard Modelbackground.[10]Eﬀective Field Theory (EFT)The coupling strength of the Higgs boson to AĀ is obtained from the partial width Γ(h → AĀ):BR(h → AĀ) = Γ(h → AĀ)/Γh(1.10)

where Γ is the total width of the Higgs boson. The SM width of the Higgs boson at 125 GeV is 4.1 MeV, which is
too small to be measured directly. Therefore, the width of the Higgs boson has to be determined indirectly, which
requires a model formulation.
The width is usually determined using the κ parametrization. Assuming that the Higgs couplings for each species
A are modiﬁed by the multiplication factor κA , the parameterization can be written by:Γ(h → ZZ ∗ )σ(e+ e− → Zh)= κ2Z ,
= κ2Z
SM
SM

(1.11)

where SM means the prediction in the Standard Model. A suﬃcient number of measurements are available in thee+ e− collider experiment to determine all the κA . The ratio σ(e+ e− → Zh)/BR(h → ZZ ∗ ) is independent of κZ

Chapter 1 Introduction

12and can be directly used to determine the Higgs width. However, at 250 GeV ILC with 2 ab−1 data, the statistics
to measure BR(h → ZZ ∗ ) is limited, and the accuracy of the width determination is compromised.
The κ formalism is not exactly model independent. In case of the Higgs coupling to ZZ , the Higgs boson has
two diﬀerent structures:
δL =

1
m2z
(1 + ηZ )hZµ Z µ + ζZ hZµν Z µνvv

(1.12)

where the coeﬃcients ηZ and ζZ mean independent parameters derived from the new physics. The coupling to
W W has a similar structure with parameters ηW and ζW . The parameters ηZ and ζW are expected to be zero inthe κ formalism. The eﬀect of the term with the ζZ depends on the momentum conﬁguration of the vector boson
because the ζZ depends on the momentum:

for a 125 GeV Higgs boson and√Γ(h → ZZ ∗ )= (1 + 2ηZ − 0.50ζZ )SM
σ(e+ e− → Zh)= (1 + 2ηZ + 5.7ζZ )SM(1.13)(1.14)

s = 250 GeV. Then, the Higgs width cannot be uniquely determined by the ratio

in Equation 1.10.
This problem is solved by the Eﬀective Field Theory (EFT) formalism. The new particles derived from thenew physics are expected to be heavy because the LHC experiment has not discovered them yet. If the newparticles are suﬃciently heavy, the physics of the 125 GeV Higgs boson can be described by integrating theseparticles out of the Lagrangian and replacing their eﬀects with an extension of the Standard Model operator. The
gauge-invariant Lagrangian in the Standard Model consists of the operators up to four dimensions. The additional
operators in six or more dimensions corrects the Standard Model. If the minimum mass of the new particle is M ,the six-dimensional operators have coeﬃcients proportional to m2h /M 2 , which is the ﬁrst order of an expansion
in m2h /M 2 . The operators in 8 or more dimensions is expected to be a further factor of m2h /M 2 . Therefore, it is
proposed to parametrize the eﬀects of the new physics on the Higgs boson by writing an eﬀective Lagrangian withSU (3) × SU (2) × U (1)-invariant operators with 6 dimensions. This is called the Standard Model Eﬀective Field

Theory (EFT) formalism.
Expected precision for Higgs boson couplings
The process e+ e− → Zh has the maximum cross section atwere obtained from an integrated luminosity of 2 ab−1√

s = 250 GeV, and about half a million Zh events. This makes it possible to precisely measure the inclusive

cross section σZh and the decay rates σZh × BR for various decay modes using the recoil mass method. The√
σZh × BR is measured to be 1.0% at s = 250 GeV [14]. Fig. 1.11 shows the distribution of the recoil mass.
Table 1.1 shows the expected precisions for Higgs boson couplings in the κ formalism. All of the Higgs boson
couplings can be calculated via a global ﬁt in the κ formalism using the basic observables of σ and σ × BR. The
total width of the Higgs boson is written by:
Γh =

ΓZZ
ΓW W
=
BRZZ
BRW W

(1.15)

where ΓZZ (ΓW W ) is the partial decay width to ZZ ∗ (W W ∗ ). In the κ formalism, ΓZZ (ΓW W ) is proportional to
the square of the κZ (κW ), which is proportional to the σZh (σννh ):ΓZZ ∝ κ2Z ∝ σZh (ΓW W ∝ κ2W ∝ σννh )(1.16)The other couplings κA and partial decay widths ΓAA , where A = b, c, g, τ, µ, γ , are written by:κ2A ∝ ΓAA = Γh × BRAA

(1.17)

1.3 Physics at Higgs factories

13

κZ can be determined precisely with accuracy of 0.38% at√

s = 250 GeV, while the other couplings κA are

determined to better than ∼ 2%.
Table 1.1 also shows the expected precisions of Higgs boson couplings in the EFT formalism. Fig. 1.10 shows
the illustration and comparison with the predictions of the uncertainties of the Higgs couplings at the HL-LHC.
In the EFT formalism, a larger global ﬁt to the Higgs boson couplings can be used. This ﬁt includes the basic
observables of σ and σ × BR, additional observables from the e+ e− → Zh reaction, and observables from theelectroweak precision physics and e+ e− → W + W − reaction. The EFT greatly improves the measurement of the
Higgs boson couplings. The details is written in [14][15].
Table1.1 Projected relative errors for Higgs boson couplings and other Higgs observables, in %, for ﬁts in the√κ and EFT formalisms. The ILC250 columns assume a total integrated luminosity of 2 ab−1 at s = 250 GeV.
√
The ILC500 columns assume a total integrated luminosity of 200 fb−1 at s = 350 GeV, and a total integrated√
luminosity of 4 ab−1 at s = 500 GeV. Three observables at the HL-LHC, BRγγ /BRZZ , BRγZ /BRγγ
and BRµµ /BRγγ , are included in all of the ﬁts. The eﬀective couplings g(hW W ) and g(hZZ) are deﬁned
as proportional to the square root of the corresponding partial widths. The last two lines give 95% conﬁdence
upper limits on the exotic branching ratios. [16]ILC250+ILC500

κ ﬁt

EFT ﬁt

κ ﬁt

EFT ﬁtg(hbb)

1.8

1.1

0.60

0.58

g(hcc)

2.4

1.9

1.2

1.2

g(hgg)

2.2

1.7

0.97

0.95

g(hW W )

1.8

0.67

0.40

0.34

g(hτ τ )

1.9

1.2

0.80

0.74

g(hZZ)

0.38

0.68

0.30

0.35

g(hγγ)

1.1

1.2

1.0

1.0

g(hµµ)

5.6

5.6

5.1

5.1

g(hγZ)

16

6.6

16

2.6

g(hbb)/g(hW W )

0.88

0.86

0.47

0.46

g(hτ τ )/g(hW W )

1.0

1.0

0.65

0.65

g(hW W )/g(hZZ)

1.7

0.07

0.26

0.05

Γh

3.9

2.5

1.7

1.6

BR(h → inv)

0.32

0.32

0.29

0.29

BR(h → other)

1.6

1.6

1.3

1.2

Precision measurement for Higgs mass
In the mass measurement, the decay mode of e− e+ → Zh, Z → l− l+ (l = e, µ) is used (recoil mass method),which is not aﬀected by the decay mode of the Higgs boson because only the leptons produced in the Z decay areused. The the recoil mass in the Higgs-associated production process is calculated by:√√
mh = ( s − (El− + El+ ))2 − |⃗pl− + p⃗l+ |2(1.18)The uncertainty in the mass of the Higgs boson (δmh ) is a source of systematic error in predicting the Higgs
boson couplings. In most cases, the uncertainties in the Higgs boson mass, δmh , is suﬃcient in 0.2%, except theChapter 1 Introduction

12

LHC 3000 fb-1 (ATLAS: ATL-PHYS-PUB-2014-016 (2014), Model Dependent κ fit)
LHC 3000 fb-1 ⊕ ILC 250 GeV, 2000 fb-1 (Model Independent EFT fit)

10
8

14%

LHC 3000 fb-1 ⊕ ILC 250 GeV, 2000 fb-1
⊕ ILC 500 GeV, 4000 fb-1 ⊕ 350 GeV, 200 fb-1 (Model Independent EFT fit)

11%

Precision of Higgs boson couplings [%]

14

6
4
2
0 g(h

g
g
g
g
g
g
g
g
g
ZZ (hWW (hγ γ (hbb (hτ τ (hgg (hcc (hγ Z (hµ µ (htt)
)
)
)
)
)
)
)
)
)

Figure1.10 Illustration of the Higgs boson coupling uncertainties in the EFT formalism, and comparison ofthese projections
to 5:theIllustration
results of ofmodel-dependent
estimatesuncertainties
for HL-LHCfrom
uncertainties.
[16]formalFigure
the Higgs boson coupling
fits in the EFTism, as presented in Table 1, and comparison of these projections to the results of modeldependent estimates for HL-LHC uncertainties presented by the ATLAS collaboration [24].
Earlier
projections for ∗HL-LHC are summarized in [29].
∗processes of h → ZZ and h → W W . It was pointed out in [17] that:δW = 6.9 × δmh , δZ = 7.7 × δmh(1.19)

where δW and δZ are the relative errors for g(hW W ) and g(hZZ) respectively. The mass of the Higgs boson canbe measured very precisely at the 250 GeV ILC. Fig. 1.11 shows the spectrum of the recoil mass using the leptonic
recoil channel. A very clean Higgs signal protruding as a sharp peak above the background can be seen. The key
point is that we can capture the production of the Higgs boson without seeing the decay of the Higgs boson at all.
17

This allows us to measure the Higgs mass with an accuracy of 14 MeV. This results in systematic errors for δW
and δZ of 0.1%.

1.3.2

√

s = 500 GeV

Direct measurement for triple Higgs coupling
The triple Higgs coupling can be measured by the e− e+ → Zhh and e− e+ → ν ν̄hh process shown in Fig. 1.12.
√
The cross section reaches the maximum at around s = 500 GeV. Combining the three channels corresponding
to the diﬀerent Z decay modes Z → l+ l− , ν ν̄ , and q q̄ , the process can be detected with a 5σ excess signiﬁcanceat beam polarization (Pe− , Pe+ ) = (−0, 8, +0.3) and integrated luminosity 2 ab−1 , and the cross section can bemeasured as ∆σ/σ = 0.27. However, there is a large contribution from the background diagram without selfcoupling, and the relative error in self-coupling λ is ∆λ/λ = 0.44 with appropriate event weighting to increase thecontribution from the self-coupling diagram.
Direct measurement for top quark Yukawa coupling
Since the production threshold of the e− e+ → tt̄h process is√

s = 470 GeV, as shown in Figure 1.13, the top

Yukawa coupling can be directly measured. Since the contribution from the irrelevant h-oﬀ-Z diagram can be√neglected at s = 500 GeV, the top Yukawa coupling gt can be extracted by simply counting the number of signal
events.

Events

1.3 Physics at Higgs factories

15
Data

400

Signal+Background
Signal300

Background-e++e → µ+µ- + X @ 250 GeV

200
100
0
110

120

130

140

150

Recoil Mass (GeV/c2)
Figure1.11 Higgs recoil mass distribution in the Higgsstrahlung process e− e+ → Zh. [18]f events in the signal region+++) µ µ H, eL eR (b) e e H,
gure 10.

nning time are dedicatedd 350 GeV, while 40% of+o each of eL e+
R and eL eR
Figure1.12 Relevant diagrams containing the triple Higgs coupling[10]ZH ,the HZZ coupling2
on ZH / gHZZ
, which
ZH / ZH . Table VIII
gHZZ /gHZZ and MH . It
onic recoil measurements
14 MeV can be achieved
ctively by the end ofp thecontribution from s =p++FIG. 13. For the case of the µ µ H channel and eL eR at s
Figure1.13
Threecontributing
to theGeV:
e− e+ →
tt̄h process[10]=250 GeV,in diagrams
the region
110-155(top)
The Mrec spectra of the signal MC events used in analysis plotted together
with the kernel function. (center) The Mrec spectrum of toy
W W fusion and the hW W coupling
MC events corresponding to the top plot.
√ (bottom) Toy MC
s = 450
GeVstatistical. The cross section of the
The W W fusion process
takes
over
the
Higgs-strahlung
processaroundevents used forextracting ZH and MH andtheir√
OF HIGGSWDECAY
W fusion process is uncertainties,
about 160 fb at whichs = 500 are
GeVgenerated. This large crosssectionthe larger
luminosity allows
using
the andfunction
which
NDENCE the hW W coupling to be
fitted
the
top
plot
as
input.
The
legend
is
the
same
as
directly measured with high precision. In terms of the Higgs cross sectioninand branching
Figure10.are describedratio, the quantities to bemeasureds measured without anyσ(ν ν̄h) · BR(h → bb̄) ∼ Λ(h → W W ∗ ) · BR(h → bb̄)
(1.20)
Higgs decay modes. This√
Combining
using thisthewith the direct measurement of the branching ratio at s = 250 GeV allows us to determine theZH measured
cross section σ(ν ν̄) with an accuracy of 2.7%, which corresponds to an expected error in the hW W coupling of∆ghW W /ghW W = 1.4%. A large data sample of the fusion process is also useful to improve the accuracy of theChapter 1 Introduction

16

h → W W ∗ branching ratio. Replacing ZZ with W W , we obtain the full width of the Higgs ∆Λh /Λh ∼ 6%.

1.3.3

√

s > 1 TeV

In the energy region above 1 TeV, more precise measurements of the Higgs self-coupling and total decay width
will be possible. In addition, it is possible to search for the direct production of unknown heavy new particles
from the single photon production process in the initial state, and to search for new particles indirectly by precisely
measuring the coupling between the Higgs boson and other particles and verifying the deviation from the value
predicted by the Standard Model.
The results of the ILC can also be described as a precise test of the Standard Model relationship that the Higgs
coupling for each particle is exactly proportional to the mass of that particle. The uncertainty of these tests isshown in Fig. 1.14. The ILC provides the understanding of the nature of the newly discovered bosons and theirimpact on the puzzle of electroweak symmetry breaking.

Figure1.14 Expected precision from the full ILC program of tests of the Standard Model prediction that the
Higgs coupling to each particle is proportional to its mass. The normalization is diﬀerent from each particle.[10]17Chapter 2

International Linear Collider (ILC)
This chapter describes the components and details of the ILC accelerator and detector as an example of the Higgs
factory. However, the method of the beam generation and the design of the accelerator varies from accelerator
to another. On the other hand, the detectors are quite similar in all the Higgs factories because the physics to bemeasured is the same. In the Higgs factory, the high-precision detector is required for the precise measurement of
the Higgs boson.

2.1 Accelerator
The ILC beam has a bunch-train structure consisting of multiple bunches; a train of 1312 bunches collide ata frequency of 5 Hz. Since it is a linear accelerator, it is easy to control the spin polarization of the particles
in the beam, and in the current design, the electron and positron polarization will be controlled to (P− , P+ ) =(∓0.8, ±0.3), respectively. The spin polarization is deﬁned by NR and NL , where NR and NL are the number ofright- and left-polarized particles, respectively.
P =NR − NL
NR + NL(2.1)

At the high energy physics, the ability to control the polarization can, for example, increase the fraction ofreactions involving W bosons (e.g., e− e+ → ν ν̄h) where only left-handed electrons are involved when P− isnegative compared to the unpolarized case. Alternatively, when P− is positive, it is possible to suppress the
background events involving W bosons in the e− e+ → Zh, Z → ll processes.
In the ILC, the process from the beam generation to collision is carried out by the following four elements.
• Electron and positron source• Dampling rings• Main linear accelerator• Beam-delivery system

2.1.1 Electron and positron source
Electron source
In the electron source, a polarized laser is used to generate polarized electrons. Fig. 2.1 shows the conﬁgurationof the electron source. When GaAs is irradiated by a polarized laser using the DC gun, polarized electrons of
140-160 keV are emitted due to the photoelectric eﬀect. Depending on the polarization scenario of the ILC,

Chapter 2 International Linear Collider (ILC)18

the target electron polarization ratio is ±80%. The polarized electrons are ﬁrst placed in the normal-conducting
acceleration cavity, where they are accelerated to 76 MeV while forming a bunch of about 3 × 1010 electrons.
Then, the energy and incident direction of the polarized electrons are uniformly aligned by the energy collimator,
and the electrons are further accelerated to 5 GeV in the superconducting acceleration cavity. Before being injected
into the damping ring, the spins are also vertically aligned by the superconducting solenoid.

Figure2.1 Schematic view of the polarised electron source[19]Positron source
The positron source utilizes polarized electrons generated by the electron source. The electrons are ﬁnallyaccelerated to 150 GeV in the main linear accelerator, as described below. Here, the electrons pass through a spiraldevice called an undulator. The undulator is located at the position shown in Fig. 2.2.

Figure2.2 Layout of positron system[19]Fig. 2.3 shows an overview of the positron source. In the undulator, the direction of the magnetic ﬁeld alternates,
and meandering electrons emit energetic photons (10-30 MeV) due to the bremsstrahlung. By injecting thesephotons to a 1.4 cm-thick titanium alloy disk, an electromagnetic shower is generated, which can produce a large
number of electron-positron pairs. After acceleration to 125 MeV, the electrons and positrons are separated byapplying a magnetic ﬁeld to produce a positron beam. The resulting positrons are accelerated to 400 MeV in the2.1 Accelerator

19

normal conduction acceleration cavity, as are the electrons, and further accelerated to 5 GeV in the superconducting
acceleration cavity, where their spin direction and energy are aligned. The accelerated positrons are injected into
the damping ring by the kicker system that generates an instantaneous magnetic ﬁeld.
It is said to be capable of ±30% positron polarization at the basic design stage, but with space for additional
undulators. It is expected that up to ±60% polarization will be possible after the upgrade. In that case, however, aphoton collimator will be required in front of the titanium target.

Figure2.3 Overall layout of the positron source[19]2.1.2 Damping ring
The electrons and positrons accelerated up to 5 GeV are injected into the damping ring. The purpose of thedamping ring is to reduce the emittance. The emittance is a parameter of the dispersion of particles in the beam,
and is deﬁned as the area of the beam in phase space.

Figure2.4 Schematic of the damping-ring layout[19]Fig. 2.4 shows an overview of the damping ring. The electron or positron beam entering the damping ring
travels around the ring, which is about 6.7 km in circumference, for about 200 ms. During this time, the beam
undergoes the bremsstrahlung in the curved part of the ring and is accelerated in the straight part. The beam, whose
momentum is reduced by the bremsstrahlung, recovers only the momentum in the direction of the reference orbit in
the acceleration part, resulting in a decrease in emittance. By repeating this process, the position and momentumof the particles in the beam are adjusted, and a low-emittance beam can be realized. The bunch is then ejected byChapter 2 International Linear Collider (ILC)20
the kicker again and transported to the main linear accelerator.

2.1.3

Main linear accelerator

As shown in Fig. 2.5, the beam from the damping ring is transported to the end of the accelerator (ELTL) andthe direction of travel is reversed (ETURN). The 5 GeV beam is accelerated to 15 GeV by compressing the bunch
length from several mm to several hundred µm in EBC1 and EBC2. The beam is then accelerated to its maximum
energy using the superconducting acceleration cavity of the Main Linear Accelerator (Main Linac).

Figure2.5 Schematic of the main linac layout [19]A 1 m long niobium superconducting acceleration cavity (Fig. 2.6) is used as the acceleration cavity. About
800 cryomodules consisting of nine acceleration cavities and the superconducting cooling system are connected
and installed in the tunnel, and the cavity is operated at an ultra-low temperature of 2 K with high frequency. The
design value of the acceleration gradient is 31.5 MV/m on average.

Figure2.6 A superconducting nine-cell 1.3 GHz resonator (cavity) [20]2.1.4

Beam-delivery system

In the beam-delivery system, the accelerated beam is narrowed down and transported to the interaction point forcollision, and the remaining particles are stopped by the beam dump. An overview of the delivery system is shownin Fig. 2.7. During the beam delivery, the beam energy and spread are measured, and the information is fed backto the ﬁnal convergence system for ﬁne adjustment. In the ﬁnal beam convergence system, the beam is focused on
by a quadrupole magnet to the rms of beam size of 516 nm and 7.66 nm in x and y axis respectively. The electronsand positrons collide at an angle of 14 mrad at the interaction point (Fig. 2.8). The beam is crossed at an angle tofacilitate the collection of non-collided particles.

2.2 Detector
Two detector concepts are proposed: the International Large Detector (ILD) (Fig. 2.9), which is mainly developedin Japan and Europe, and the Silicon Detector (SiD), which is mainly developed in the U.S. The ILD is larger thanthe SiD and can acquire more spatial information by using gas TPC. When the ILC is in operation, the two detectors
are placed alternately on the beamline by the push-pull system, and the results from both detectors are used forcomplementary veriﬁcation. The DAQ of the ILC is designed to reduce power consumption by transferring data2.2 Detector

21

Figure2.7 Schematic of the beam-delivery system layout [19]Figure2.8 Design of the interaction point, detector, and shielding [19]during the 5 Hz bunch train. The length of the bunch train is 1 ms out of 200 ms, so the electric power is turnedon only for about 1% during the operation, called power pulsing, which reduces power consumption. In particular,
the components of the ILD will be discussed.
The structure of the ILD is shown in Fig. 2.10. From the decay point (IP) to the outside of the detector, thestructure is as follows.
• Vertex detector• Silicon tracking system; Silicon detector and Time Projection Chamber (TPC)• Calorimeter; Electromagnetic calorimeter (ECAL) and Hadron calorimeter (HCAL)• Solenoid coil
• Muon detector

2.2.1 Vertex detector
The vertex detector is a semiconductor detector used to measure the production points of primary particles
and the decay points of short-lived particles produced by beam collisions. The decay point is reconstructed byChapter 2 International Linear Collider (ILC)

22

Figure2.9 View of the ILD detector concept [21]Figure2.10 Quadrant view of the ILD detector concept [21]connecting the points where the particles pass as the track. It consists of three ladder layers in a cylindricalconcentric shape, and each ladder has a two-layer structure with pixel sensor layers placed 2 mm apart on bothsides (Fig. 2.11). In this way, six positions are detected for each charged particle track. The ladder of the ﬁrst
ladder layer has half the length of the other two ladders to reduce the background. Three types of pixel sensors arebeing investigated.
• CMOS Pixel Sensors (CMOS)• Fine Pixel CCD (FPCCD)

2.2 Detector

23• Depleted Field Eﬀect Transistors (DEPFETs)

Figure2.11 Mechanical support structure of the ILD vertex detector [21]2.2.2 Silicon tracking system
The silicon tracking detector is designed to obtain the passage point and time of ﬂights for the track reconstruction.
The layout of each detector is shown in Fig. 2.12. By taking advantage of the high position resolution and timestamp of the silicon detector and combining it with the hit information of the TPC, it is possible to obtain ahigh-deﬁnition time stamp of the track.

Figure2.12 Layout of the tracking sysytem [21]2.2.3 Time Projection Chamber (TPC)
The ILD main tracking detector uses a large gas TPC, because the tracking detector must have a low mass inorder to accurately measure the energy in the calorimeter. It provides a large number of 3D spatial points and amore continuous track than a silicon detector, thus increasing the position resolution. Fig. 2.13 shows the structureChapter 2 International Linear Collider (ILC)

24of the TPC. There is a cathode in the center, and electron ampliﬁcation and detection layers are placed on the plates
at both ends. The Micro Pattern Gas Detector (MPGD) such as a Gas Electron Multipliers (GEM) and Micromegas
are being investigated for the electron ampliﬁcation.

Figure2.13 Structure of the TPC [21]The inside of the TPC is ﬁlled with T2K gas [22], which is a mixture of Ar, CF4 , and isobutane. The ionizedelectrons generated when charged particles pass through the TPC are drifted by the electric ﬁeld applied in the
direction of the beam axis and detected as signals by the MPGD. This makes it possible to reconstruct the charged
particle trajectory in three dimensions using the drift time of the ionized electrons and the two-dimensional signal.
In addition, the dEdx can be calculated by the magnitude of the signal, and the particle can be identiﬁed.

2.2.4

Calorimeter

A calorimeter is a detector that measures the energy of a particle. Because of the reconstruction algorithm of theParticle Flow Algorithm (PFA) described in the next section, the ILD calorimeter is divided into an electromagnetic
calorimeter, which measures the energy of photons, and a hadron calorimeter, which measures the energy of neutral
hadrons. Both calorimeters are sampling calorimeters, with an alternating arrangement of absorber layers thatgenerate showers and detection layers that detect particles in the showers. Incident high-energy particles interact
with the absorber layers to create a shower, and the energy of the particles in the shower is measured in the detection
layers. The energy of the incident particles is reconstructed from the energy of the shower and its shape. Photons
and electrons have a short interaction length due to their electromagnetic interaction, and form a dense shower
with a short length and narrow width. On the other hand, hadrons have a small cross section due to their strong
interaction, and their showers spread out due to recoil, resulting in large, wide, low-density showers.
The layout of the Electromagnetic CALorimeter (ECAL) within the ILD detectors is shown in Fig. 2.14. The
ECAL identiﬁes photons and measures their energies. Tungsten works as an absorber layer. The density of tungsten
is larger than that of iron, and its Molière radius is smaller, so it can eﬃciently generate electromagnetic showers
and allows the ECAL to be compact. Several technology options for the detection layer are investigated: one using
pixelated silicon detectors (Si-ECAL), one using strips of plastic scintillators and SiPMs (Sc-ECAL), and a hybrid
design mixing the two. All of them have a cell size of 5 mm × 5 mm to measure high-density electromagnetic
showers, and can realize a very highly granular calorimeter.

2.2 Detector

25

Figure2.14 The electromagnetic calorimeter within the ILD detectors [21]The layout of the Hadron CALorimeter (HCAL) is shown in Fig. 2.15. The absorber layer is made of iron,which is also suitable for measuring the energy of electromagnetic showers generated by hadronic interactions,and the calorimeter is large enough to capture the hadronic showers. Two technology options of detection layers
are considered: a semi-digital type (SDHCAL) that uses a gas RPC with semi-digital readout (2bit) with a
10 mm × 10 mm cell, and an analogue type (AHCAL) that uses a 30 mm × 30 mm scintillator tile readout by a

SiPM.

Figure2.15 Arrangement of AHCAL layers [21]2.2.5 Solenoid coil
3.5 T magnetic ﬁeld is applied to the entire detector by a superconducting solenoid coil. The momentum ismeasured by bending the charged particle track. The arrangement of the coils is shown in Fig. 2.16. Unlike

Chapter 2 International Linear Collider (ILC)

26

conventional detectors, the calorimeters are placed inside the coils for the PFA. In addition, there is an antiDetector-Integrated-Dipole (anti-DID) on the outside of the coil. It generates a magnetic ﬁeld to protect the vertex
detector and the tracking system from the electron-positron pair background created by the gamma-ray reaction
caused by the beam eﬀect.

Figure2.16 ILD magnet cross section [21]2.2.6

Muon detector

The iron yoke and the detection layers are used to measure muons. It is also used as the tail catcher to measure
the energy of particles that have passed through the calorimeters. Two technology options of detection layers arebeing investigated: using a scintillator strip equipped with a wavelength shifting ﬁber and a SiPM, and using an
RPC. As shown in Fig. 2.17, 14 detection layers are inserted between the iron yokes in the cylindrical direction
and 12 layers in the beam axis direction. The inner part of the detector, where the detection layers are crowded,
is designed as the tail catcher, while the outer part, where the detection layers are separated from each other, isdesigned for muon detection. The iron yoke serves not only to detect muons and generate hadron showers, but also
to conﬁne the magnetic ﬁeld of the solenoid.

2.3 Particle Flow Algorithm (PFA)
An unprecedented jet energy resolution is required at the ILC to cleanly separate H , W , and Z hadronic decays.
Their ﬁnal states consisting of multiple jets are formed after many interaction processes. Since the invariant massesof the jets are used to identify and reconstruct the particles, the accurate reconstruction of them is very importantfor precise measurements. The invariant mass of the di-jet is given by
M 2 = 2E1 E2 (1 − cos θ12 )(2.2)

where E1 and E2 are the jet energies, and θ12 is the angle between them. If the angular uncertainty can be neglected,
the jet energy resolution σE /E can be converted into the mass resolution:
σM
1 σE
=√
M
2 E

(2.3)

2.3 Particle Flow Algorithm (PFA)

27

Figure2.17 Sensitive layers of the muon detector [21]An invariant mass resolution comparable to the gauge boson width:ΓZ
σm
ΓZ= 2.7% ≈
≈
m
mW
mZ

(2.4)

leads to an eﬀective 3.6σ separation of the hadronic decay of the W/Z boson. In the traditional method, the jetenergy resolution is written by:

α
σE
=√
⊕β
E
E(GeV)(2.5)

where α is the stochastic term and usually greater than 60%, and β is the constant term and usually a few %. To√
achieve the target of σm /m = 2.7%, the stochastic term have to be < 30%/ E(GeV).
√
Therefore, the ILC is aiming at a jet energy resolution of σE /E = 30 − 40%/ E(GeV) so that the decayof the Higgs, and Z/W bosons can be distinguished by reconstructing the invariant masses of the two jets.
The requirements for the jet energy resolution are beyond what can be achieved with the current state-of-the-art
detectors. An alternative to the classical reconstruction method is developed, the Particle Flow Algorithm (PFA),
which provides a signiﬁcant improvement in the jet energy resolution. The particle ﬂow reconstruction requires ahighly granular calorimeter.

2.3.1 Jets
Through a process of the hadronization, quarks are transformed into colorless hadrons, which are observed bydetectors. At the hadronization energy scale, the QCD couplings become large. Therefore, these processes cannot
be calculated by the perturbation theory. However, a number of phenomenological models have been developed.
Although each model has many free parameters and is far from a concrete theoretical description, the experimental
data can be described reasonably well by these models.
According to the color conﬁnement, the only state that can exist as a free particle is the colorless state. Therefore,
all bound states of quarks and antiquarks are colorless. When quarks and antiquarks are produced in a process
such as e+ e− → q q̄ , they separate with equal and opposite momentum in the center-of-mass frame. At distancesChapter 2 International Linear Collider (ILC)28

as short as 1 fm, they can move as quasi-free particles due to the asymptotic degrees of freedom of QCD. As
the distance increases, each particle undergoes a hadronization process and materializes as a collimated spray ofcolorless particles called a jet. Gluons are similarly hadronized.
The mechanism of the jet production can be explained in two steps. In the ﬁrst step, quarks accelerated over shortdistances of less than 1 fm in the production process emit gluons. Similar to the bremsstrahlung process, coloredparticles can also emit gluons. Since the gluons have a color charge, they can also emit additional radiation. This
process causes a cascade of particles known as a parton shower.
In the second step, as the produced quarks are further separated, a gluonic ﬂux tube is constructed between eachpair, conﬁning the two objects. At distances as large as 1 fm, the energy stored in the color ﬁeld between thetwo objects increases to enough energy to produce a new q q̄ pair. This causes the color ﬁeld to split into smallerﬁelds with lower energy, a favorable condition. This process continues until the quark and antiquark energies
are suﬃciently low to produce a chain of q q̄ pairs, which combine into colorless hadrons. The unstable hadrons
produced in the hadronization process decay into more stable particles, which are observed by the detector.

2.3.2

Concept of PFA

In order to achieve the jet energy resolution of 3–4%, a method called the Particle Flow Algorithm (PFA) has
been devised [23]. As shown in Fig. 2.18 (left), the jet energy was conventionally obtained as the sum of themeasured energies in ECAL and HCAL. In a typical jet, about 72% of the energy (62% charged hadrons and√
10% neutral hadrons) is measured by HCAL, and the typical resolution of HCAL of 55%/ E(GeV) makes it
diﬃcult to achieve the target jet energy resolution. On the other hand, the PFA identiﬁes each particle in the jet
and determines its energy and momentum with the most appropriate detector, as shown in Figure 2.18 (right). In
the HCAL, only long-lived neutral hadrons (about 10% of the jet energy) are measured. This allows the jet energy
resolution to be signiﬁcantly improved by measuring each particle with a detector having the optimum resolution.

Figure2.18 The concept of the PFA. Charged particles (purple) are reconstructed and measured by the internal
tracker, photons (red) by the ECAL, and neutral hadrons (black) by the HCAL. [23]The PFA reconstructs the particles in the jet from the charged particle tracks obtained by the tracking detector
and the shower information obtained by the calorimeter. Particles bent by the magnetic ﬁeld are reconstructed as
charged particles by the internal tracker, and particles unaﬀected by the magnetic ﬁeld are reconstructed as neutral
particles by the calorimeter. Therefore, it is important to separate the charged particle showers from the neutral
particle showers with high accuracy, and a highly granular calorimeter is required for this purpose.
Fig. 2.19 shows the possible errors in the reconstruction using the PFA, which are called confusion. As shownin the left and center ﬁgures, when a charged hadron shower and a photon or neutral hadron shower occur near

2.3 Particle Flow Algorithm (PFA)each other, the latter may be recognized as the charged hadron shower. In addition, as shown in the right ﬁgure, thetail of a charged hadron shower may be recognized as a separate neutral hadron shower. In order to eliminate theseerrors, the high-granular calorimeter and the reconstruction algorithm that optimally integrates the informationfrom the tracking detector and calorimeter are required.

Figure2.19 Possible errors during the reconstruction using the PFA. [23]The PandoraPFA [23][24] is the typical reconstruction program that incorporates PFA based on the ILD. It
uses Monte Carlo simulations to reconstruct jets and verify the performance of the ILD model. Fig. 2.20 showsthe event display, which is color-coded by energy and particle type, indicating that the PandoraPFA is able toseparate charged particles from neutral particles by integrating the information from the tracking detector and thehigh-granular calorimeters.

Figure2.20 Event display for the PandoraPFA simulation with 100 GeV jets. [24]The PandoraPFA development is guided by a detailed understanding of the relative roles played by resolution
and confusion eﬀects in diﬀerent energy regimes, as well as detector characteristics that aﬀect performance. In
order to use the energy-momentum match, PFA calorimeters with their emphasis on imaging must also have highenergy resolution. In addition, the energy uncertainty of particles within the jet contributes signiﬁcantly to theresolution of the jet at low energies where the particles are well separated, but at higher energies the eﬀect ofconfusion becomes signiﬁcant. The transition is around 100 GeV as shown in the Fig. 2.21. This performance is29

Chapter 2 International Linear Collider (ILC)30

compared to the resolution obtained with the conventional approach, which is based on calorimeter information
only. At jets as high as 500 GeV, confusion dominates, as shown separately, but is greatly improved by the particle
ﬂow. Note that the degradation at high energies is also due to leakage, which has a signiﬁcant impact on purecalorimeter.

Figure2.21 Jet energy resolution simulation using the ILD as a function of energy, where rms90 is the RMS at
the range containing 90% of the events. The contribution from confusion, and the resolution obtained from thecalorimeters alone for comparison, and that of an ideal calorimeter with given parameters are also shown. [24]2.3.3

Physics contribution of PFA calrimeter

The Highly-granular calorimeters required by the PFA will greatly contribute to the precise Higgs physics at
the future Higgs factories such as the ILC. The PFA realizes the ultra high jet energy resolution of 3–4%, which
realizes the precise measurement of the hadronic decay of H/W/Z , and then realizes the precise measurementof the Higgs boson couplings. The ILD has initiated a systematic benchmarking eﬀort to study the performanceof the latest ILD concept, and to determine the correlations between science objectives and detector performance[25]. The list of benchmark analyses is shown in Table 2.1, and the precise jet measurement is crucial in many
important physics. The PFA calorimeter is the critical system to achieve the ultra high jet energy resolution.
In order to measure the branching ratio and coupling of the Higgs boson, the jet tagging is necessary, because
the Higgs decay process of h → W W ∗ /ZZ ∗ /q q̄/gg produces di-jets, and the decay mode can be determined onlyby the invariant mass of the jets. The cross-section of each decay process can be calculated by the events after thejet tagging, then the branching ratio can be calculated.
Since the invariant masses of the jets are used to tag the jets and measure the Higgs boson couplings accurately,
the accurate reconstruction of jets is very important for the precision Higgs physics. Jets contain a number ofparticles involving charged particles of 64%, gamma-ray of 26%, neutral hadrons of 10%, and they inject into a2.3 Particle Flow Algorithm (PFA)

31

Table2.1 Table of benchmark reactions which are used by ILD to optimize the detector performance. The
analyses are mostly conducted at 500 GeV centre-of-mass energy, to optimally study the detector sensitivty.
The channel, the physics motivation, and the main detector performance parameters are given. [25]Measurement

Main physics question

main issue addressed

Higgs mass in H → bb̄

Precision Higgs mass determina-

Flavour tag, jet energy resolution,

tion

lepton momentum resolution

Rare decay, Higgs Yukawa cou-

High-momentum pt resolution, µµ µpling to muons

identiﬁcation

Limit on H → invisible

Hidden sector / Higgs portal

Jet energy resolution, Z or recoil→

Branching ratio H+ −mass resolution, hermeticity
Coupling between Z andContact interactions, new physics

Highly boosted topologies, τ re-left-handed τ

related to 3rd generation

construction, π 0 reconstruction

Cross

sectionof

Vector Bosons Scattering, test va-

W/Z separation, jet energy reso-+ −e e → ννqqqq

lidity of SM at high energies

lution, hermeticity

Left-Right asymmetry in

Full dim-6 EFT interpretation of

Jet energy scale calibration, lepton+ −e e → γZ

Higgs measurements

and photon reconstruction

Hadronic branching ratios

New physics modifying the Higgs

Flavour tag, jet energy resolutionfor H → bb̄ and cc̄

couplings
fromForm factors, electroweak cou-

Flavour tag, PID, (multi-)jet ﬁnal

and

pling

states with jet and vertex charge

Discovery range for low

Testing SUSY in an area inacces-

Tracks with very low pt , ISR pho-

∆M Higgsinos

sible for the LHC

ton identiﬁcation, ﬁnding multiple

AF B , ALR+ −e e → bb̄tt̄ → bb̄qqqq/bb̄qqlν

vertices
Discovery

range

for

Invisible particles, Dark sector

Photon detection at all angles, tag-

WIMP’s in mono-photon

ging power in the very forward

channelcalorimeters

Discovery range for extra+ −Higgs bosons in e e→

Additional scalars with reduced

Isolated muon ﬁnding, ISR photon

couplings to the Z

identiﬁcation.

Zh

speciﬁc area. In order to measure the invariant mass of the jets accurately, an ultra high jet energy resolution isessential. The PFA calorimeters realize the high performance of the particle identiﬁcation and separation of thecontribution of each particle, hence, signiﬁcantly improved the jet energy resolution.
Since the PFA ECAL measures the energy of the gamma-rays, which make up 24% of the jets, it has the large
contribution of the measurements of the jet energy. In addition, not only electrons and gamma-rays, but also
charged hadrons and muons are injected to the ECAL. The PFA ECAL needs to extract only gamma-rays froma large number of particles in a speciﬁc area and measure their energy, which requires a very high granularity.
For example, when an electron and a gamma-ray are incident on a nearby location at the same time and their
showers are overlapped, the energy contribution of the electron is subtracted from that of the gamma-ray, thenthe gamma-ray energy is measured accurately. When a charged hadron and a gamma-ray are incident and theChapter 2 International Linear Collider (ILC)

32

gamma-ray shower and charged hadron track are overlapped, not only the energy contribution from the charged
hadrons is separated from the reconstructed energy, but also the information of the particle track should be sent
to the HCAL. The particle tracks and showers must be accurately measured and the contribution of each particle
must be separated, requiring 3D reconstruction with highly-granular cells.

2.3.4

Requirement for PFA ECAL

In order to separate the particles using the very compact ECAL, the material with small Molière radius isrequired, and the granularity of the calorimeter must be higher than the conventional calorimeters with a O(m)granularity. In order to separate the photons and elucidate the substructure of the hadronic shower, the transverseand longitudinal cell sizes of ECAL and HCAL must be on the order of the radiation length X0 , resulting in achannel number of 107 –108 . Both ECAL and HCAL must be contained within the magnetic coil in order to keep
as little material as possible in between when integrating the tracking and calorimeter information.
The requirement of the granularity at the PFA ECAL is the cell size of 5 mm × 5 mm. Fig. 2.22 shows the
conﬁguration with the cell size less than 10 × 10 mm2 meets the ILC jet energy requirement of 3–4%. For 45 GeV
jets, this dependence is relatively weak because the confusion term does not signiﬁcantly aﬀect the resolution. For
higher energy jets, the performance drops signiﬁcantly with increasing cell size mainly due to the confusion. The
cell size for the PFA ECAL has to be at least 10 mm × 10 mm to meet the jet energy requirement, but If aiming forhigher accuracy and higher energy measurements, the 5 mm × 5 mm segmentation is preferred.

Figure2.22 The dependence of the jet energy resolution (rms90 ) on the ECAL transverse segmentation at the Si-ECAL. [21]The highly-granular PFA ECAL with a cell size of 5 mm × 5 mm make a signiﬁcant contribution to the precise
measurement of the Higgs boson in the ILC.

33

Chapter 3

Scintillator Electromagnetic CALorimeter(Sc-ECAL)
In the PFA, particle tracks are identiﬁed one by one by mapping the track information of the tracking system to thehit information of the calorimeter. The electromagnetic calorimeter is required to have a transverse segmentation of
5 mm×5 mm, which is much higher than that of the typical electromagnetic calorimeter in the collider experiments.

This chapter describes the details of the electromagnetic calorimeter options (Fig. 3.1), especially the scintillator
ECAL.

Figure3.1 Technology options of the ECAL (left) and HCAL (right). [21]3.1 Calorimeter3.1.1 Shower
When high-energy electrons are injected into a material, they cause bremsstrahlung and emit γ -rays. The
generated γ -rays undergo pair production and emit electron-positron pairs. These two processes are repeated until
the energy of the produced particles becomes lower than the critical energy below which the ionization energy loss
dominates and the bremsstrahlung is no longer emitted. This phenomenon, in which incident electrons interact
with matter and develop in time like a shower, is called an electromagnetic shower. The length of the shower inthe direction of the incident axis is proportional to log E0 (where E0 is the energy of the incident particle), and theChapter 3 Scintillator Electromagnetic CALorimeter (Sc-ECAL)

34

shower radius is deﬁned as the Molière radius RM :RM [g/cm2 ] ≈216[MeV]X0
Ec [MeV](3.1)

where Ec is the critical energy of the material and X0 is the radiation length:
X0 [g/cm2 ] ≈716[g/cm−2 ]A√
Z(Z + 1)In(287/ Z)(3.2)

where the A is the mass number and the Z is the atomic number of the material. ∼90% of the particle energy is
contained within the Molière radius.
On the other hand, when high-energy hadrons are injected into a material, spallation reactions occur and many
particles are produced due to the strong interaction. As a parameter of the shower, the nuclear interaction length
λ0 ∼ 35A1/3 [g/cm2 ] is used, which is generally much larger than the radiation length. Therefore, a thick layerof high-density material is required to capture the entire shower. Because the cross section of the hadron shower
is smaller than that of the electromagnetic shower and much of the energy is used for nuclear decomposition, themeasurement of the hadron shower results in poor energy resolution.

3.1.2

Total absorption calorimeter and sampling calorimeterIn the total absorption calorimeter, the absorber itself is used as a detector, and particles are detected using
scintillation light or Cherenkov light. This type of calorimeter has good energy resolution because it can absorb
and detect the energy of the entire shower, but it requires a larger calorimeter to absorb all the energy, especiallyfor hadron showers, and the cost is high.
The sampling calorimeter has a sandwich structure of absorber and detector. A plastic scintillator, silicondetector, or gas detector is used in the detection layer. Since most of the energy of the shower falls in the absorberlayer and only a part of the energy can be measured in the detection layer, the energy resolution is low. However,
it is possible to build a large-scale calorimeter that can cover the entire shower length at low cost. In addition, it iseasy to make the highly-granular detection layer, making it suitable for the ILD detectors using the PFA. Therefore,
the ILD adopts sampling type calorimeters.

3.2 Scintillator ECAL (Sc-ECAL)
There are two technology options of the analogue ECAL for the PFA ECAL for the ILD. Both options are thesampling calorimeters. This section mainly gives the overview of the scintillator ECAL (Sc-ECAL).

3.2.1

Silicon ECAL (Si-ECAL)

Si-ECAL is one of the technology options for the ILD ECAL. The structure of the Si-ECAL is shown in Fig.
3.2. The Si-ECAL uses a silicon semiconductor detector as the detection layer. It has the advantage of better
signal-to-noise ratio and higher readout accuracy than the Sc-ECAL, while it requires a large number of readout
channels of about 108 . A silicon pad sensor with 5 mm × 5 mm silicon cells is placed on a tungsten plate to form
the orthogonal structure of the detection layer and absorber layer. Since the detection layer can be thinner than the
scintillator, the entire ECAL layer can be made thinner.

3.2 Scintillator ECAL (Sc-ECAL)

Figure3.2 Cross section of the electromagnetic calorimeter layers for the silicon option. [21]3.2.2 Scintillator ECAL (Sc-ECAL)
The Sc-ECAL consists of three parts: a cylindrical barrel around the beam axis, an end cap that covers bothends of the barrel, and a ring that ﬁlls the gap between the barrel and the end cap. The Sc-ECAL is capable ofcovering almost all particles produced by collisions at the center of the ILD. The DAQ mechanism and cabling are
all integrated into the space between the barrel and the end cap to reduce dead space as much as possible. The blue
area in Fig. 3.3 is the barrel of the Sc-ECAL. The barrel has two rings in the beam axis direction, each divided
into 8 sections in the azimuthal direction. The Si-ECAL also has the same mechanical structure.
The layer structure is shown in Fig. 3.4. In order to capture electromagnetic showers, 30 layers of absorberlayers and detection layers are arranged alternately. The thickness is designed to be ∼2 mm for the absorber layerand ∼3.5 mm for the detector layer.
The Sc-ECAL uses scintillator strips readout by silicon photomultipliers (SiPMs) in the detection layer. The
use of plastic scintillators makes the calorimeter less expensive than silicon detectors. The scintillator strips arearranged orthogonally in a direct line between the front and back layers to create pseudo 5 mm × 5 mm pixels,
as shown in the bottom of Fig. 3.4. In the current design, the strip has a dimension of 5 mm wide, 45 mm long,and 2 mm thick, and a SiPM is attached to the surface. It is possible to reduce the number of readout channels toabout 1/10 compared to Si-ECAL. On the other hand, Sc-ECAL has a problem of false hits (ghost hits) when two
particles enter the ECAL at the same time at a close distance by crossing the strips (Fig. 3.5), so the length of the
strip should be optimized to reduce ghost hits, as discussed in Section 4.2.
The Sc-ECAL uses tungsten (X0 = 3.5 mm, RM = 9.3 mm) in the absorber layer. Tungsten forms the narrow
showers, and is suitable for the compact detector to achieve the better separation of particles in a limited space.

35

Chapter 3 Scintillator Electromagnetic CALorimeter (Sc-ECAL)

36

Figure3.3 The electromagnetic calorimeter (in blue) within the ILD Detector. The cylindrical (in green) object
outside the ECAL is hadron calorimeter. [21]Figure3.4 Structure of the Sc-ECAL. ScintillatorX and ScintillatorY are positioned orthogonally. [21]3.3 Physics prototype
The concept of Sc-ECAL has been already validated using a physics prototype [26]. This section summarizes
the structure and performance evaluation of the physics prototype.

3.3 Physics prototype

Figure3.5 Ghost hits in the ScECAL. In addition to the true hit pair, a false hit pair is generated, and it is notpossible to determine which is the correct hit pair or combination.

3.3.1 Detector
The physics prototype for the Sc-ECAL shown in Fig. 3.6 was constructed and tested. The prototype consistedof 30 pairs of alternating tungsten absorber and scintillator layers, with the total thickness of 266 mm. Fig. 3.7
shows the design of a detection layer, consisting of four rows of 18 scintillator strips. Fig. 3.8 shows the designof a single polystyrene-based scintillator strip with the central hole for the wavelength shifting (WLS) ﬁber. The
size of the strip was 9.85 × 44.71 × 3.02 mm3 , and a notch with a depth of 1.40 mm and a width of 4.46 mm toaccommodate the SiPM. A double clad 1 mm diameter Y-11 WLS ﬁber produced by Kuraray [27] with a lengthof 43.6 mm was inserted into the hole of each strip. Each strip was wrapped with a 57 µm-thick reﬂective foil
produced by Kimoto [28]. A multi-pixel photon counter (MPPC), from Hamamatsu Photonics K.K. [29], was usedas the photosensor. The size of the MPPC package was 1.3 × 4.2 × 3.2 mm3 . The four long sides of each strip
were polished to precisely control the strip size and to ensure reﬂection of the surfaces.
The signal lines from the MPPCs and their power supply lines were grouped together on a ﬂat cable, and thesecables were connected to a single base board outside the prototype as shown in Fig. 3.6. It contained six analogueboards with a readout ASIC [30]. Each ASIC controlled 18 MPPCs, and one base board controlled 108 MPPCs.

3.3.2 Test beam at FNAL
The prototype was exposed to particle beams of varying type and energy at the Meson Test Beam Facility number
6 (MT6) at the Fermilab: electron beams from 1 to 32 GeV to study the electromagnetic response of the detector;
muons from 32 GeV to calibrate the detector; and charged pions from 1 to 32 GeV to study the hadronic response.

37

38

Chapter 3 Scintillator Electromagnetic CALorimeter (Sc-ECAL)

Figure3.6 The Sc-ECAL prototype in front of the CALICE AHCAL [26]Figure3.7 The arrangement of 72 strips in a scintillator layer [26]

3.3 Physics prototype

Figure3.8 Top and side views of a scintillator strip (left) and the notches cut into the strips to accommodate
the MPPC packages (right). All dimensions are given in mm. [26]3.3.3 Performance of the prototype
Fig. 3.9 shows the mean reconstructed energy as a function of the injected electron beam energy. The slope
and oﬀset at the linear ﬁt shown as the solid line are (130.22 ± 0.26) MIP/GeV and (23.2 ± 1.6) MIP, respectively,
where the MIP is the detector response to the minimum ionized particle. The maximum deviation from linearity
at each beam energy is (1.1 ± 0.4)%, at 8 GeV.

Figure3.9 Response of the ScECAL prototype to 2–32GeV electrons (top), deviation from the result of a linear
ﬁt (bottom). The error bars show the statistical and systematic uncertainties. [26]Figure 3.10 shows the energy resolution as a function of the inverse of the square root of the beam energy. The

39

Chapter 3 Scintillator Electromagnetic CALorimeter (Sc-ECAL)

40

curves show the results of ﬁtting the data with the two-component parameter for energy resolution:
σE
Cstoch=√⊕ Cconst
Ereco
Ebeam [GeV](3.3)

where Cstoch and Cconst are the ﬁt parameters and determined to be (12.5 ± 0.4)% and (1.2 ± 0.4)%, respectively.
The uncertainties include both systematic and statistical contributions.

Figure3.10 Energy resolution of the Sc-ECAL as a function of the inverse square root of the beam energy.
The error bars show the statistical and systematic uncertainties. [26]The left ﬁgure in Fig. 3.11 compares the simulated response of the prototype to electrons with the data. The
slope of dEreco /dEbeam = 130.27 ± 0.06 MIP/GeV observed in the simulation is consistent with the data of
130.03 ± 0.24 MIP/GeV, but the oﬀset is −3.0 ± 0.1 MIP, which is 27 MIP less than the data. This observation

is clearly illustrated by the ratio of the simulation to the data in Fig. 3.11, left, bottom, suggesting that there
is a constant diﬀerence at all energies. This can be attributed to a small amount of background contamination
remaining in the data, even though the detector noise is determined by overlaying random trigger events on top of
the simulated events.
Fig. 3.11 right shows the energy resolution of the data and simulations under several diﬀerent conditions modeledby the simulations. The simulations agree with the data within the uncertainty range; the discrepancy persists when
applying the beam energy spread from higher beam energies to the data recorded at 2 GeV and 4 GeV (2.3 ± 0.3%).

3.3.4

Issues of physics prototype

The concept of the Sc-ECAL was validated using the physics prototype, but it remains some issues. First, thepixel size of 10 × 10 mm2 doesn’t meet the requirement of 5 × 5 mm2 at the PFA ECAL. At the time of the physics
prototype, the cell size of 10 × 10 mm2 was considered to be suﬃcient, but due to the progress of simulation studies

3.3 Physics prototype

Figure3.11 The response (left) and the energy resolution (right) of data and the simulated prototype to theelectron beams. [26]and updates of the ILD design, the pixel size requirement is now 5 × 5 mm2 .
Second, the strip design was complex and not suitable for mass production towards the construction of the full
detector. The machining of the notch and hole for a WLS ﬁber took a lot of work at the cast moulding, and the
production of the mould with the complex design was diﬃcult at the injection moulding. Furthermore, the MPPC
was located at the side of the strip, so the soldering the MPPC to the board also took a lot of work and the area at
the MPPC itself became an inactive space. Therefore, an improved strip design is required.
Third, a fully integrated electronics (ECAL Base Unit, EBU) has been developed after the physics prototype.
The EBU is equipped with a readout ASIC, SPIROC2E. The EBU can control a large number of MPPCs, andcalibrate them using LED. The temperature is monitored using temperature sensors on the EBU.
In order to overcome these issues, the technological prototype of the Sc-ECAL is proposed to demonstrate theperformance of the Sc-ECAL using the full-scale prototype, and to prepare for the construction of the actual
detector.

41

43

Chapter 4

Large technological prototype
The concept of the Sc-ECAL was already validated using a physics prototype. Now we focus on demonstrating
the performance of Sc-ECAL with a technological prototype with fully integrated detection layers.

4.1 Technological prototype
The technological prototype has been constructed as a joint eﬀort by the ILC-ILD group and the CEPC-ECAL
group. Fig. 4.1 shows the layout of the sandwich structure (top) and an exploded view of the Sc-ECAL prototype(bottom). The absorber layers and alternating detection layers form a sandwich structure. The technologicalprototype consists of 15 super-layers. Each super-layer contains two sets of detection layers and a single tungstencopper alloy absorber plate inserted in the center of the sandwich structure (Fig. 4.1). The detection layer and thereadout electronics are integrated into the ECAL Base Unit (EBU) board. Thirty EBU boards are used in total.
One EBU detection layer contains 210 scintillator strips coupled with a SiPM; the readout of the SiPM is done by
the SPIROC2E chip [31] with 36 integrated channels. There are 6300 SiPM channels in total for the whole system
readout by 180 SPIROC2E chips.
The technological prototype has been constructed with full 30 layers and fully integrated detection layers using
the same technology as foreseen in the actual detector to demonstrate the performance of the Sc-ECAL andthe scalability. The technology options for the PFA HCAL such the Analogue Hadron CALorimeter (AHCAL)
and Semi-Digital Hadron CALorimeter (SDHCAL) have completed the performance demonstration of a large
technological prototype, while the PFA ECAL is not yet at that stage, and the performance demonstration with alarge technological prototype is urgently needed. The possibility of the construction of the Sc-ECAL can be shownby constructing the full-scale prototype using the same technology as for the actual detector and establishing thesystem for the mass production. The high performance and feasible technology of the Sc-ECAL can be shown by theperformance evaluation of the technological prototype with cosmic-ray test, LED test, and test beam experiment.
The development of a highly granular calorimeter is of great signiﬁcance because it is an indispensable technology
for realizing precise physics at the future Higgs factories. The construction and performance demonstration of the
Sc-ECAL technological prototype is an important research that will greatly contribute to the precision measurementof Higgs bosons with the PFA calorimeter. This will be the ﬁrst ever demonstration for the PFA-ECAL concept
with a technological prototype among the technology options.

Chapter 4 Large technological prototype

44

Figure4.1 The layout of sandwich structure (top) and exploded view of the full-scale Sc-ECAL technologicalprototype (bottom)[32]

4.2 Strip Splitting Algorithm (SSA)
This section describes the principle of a novel reconstruction algorithm for the Sc-ECAL called Strip Splitting
Algorithm (SSA), and the simulation study using the SSA to optimize the strip length.

4.2.1

Strip Splitting Algorithm

In order to achieve the cell size of 5 mm × 5 mm with the scintillator strips aligned alternately in orthogonal
orientations, a method called the Strip Splitting Algorithm (SSA) is used [33]. As shown in Fig. 4.2 (left), a
scintillator strip layer consisting of n strips is arranged orthogonally in the upper and lower layers, and a particle
passes through this layer. The central strip layer is divided into n virtual cells according to the projections fromthe upper and lower strips, as shown in Fig. 4.2 right. For the k -th virtual cell (k = 1, . . . , 9), the weighting factor
wk is obtained by:
wk =

∑

Ei

(4.1)

i

where

∑

i is the sum over the strips with the same index at upper and lower layers, and Ei is the energy deposit instrip i. The energy deposit in the virtual cell k is deﬁned by weighting the energy deposit Estrip of the strip in the
middle layer:

where,∑

wk
Ek = Estrip ∑
j wj

(4.2)

j represents the sum over all strips at upper and lower layers.

The SSA is applied to all layers and strips to realize the 5 × 5mm2 cell segmentation. This is the ﬁrst
implementation of the SSA to the real detector.

4.3 Prototype design

Figure4.2 A cartoon illustrating the SSA procedure. The energy, Estrip reconstructed in the central, “longitudinal”, strip is split among virtual cells (k = 1, . . . , 9) by considering the energy in the orthogonally aligned“transverse” strips in neighboring layers. [33]4.2.2 Optimization of the strip length
Two jet events with center-of-mass energy of 200 GeV were simulated with the ILD including the Sc-ECAL
using diﬀerent strip lengths, and analyzed using the PandoraPFA. Figure 4.3 shows the jet energy resolution fordiﬀerent strip lengths. In order to resolve the ambiguity caused by intersecting strips of 5 mm width and diﬀerent
lengths, the SSA was implemented in the PandoraPFA. The results with and without SSA show that there is nostrong degradation with the application of SSA or with increasing the length of the strip. A strip length of 45 mm
as with the physics prototype is chosen as the baseline

4.3 Prototype design
This section focuses on the design of the detection layer and the readout electronics.

4.3.1 Design of detection layer
The technological prototype consists of 30 alternating detection layers and absorber layers, one detection layer
is also called Ecal Basic Unit (EBU) with an integrated readout electronics. Each detection layer consists of an
integrated sensitive unit and readout electronics, with the scintillator strip and SiPM forming the sensitive detection
unit and the readout electronics PCB also serving as the mechanical structure for the sensitive unit. The total
thickness of a detection layer is less than 6 mm, including the thickness of the sensitive unit, the PCB and theelectronics, where the thickness of the scintillator strip plus the reﬂective ﬁlm package is less than 3 mm, and thethickness of the PCB is only 1.2 mm.
Fig. 4.4 shows the layout of the detection layer. The technological prototype uses a 5 mm × 45 mm × 2 mm
scintillator strip. The detection layer consists of 210 channels divided into 5 rows and 42 columns, with a total
sensitive area of 222.3 mm × 226.6 mm, which can contain the lateral spread of the electromagnetic showers andreduce energy leakage. Each scintillator is wrapped with 65 µm 3M ESR reﬂective ﬁlm, leaving 300 µm gaps

45

Chapter 4 Large technological prototype

46

Figure4.3 Jet energy resolution as a function of strip length for the ScECAL option, shown without (red) andwith (blue) the strip splitting algorithm [21]between adjacent strips in the shorter side and 400 µmgaps in the longer side to cover the scintillator processing
errors and assembly accuracy. The fraction of the dead area caused by the gap between scintillators is about
6.5%. The prototype uses two types of SiPMs from Hamamatsu, both with a package size of 1.9 mm × 2.4 mm.
The 24 layers use Hamamatsu MPPC S12571-010P with 10,000 pixels at 10 µm pitch and the other 6 layers use
Hamamatsu MPPC S12571-015P with 4,489 pixels cells at 15 µm pitch. In order to calibrate the SiPM gain, a
LED is installed for each strip on the front-end board.

4.3.2

Design of absorber layer

The photon energy of physical interests at the ILC ranges from 100 MeV to 100 GeV, so the prototype has tohave suﬃcient amount of material in the longitudinal direction to avoid energy leakage. The radiation length oftungsten is 0.35 cm, and the the Molière radius is 18 g/cm2 . These are the smallest among the common materials,
and tungsten can absorb more energy of electromagnetic particles with the same thickness. So it is ideal to choose
tungsten as the absorber material.
However, the pure tungsten material itself is very hard and brittle, not easily machined, and prone to breakage
during transportation and assembly. The tungsten alloy with copper increases the radiation length, which is notdesirable to the electromagnetic shower absorption, so a lower percentage of copper is desired. The tungsten-copper
alloy with a mass ratio of 85:15 is chosen based on industrial production experience, with an equivalent radiation
length of 0.44 cm. The prototype adopts a 30 × 3.2 mm absorber layer design, and the total longitudinal thicknessof the absorber is about 22 X0 . In this conﬁguration, more than 99% of the energy of the electromagnetic showerfrom 100 GeV gamma is deposited in the prototype.

4.3 Prototype design

Figure4.4 Layout of detection layer, scintillator strips, and LED distribution

4.3.3 Design of mechanical structure
For a more ﬂexible and secure assembly of the prototype, two sets of the detection and absorption layers arealternately arranged mechanically to form a super-layer, where the strips are aligned in orthogonal orientations forthe two detection layers, as shown in Fig. 4.5. The bottom layer is an absorber layer, followed by a detection layer
with the scintillator unit side down. A 1.8 mm high through-hole polyimide spacer is placed in the middle of theelectronics plate where the mechanical holes are located, followed by a second absorber layer to avoid damaging
the electronics by direct contact between the absorber layer and the electronics. The top layer is another detection
layer with the scintillator unit upward to keep the entire super-layer surface ﬂat, and similarly a 1.8 mm polyimide
spacer is placed at the location of the mechanical hole between the absorber layer and the electronics. The ﬁnal
absorber and the detection layer are assembled as a super-layer by screwing them to the support structure. The
edges of the support structure are hollowed to reduce the weight and to facilitate assembly and handling, and toprovide ventilation holes for heat dissipation in the front panel. The prototype consists of 15 super layers with 30
alternating detection and absorption layers, plus two detection layers with SiPM double-side readout.
The prototype also needs to have an overall prototype mechanical structure with speciﬁc requirements including
the followings:• Each super-layer can be ﬂexibly assembled and disassembled as an independent unit
• The longitudinal spacing between super-layers should be less than 2 mm
• Independent heat dissipation system, to ensure the normal temperature of the working environment• It provides some protection from light47

Chapter 4 Large technological prototype

48

Figure4.5 Schematic diagram of the super-layer structure, with two consecutive detection layers rotated by 90
degree arranged vertically, and the absorber and detection layers assembled together by a support frame• Capable of supporting the entire gauge for easy transport for the test beam experiment.
In order to meet all the requirements, the mechanical structure of the prototype is designed as shown in Fig. 4.6.
Each side panel of the mechanical structure is milled and processed with a whole aluminum plate, ensuring theoverall mechanical strength and the light weight. There are 18 sets of card slots designed inside the upper andlower panels, each card slot can support a super-layer, and 1.5 mm space is reserved between two super layers forcontingency. The left and right side panels can be disassembled separately, and the super-layer can be assembled
and disassembled from both sides by plugging and unplugging. After assembling, the super-layer can be ﬁxed by
12 screws at the corresponding positions on the left and right sides and the upper side to ensure the stability of thesuper-layer. Each front panel has one power cable and one signal cable, and all the wirings are connected throughan interface on the mechanical structure, which is designed for eﬀective light avoidance. There are 18 HDMI portson the upper side panel and 18 HDMI ports on the right side panel for the signal cable connection of the front
panel, and two 16-wire connectors for the power supply of the front panel. There is a set of six fans on the left
and right side panels, with a total power of 120 W and the same direction of airﬂow, which can be used to cool thefront panel during operation. In addition, the front and rear panels are made of separate 1 mm aluminum plates
at the corresponding positions in the detection layer, and the marker lines are drawn according to the actual sizeand position of the detection layer to facilitate the positioning of the prototype for subsequent beam testing and to
reduce the amount of material in front of the detection layer.

4.4 Scintillator strip
The detection layer of the technological prototype consists of 5 mm × 45 mm scintillator strips on the EBU
board. The scintillation light is detected by the Silicon PhotoMultiplier (SiPM) mounted on the EBU.

4.4 Scintillator strip

Figure4.6 Design of the mechanical structure of the prototype, the schematic diagrams of super layer structure(top left), super layer arrangement (top right), the internal section of the prototype (bottom left), and the
exploded view of the prototype (bottom right)

4.4.1 Scintillator material
A plastic scintillator is a transparent light-emitting organic material, consisting of a base material and a lightemitting substance (e.g., PPO, biphenyl, etc.). The light-emitting substance is called the ﬁrst solvent and the lightyield of the scintillator can be increased by adjusting the light-emitting substance. In addition to the luminescent
substance, a wavelength-shifting agent, also known as a secondary solvent, is usually added to the scintillator.
The wavelength shifter absorbs the ﬂuorescence of the light-emitting substance and emits ﬂuorescence at diﬀerent
wavelengths. The use of wavelength-shifting agents can reduce the self-absorption eﬀect of scintillators, and can
optimize the scintillator ﬂuorescence spectrum to match the spectral response of the photodetector.
There are two major methods for producing scintillators: cast moulding and injection moulding. In the castmoulding method, the scintillator material is moulded at low temperature. The scintillator produced by the cast

49

Chapter 4 Large technological prototype

50

moulding has high light yield, but it is expensive because it takes a long time to mould. Also, since it is basicallymoulded as a large plate, it must be machined into the desired shape. The injection moulding is a method where
the scintillator material at high temperature is injected to a mould. Although the amount of light yield is smaller
than that of the cast moulding, it is suitable for a large scale production such as scintillators for collider experiments
because it can produce any shape at low cost.
The technological prototype uses BC-408 made by Saint-Gobain [34], a plastic scintillator based on polyvinyl
toluene (PVT) produced by the cast moulding, with the performance parameters shown in Table 4.1. It emits about
10,000 scintillation photons per 1 MeV electron energy deposit. The emission spectrum is in the visible light
range, and a photodetector with sensitivity to visible light can be used. It has a time response performance on the
ns scale. The scintillator strip is wrapped in the Enhanced Specular Reﬂector (ESR) ﬁlm from 3M [35], as shownin Fig. 4.7. The ESR ﬁlm has a reﬂectance of 98% or higher in the visible light range.
Table4.1 Performance parameters of BC-408 [34]Light output, %Anthracene

64%

Rise time

0.9 ns

Decay time

2.1 nsWavelength of maximum emission

425 nmLight Attenuation length

210 cmFigure4.7 Scintillator strip. The photo shows a scintillator strip 5 mm wide, 45 mm long, and 2 mm thick,with the ESR ﬁlm.[36]The dedicated plastic scintillator material with low cost and high light yield is also developed for the Sc-ECAL.
The focus of the development is on polystyrene-based scintillators using the injection moulding, which is suitable
for a large scale production. By optimizing the manufacturing parameters, moderately high light yields of 65–70%
have been achieved over commercial PVT-based scintillators. The details of the scintillator strip produced by the
injection moulding is discussed in Appendix A.

4.4 Scintillator strip

51

4.4.2 Scintillator design
The scintillator strip is coupled by the SiPM, and three coupling models are investigated: side-end coupling,bottom-end coupling, and bottom-center coupling. The uniformity of light yield along the strip is important to the
ECAL energy resolution. The results of the performance test with three coupling models are shown in Fig. 4.8.
The bottom-center coupling gives the best uniformity with additional advantages: avoiding the dead area between
scintillators introducing by SiPMs, simplifying the detection layer assembly, and allowing for a large-size SiPM.
The bottom center coupling is adopted as the default design of the detection layer. Fig. 4.9 shows the design ofscintillator strip for the prototype.

Figure4.8 Light yield measurement at diﬀerent SiPM coupling: side-end coupling (left), bottom-end coupling(center), and bottom-center coupling (right). Commercial PVT scintillator coupled with MPPC S12571-015P
is used.

Figure4.9 Design of the scintillator strip. Unit is mm.

The SiPM double-side readout is being developed, and discussed in Appendix A.

Chapter 4 Large technological prototype

52

4.5 Silicon PhotoMultiplier (SiPM)
As mentioned above, the Silicon PhotoMultiplier (SiPM) is used to read out the scintillation light. The SiPM
consists of Avalanche PhotoDiodes (APDs) aligned on pixels. Compared to the conventional PhotoMultiplier Tube
(PMT), the SiPM has the following advantages:• Compact size
• Low cost
• Low operation voltage• Magnetic ﬁeld resistance• Photon counting
The Multi-Pixel Photon Counter (MPPC) manufactured by Hamamatsu Photonics is used in the Sc-ECAL. The
Sc-ECAL uses a surface-mount type with an active area of 1.0 mm × 1.0 mm and 10/15 µm pixel pitch (Fig. 4.10
left). The details of the MPPC are described below.

Figure4.10 Hamamatsu MPPC S12571[37]4.5.1

Principle

The MPPC consists of a number of Geiger-mode APD pixels spread on a 1 mm × 1 mm to 3 mm × 3 mm siliconchip as shown in Fig. 4.11 left and Fig. 4.12. The cross section of the pixel is shown in Fig. 4.11 right. By
applying a reverse voltage slightly higher than the threshold (breakdown voltage) for the APD to operate in the
Geiger mode, the photoelectrons produced by the incident photons are avalanche ampliﬁed in the ampliﬁcation
region. A current through the ﬁred pixel causes a voltage drop in the quenching resistor connected to the pixel.
The output charge Qpix from a pixel is proportional to the pixel capacitance Cpix and the overvoltage ∆V (the4.5 Silicon PhotoMultiplier (SiPM)

53

diﬀerence between the operation voltage Vop and the breakdown voltage Vbd ):[Figure 1-15] Schematic of a V/V high-pass amplifier circuit

Qpix = Cpix (Vop − Vbd )

Rx

(4.3)

Rx

If the Cpix and ∆V are constant, the output is constantregardless of the incident photons. By lowering the potential
Vout
Vin

+
diﬀerence across the ampliﬁcation region,
the avalanche converges and can respond to the next incoming photon.
CR

KAPDC0075EA

The exceedingly high levels of avalanche gain (on the order of several 105 to 106) in Geiger mode make this APD
operation regime particularly interesting to applications with low light levels; specialized GAPDs have beendeveloped for utilization in such applications. However, in order to overcome GAPD’s unavailability forphotoelectron detection during its recovery time and to address its lack of a linear response, a far more versatile
category of silicon photodetectors has been developed based on the GAPD concept by arranging a matrix of themwithin the same field-of-view of the incident light signal. We will now proceed to learn about the multi-pixel
photon counter or MPPC.

1-3. MPPC (multi-pixel photon counter)
Also known
Silicon Photomultiplieror SiPM,the [38]MPPC Redis a circles
common-bias
common-output
Figure4.11 Structure
and asoperatingprinciple ofMPPC.
are andelectrons.
In reality, holes(common-cathode) matrix of GAPD elements (called pixels or microcells) connected in parallel and fabricated on
generated by the electron
avalanche
also
cause
the
avalanche.
a monolithic silicon crystal. Figures 1-16, 1-17, and 1-18 illustrate the layout of MPPC pixels.
[Figure 1-16] Individual MPPC pixels (microcells) with a metal-composite quenching resistor fabricated aroundeach microcell(a) Pixel pitch: 25 Pm(b) Pixel pitch: 50 Pm(c) Pixel pitch: 75 Pm[FigureMagniﬁed
1-17] Conceptual
illustrationof the MPPC
as a matrixof GAPD
pixels(microcells)
connected
parallel [39]Figure4.12
imagesof MPPCswith
25 µm, 50 µm, and
75 µm
pixelinpitches

A single pixel is saturated by an electronGeiger-mode
avalanche
from a single photoelectron, so it is impossible to observe
APD
pixel
more than one photoelectron. The MPPC with many tiny pixels outputs the sum of the charges of all pixels. As
shown in Fig. 4.13, the number of incident
photons
can be measured one by one and the number of incident
Quenchingresistor
photons at a time can be determined. This is one of the main features of MPPC. Fig. 4.14 shows an example ofthe MPPC output waveform. The peaks corresponding to the number of photoelectrons can be clearly seen, and
KAPDC0029EA

15

because the ampliﬁed layer is thin, the signal rises quickly and the MPPC can have an excellent time resolution.

4.5.2 Gain, breakdown voltage
The electron avalanche terminates when the applied voltage drops below the breakdown voltage, so the MPPC
gain is proportional to the overvoltage, and is obtained by dividing the charge from Eq. 4.3 by the elementarycharge (1.602 × 10−19 C ). Therefore, the MPPC gain can be obtained from the diﬀerence of the peaks between thepedestal and one photoelectron charge in the ADC distribution shown in Fig. 4.15.
There is a linear relation between the applied voltage and the single photoelectron gain. The breakdown voltage
can be measured as the voltage with zero gain. It is known that the breakdown voltage has relatively large
temperature dependence. This has been conﬁrmed for devices of various pixel sizes and temperatures ranging
from room temperature to liquid nitrogen temperature, and the temperature coeﬃcient has been measured to beapproximately 50 mV/K [41].

54

Chapter 4 Large technological prototype

Figure4.13 Image of photon counting by MPPC [40]Figure4.14 Example of the MPPC waveform[40]4.5 Silicon PhotoMultiplier (SiPM)

Figure4.15 Pulse height spectrum of MPPC [40]4.5.3 Photon detection eﬃciency, dark noise
One of the important properties of a photodetector is its Photon Detection Eﬃciency (PDE). The PDE of the
MPPC is determined by three factors: quantum eﬃciency (QE), ﬁll factor (ratio of photosensitive area to sensor
area), and probability of electron avalanche. MPPC has a higher QE than PMT due to the structure of the APD,
but the ﬁll factor is 50–70% due to the presence of insensitive regions around each pixel. The probability of anelectron avalanche depends on the overvoltage, so the PDE also depends on the overvoltage.
Even in the absence of photon incidence, dark noise is generated by an avalanche of electrons due to thermal
excitation. The size of the noise is identical to one photoelectron, but events equivalent to two or more photoelectrons
may appear due to the eﬀect of the cross-talk after-pulse described below.

4.5.4 Cross-talk, after-pulse
When an electron avalanche occurs in one pixel, photons with infrared wavelengths are generated, and they
may enter an adjacent pixel and trigger another electron avalanche. This is called a cross-talk. This results inthe measurement of more photoelectrons than actual incident photons. A trench structure between adjacent pixels
ﬁlled with tungsten can reduce the cross-talk.
The electrons in the electron avalanche are trapped in the lattice defects of the crystal in the ampliﬁed region,
and are re-emitted after a certain period of time, which can cause another avalanche. This is called an after-pulse.
The capture probability of electrons and the time constant of re-emission change depending on the depth of thepotential of the lattice defect. The understanding of this phenomenon is still in progress, but it can be reduced by55

Chapter 4 Large technological prototype

56
using a silicon wafer with a better quality.

4.5.5

Saturation

As the number of photons entering the MPPC increases, more than two photons enter one pixel. However, even
if more than two photons are injected into one pixel, the electron avalanche occurs only once. Therefore, as shownin Fig. 4.16, as the number of incident photons increases, the linearity with the number of excited pixels (numberof detected photons) becomes worse. Furthermore, if more photons than the number of pixels are incident, thephotons above the number of pixels cannot be detected, resulting in a constant output. Therefore, the number of
excited pixels can be expressed by the following equation.
Nf ired = Ntotal × {1 − exp(

−Nphotons × P DE)}
Ntotal(4.4)

To avoid the saturation, it is necessary to use MPPCs that have a suﬃcient number of pixels with a smaller pixel
pitch for simultaneously incident photons. The details in the saturation is discussed in Chapter 8.

Figure4.16 Saturation of MPPC [40]4.5.6

Small-pixel SiPM

The Sc-ECAL requires a large dynamic range because an electromagnetic shower forms the dense and thinshower and the BhaBha scattering causes the many shower in a close region. A large number of MIPs up to about
1,000 can be injected to one strip at a time, so a SiPM with a large dynamic range is required.
There has been an important development in the SiPM for the Sc-ECAL. Hamamatsu Photonics K.K. hasdeveloped an MPPC with a reduced pixel pitch down to 10 or 15 µm, which is quite useful to achieve the larger

4.6 ECAL Base Unit (EBU)

57

dynamic range required for the Sc-ECAL. The technological prototype uses both types of a pixel pitch of 10 and
15 µm (S12571-010P, S12571-015P[37]).
The latest small-pixel MPPCs have been further improved with trench structures between pixels. They reduce acrosstalk and dark noise, and improved photon detection eﬃciency [42]. The properties of small-pixel MPPCs areshown in Table 4.2.
Table4.2 Properties of small-pixel MPPCs by Hamamatsu Photonics K.K. [37][42]ModelS12571-010P

S12571-015P

S14160-1310PS

S14160-1315PS

Photosensitive area

1 × 1 mm

1 × 1 mm

1.3 × 1.3 mm

1.3 × 1.3 mm2

2

2

2

Pixel size

10 µm

15 µm

10 µm

15 µm

Number of pixels

10000

4489

16675

7296

Photon detection eﬃciency

10%

Ampliﬁcation rate

1.35 × 10

25%
5

2.3 × 1018%
5

1.8 × 1032%
5

3.6 × 105

Cross-talk probability

∼ 5%

∼ 15%

< 1%

< 1%

Fill facror

33%

53%

31%

49%

4.6 ECAL Base Unit (EBU)
The electronics system of the technological prototype includes the front-end readout electronics and back-end
Data AcQuisition system (DAQ) [43]. Each front-end board has a corresponding Data InterFace board (DIF), whichis responsible for powering the front-end board, distributing commands, and collecting data. All DIF boards areconnected to the back-end DAQ board, and all front-end boards are synchronized for triggering and data collection.
The back-end part is responsible for sending clock, trigger, conﬁguration commands, and uplink data collection
to the front-end boards. The front-end board also integrates temperature monitoring, charge scaling, and LED
scaling systems for a series of monitoring and scaling of the prototype system.

4.6.1 Front-end readout electronics
The SPIROC chip [44] is a dedicated chip for the SiPM multi-channel readout designed and developed by
OMEGA [31]. The latest version SPIROC2E is used in the technological prototype. SPIROC2E supports 36
channels of input, mixed analog and digital parts. Fig. 4.17 and 4.18 illustrate the structure of one analog channel
and the digital section of the SPIROC chip respectively. The analog section is responsible for input analog signal
ampliﬁcation, shaping and ﬁltering, and charge and time sampling. The ADC part uses a 12-bit Wilkinson ADC
to convert the shaped and ampliﬁed signal. The DAC is mainly responsible for adjusting the SiPM bias voltage for
SiPM temperature compensation, and setting the trigger threshold and gain automatic switching threshold. The
digital section is responsible for data packing and caching, generating the necessary ﬂag bits, and writing the chip
conﬁguration registers and data transfer and communication.
Table 4.3 shows the main parameters of the SPIROC2E chip. SPIROC2E features large dynamic range, low
noise, low power consumption, high accuracy, and a large number of readout channels. The SPIROC2E chip has
self-triggering and forced-triggering modes. The latter mode can further reduce power consumption because of
the long interval between ILC collisions, so that the analog part of the readout electronics can be powered down
during the analog-to-digital conversion and data transfer until the next bunch train. In addition, the 16 instanceChapter 4 Large technological prototype

58

Figure4.17 One analog channel structure of the SPIROC chip [44]Figure4.18 Digital section structure of the SPIROC chip [44]buﬀer depth per channel are speciﬁcally designed for the ILC collision mode.
Each detection layer has 210 SiPMs, and all SiPMs are readout by a cascade of 6 SPIROC2E chips, with the lastchip’s 6 channels left idle. Each chip readouts the SiPM at the corresponding location according to the principleof the shortest alignment, and Fig. 4.19 shows the distribution of the readout channels for each chip. The power
module of the front-end board is placed on the DIF board, including the power supply for SPIROC2E and SiPM
high voltage. This design can reduce the power consumption and thickness on the front-end board, and the designof independent modules of the front-end board and data readout board is convenient for maintenance and operation.

4.6.2

Temperature monitoring system

The temperature variation aﬀects the properties of the SiPM such as the carrier mobility and the breakdown
voltage Vbr . The overvoltage Vover of SiPM is equal to the diﬀerence between the operation voltage Vop and thebreakdown voltage Vbr . When Vbr increases with increasing temperature and Vop is kept constant, Vover decreases.

4.6 ECAL Base Unit (EBU)59
Table4.3 Performance parameters of SPIROC2E [44]Input signal polarity+

Trigger

Self-triggering and forced-triggering

Number of channels

36

Dynamic range

2000 times

Shaping time

25–200 ns

Signal output

Charge and time

Bias voltage adjustment

0–4.5 V (8 bit)

ADC bit widths

12 bitPower consumption∼8 mW per channel (continuous operation mode)

Incident buﬀer depth

16

Figure4.19 Distribution of ASIC readout channels

The gain and PDE of SiPMs are proportional to Vover . It is necessary to control the operating temperature of
SiPMs within a certain range and monitor the temperature for the correction of the temperature dependence of thegain and the energy response of SiPMs.
The overall power consumption of the front-end readout electronics is ∼60 W/h. The two major sources of theheat dissipation in the front-end electronics are the SPIROC2E chip on the EBU board and the high-voltage chipon the DIF board. The temperature distribution of the front-end board is related to the location of the chips, and the
SiPMs are soldered at diﬀerent locations on the front-end board, so it would be too much to install a temperature
sensor for each SiPM location. It is possible to measure the temperature at several locations and calculate thetemperature at each SiPM location by a special reconstruction algorithm [45]. Then the SiPM gain can be corrected
oﬄine or be compensated online by adjusting the operating voltage. Each EBU is equipped with 16 temperatureChapter 4 Large technological prototype

60

probing chips soldered at several locations, as shown in Fig. 4.20, covering mainly around the devices with large
heat generation and the edges of the whole EBU. Each temperature probing chip can measure from 0 ◦ C to 85 ◦ Cwith an accuracy of ±0.1◦ C.

Figure4.20 Distribution of 16 temperature probe chips on EBU

4.6.3

Electric scaling system

The SPIROC2E has both high and low gain modes. The high gain mode is used when the input signal is small
and the low gain mode is used when the input signal is large. Each SPIROC2E chip has a probe pin that canbe connected to an external input signal, and the chip’s internal conﬁguration allows to achieve scaling of allelectronics readout channels. The step voltage signal ∆V is converted to a charge Q = Ct × ∆V on the seriescapacitor Ct , allowing the front-end electronics readout system to be scaled by the analog signal input, commonlyreferred to as electrical scaling. The equivalent input capacitance of the preamp is about 16.5 pF and the external
resistance to ground is typically 100 Ω. The corresponding choice of capacitance of 18 pF yields a decay timeτ ∼ 3.5 ns of the scaled signal, which basically matches the signal waveform characteristics of a SiPM. The

digital-to-analog converter (DAC) provides an output voltage of 0–2.5 V to six ampliﬁers, which is then converted
by 18 pF capacitors to a charge similar to that of the SiPM signal waveform.

4.6.4

LED scaling system

Each strip is equipped with an LED for gain calibration and monitoring. Fig. 4.21 shows the circuit schematic of
the LED scaling system. Because not all channels can be covered by a single driver, the 210 channels are divided

4.7 Construction

61

into 14 groups and the scale of each group is selected by a selector switch. By adjusting the signal strength of thedriver circuit, the bias voltage on the LEDs can be controlled. The LEDs can be turned on and oﬀ by using two
NMOS onsets at the ends of each LED to generate light pulses with a width of less than 10 ns.

Figure4.21 Circuit schematic of LED narrow pulse scale system

The LED is located at a distance of 5.26 mm from the SiPM in a hole punched on the PCB board as shown in
Fig. 4.22. The LED is inverted and welded to the back of the PCB board, and the ESR has also made a hole inthe corresponding position. The light from the LED is transmitted in the scintillator to the SiPM surface. The
wavelength of LED is ∼400 nm, which matches with the peak wavelength of the SiPM measurement spectrum.
SiPM
Scintillator
PCB
LED

Figure4.22 LED position for one channel

4.6.5 Data Acquisition System
SiPM type

S12571-015P

S12571-010P

S12571-015P

Double-side

The back-end data acquisition system of the technological prototype includes a DAQ board,
FELIX
readout
layer acquisition
LayerID0
1 diagram2
3 of
4 the electronic
27 28
29 system
30 31of the prototype, includingcard and server. Fig. 4.23 shows
the schematic
readout

the main functions of each module and the upstream and downstream logic. The DAQ board is connected to the 30
front-end DIF boards via HDMI cable. Its main functions are: (1) aggregating transmission data from the DIFs;…

(2) distributing clocks and commands synchronously to the DIFs; (3) receiving external trigger information andfan-out to the DIFs after logical processing; and (4) communicating with the back-end FELIX and uploading data.
FELIX is a data acquisition system designed for ATLAS upgrade [46] with high bandwidth and high throughput
Detection
layer data acquisition systems for complex detector systems in next-generation
scalability to meet the needsof back-end
layeracquisition card and the DAQ board are connected by two opticalhigh-energy physics experiments. Absorber
The FELIX

ﬁbers, and their functions are: (1) DAQ link processing; (2) data routing; and (3) data exchange with the server.

4.7 Construction
This section gives the fabrication and assembly of the detection layer, and the assembly and commissioning of
the complete technological prototype in conjunction with the data acquisition system.

2

Chapter 4 Large technological prototype

62

Figure4.23 Schematic diagram of the readout system

4.7.1

Production of detection layer

The detection layer consists of the following components: scintillator strip, reﬂective ﬁlm, SiPM, and electronics.
Fig. 4.24 shows the ﬂow of the detection layer fabrication. After the production of the electronics board and thesoldering of the SiPMs, the electronics test and the SiPM and LED test are performed to ensure that all devices
are working properly. In addition, all front-end boards are tested in a temperature-controlled room for 48 hours
at 50 ◦ to ensure the long-term stability of all front-end boards. The left in Fig. 4.24 shows the strips wrappedwith the ESR ﬁlm. All strips are made of several large 2 mm thick BC-408 plastic scintillator plates cut into
5 mm × 45 mm × 2 mm scintillator strip and a dimple for coupling to the SiPM is machined on the bottom of the
strip. The reﬂective ﬁlm required to package the strip is made from 3M ESR ﬁlm, cut to the size of the strip withthe corresponding perforation for the SiPM and LED. After the strip is wrapped with the ESR ﬁlm, 10% of eachbatch is randomly selected for the light yield test to ensure that the strips produced in each batch meet the lightyield requirements of the prototype. The strips are assembled and adhered to the EBU board using an epoxy resin
adhesive. The right in Fig. 4.24 shows the complete detection layer. A total of 30 detection layers re fabricated forthe prototype, and 2 additional layers with the SiPM double-side readout are also fabricated, discussed in Appendix
A.
Fig. 4.25 shows the components of a super-layer and Fig. 4.26 shows the assembled super-layer. The two
detection and absorber layers are assembled into a super-layer. All detection layers are assembled in a clean room.
A total of 15 super-layers were produced, and the contents of the super-layers are shown in Table 4.4. An additional
super-layer with the SiPM double-side readout was also produced, and the details are discussed in Appendix A.
Table4.4 Items of super-layers

Super-layer

Number of modules (EBU)

SiPM

Strip length

Strip material (process)

Bottom-side readout 1

12 (24)

S12571-010P

45 mm

BC-408 (casting)

Bottom-side readout 2

3 (6)S12571-015P

45 mm

BC-408 (casting)

Double-side readout

1 (2)S12571-015P

90 mm

Polystyrene (injection)

4.7 Construction

63

Figure4.24 Plastic scintillator strips wrapped with the ESR reﬂective, the outside of ESR is sealed with 3M
insulation tape (left). Single-layer board after assembling scintillator strips (right)

Figure4.25 Components of a super-layer

4.7.2 Assembly and integration of prototype systems
The super-layer is the basic unit of the prototype and each super-layer can be individually assembled anddisassembled in a very ﬂexible way to facilitate diﬀerent tests. After the fabrication, each super-layer is inserted
one by one into the corresponding slot and screwed to the a mechanical frame. Fig. 4.27 shows the arrangementof the detection layers for each type of SiPM. The 15 µm-pitch SiPM (S12571-015P) has lower dynamic range
compared to the 10 µm-pitch SiPM (S12571-010P), so the detection layers with S12571-015P are placed on theChapter 4 Large technological prototype

64

SiPM
Scintillator
PCB
Figure4.26 Assembled super-layer unitsLEDﬁrst and last layers of the prototype where the saturation eﬀect is small. The fan cooling system is assembled on
the outermost side of the mechanical structure, with a set of 120 W cooling systems on the left and right sides
emitting air in the same direction. The overall dimensions are about 796 mm × 428 mm × 538 mm, weighing
more than 200 kg as shown in Fig. 4.28.
SiPM type

S12571-015P

S12571-010P

Double-side

S12571-015P

readout layer
LayerID

0

1

2

3

4

27

28

29

30

31

…

Detection layer
Absorber layer
Figure4.27 Layout of the detection layers corresponding to the SiPM types of S12571-015P (15 µm-pitch)and S12571-010P (10 µm-pitch)

The main body of the technological prototype can be separated, and the front-end board is powered by connecting
a power source outside the prototype, and the DAQ board is connected to the server. Fig. 4.29 shows the jointcommissioning of the prototype with the data acquisition system. All parts of the prototype are functioning
properly, and more tests to evaluate the key performance of the technological prototype are presented from the next
chapter.

4.8 Commissioning
The purpose of this study is to demonstrate the performance of the Sc-ECAL. This Sc-ECAL technologicalprototype is the ﬁrst large-scale technological prototype for the PFA ECAL, and the demonstration of its performanceis crucial toward the construction of the actual detector. By calibrating the key parameters of the prototype and4.8 Commissioning

65

Figure4.28 The internal structure and the appearance of the main part of the assembled prototype

Figure4.29 Joint commissioning of the prototype and data acquisition system

checking their stability, it can be veriﬁed that the Sc-ECAL can be operated stably in the actual detector. By
demonstrating the performance such as the position resolution, shower scalability, and jet energy resolution, it canbe conﬁrmed that the Sc-ECAL meets the requirements for the PFA ECAL required for the precision physics at
the future Higgs factory.
To achieve these objectives, a four-step study is conducted:• Calibration and stability check of the key parameters of the technological prototype• Performance evaluation of the technological prototype• New method for the saturation correction

Chapter 4 Large technological prototype

66• Evaluation of the jet energy resolution

Please note that the analysis uses 30 standard detection layers, and does not use the two detection layers with the
SiPM double-side readout due to the diﬀerent conﬁguration.
At the ﬁrst step, the key parameters such as the SiPM gain and MIP response are calibrated channel by channel
using the LED and cosmic-ray. The stabilities of these parameters are also checked by taking the long-term
calibration run. By looking at the stability of each channel and each layer, it can be veriﬁed whether the actual
detector can be operated stably.
At the second step, the performance of the technological prototype is evaluated. The position resolution isevaluated by the straight track of cosmic-ray events, and make sure it meets the requirement of the 5 mm ×
5 mm cell size for the PFA ECAL. Because the test beam experiment was cancelled due to the COVID-19, theperformance using the electromagnetic shower is evaluated by the cosmic-ray induced showers. The performanceis compared with the Monte Carlo simulation, and it is veriﬁed that the prototype is working as expected.
At the third step, a new method for the saturation correction is developed. The saturation is an issue at the
Sc-ECAL because the Sc-ECAL has many pile-up hits from the dense EM shower. A novel measurement method
and modeling of the SiPM saturation is developed for more accurate correction of the saturation for the use of thescintillator and SiPM. This method makes an impact on the saturation correction for not only the Sc-ECAL, butalso other detectors using the scintillators and SiPMs.
At the ﬁnal step, the jet energy resolution is evaluated using the full simulation of the ILD detectors. The
parameters of the Sc-ECAL obtained by the technological prototype, and the saturation behavior based on the new√
method are used in the evaluation. It is conﬁrmed that the jet energy resolution of 3 − −4%/ E(GeV) required
for the precision Higgs physics is achievable with the Sc-ECAL. We will also discuss the usefulness of the new
saturation model and the comparison of SiPM types to contribute to the design decision of the actual detector.

67

Chapter 5

Commissioning and Reconstruction
The Sc-ECAL technological prototype has been constructed, then is commissioning. The commissioning
includes the LED test and cosmic-ray test, which can be used to calibrate the key parameters of the prototype andevaluate the performance of the Sc-ECAL. The calibrations for the key parameters of the Sc-ECAL such as the
SiPM gain and MIP response should be performed to make sure the detector is working property and establish
how to operate the actual detector. The algorithm for the reconstruction is developed and applied to the analysis of
the cosmic-ray data.
This chapter shows the ﬂow of the commissioning, calibration procedure, and the reconstruction for the cosmicray test. The procedures of the calibration and the algorithm of the reconstruction can be applied to the actual
detector as well. The results of the calibration and performance evaluation are shown from the next chapter.

5.1 Calibration and commissioning test
The completed technological prototype needs the detector calibration and performance test. The calibrations forseveral parameters are necessary to reconstruct the physics event. After the calibrations, the performance of the
prototype should be checked. This section gives the calibration procedure and the tests for the calibrations andperformance evaluation.

5.1.1 Calibration procedure
The raw signal from the prototype is based on the ADC count. The signal ADC count should be converted tothe energy using several calibration factors. The calibration for the prototype is performed in 5 steps:• Gain calibration• Inter-calibration• Cross-talk and after-pulse calibration• Pedestal calibration• MIP response calibration
As the ﬁrst step, the per-channel response is converted to the number of photoelectrons using the single photoelectron
gain of the SiPM. The ADC-photoelectron conversion factor, cgain , is determined by the single photoelectron charge
measured by the LED light. After the calibration, the non-linear response of the large signal can be corrected.
The saturation of the SiPM, discussed in Chapter 8, is a function of the number of photoelectrons, so the signal

Chapter 5 Commissioning and Reconstruction

68

converted by the cgain can be used to the correction of the SiPM saturation.
As the second step, the charge injection of the electronics is performed. The cgain is measured using a highgain ampliﬁer to suﬃciently separate the photoelectron peaks, whereas the physics data acquisition uses a low gain
ampliﬁer due to the wide dynamic range required. The inter-calibration factor, cinter , is used to convert the low
gain signal to the unit of high gain. The cinter is measured as the ratio of the amplitudes of the response to LED
light with the high gain to the low gain settings.
As the third step, the probability of the cross-talk and after-pulse PCT AP is measured. The SiPM saturation
contains the eﬀect of the cross-talk and after-pulse. By determining the CTAP probability in each channel using
the LED light, the SiPM saturation can be corrected more accurately.
As the forth step, the pedestal is subtracted from the signal ADC counts. The pedestal, cpedstal , can be obtainedby the mean of the distribution of the events without signal.
As the ﬁfth step, the per-channel response is normalized using the response to the minimum ionized particle(MIP) in the cosmic-ray data. The calibration factor, cM IP , is expected as the most probable value (MPV) of the
Landau distribution obtained by the cosmic-ray. The injection angle of the cosmic-ray is corrected to the verticalincidence. After this calibration, the detected energy of the detector is expressed in units of MIP.
Using these calibration factors, a signal in channel i for the physics event can be written by:() cgaincinter
(T )
i
i
Acorr
[MIP] = FP−1
(Ai [ADC](T ) − cpedestal ) gainiinter cM IP (T )CT AP
cci (T ) ii

(5.1)

where Ai [ADC](T ) is the uncorrected signal of the cell in ADC counts at temperature T , and F −1 with a parameter
PCT AP is the function for the saturation correction. Some calibration factors are determined as a function of
inter

ci
temperature. The (Ai [ADC](T ) − cpedestal ) cgain
converts the uncorrected signal in ADC counts to the signal in(T )icgain (T )iconverts
units of the number of photoelectrons. The FP−1
corrects the saturation of the SiPM. The cintercM IP (T )
CT AP
i

i

the signal in the number of p.e. after the saturation correction to the corrected signal in units of the number of
MIPs.
The sum of these signals is the energy of the physics event in units of MIP, which is written by
Ereco [MIP] = Σstrip Acorr
[MIP]
i

(5.2)

The average value of Ereco as a function of incident beam energy represents the calibration of the energy scale in
GeV.

5.1.2

LED test

For the ﬁrst to third calibration steps, cgain , cinter , and PCT AP are determined using the LED test. The gain and
CTAP calibration need the LED light with low intensity in order to separate the photoelectron peaks, while theinter-calibration needs some runs with several light intensities in order to obtain the ratio of the low gain and highgain. The LED scan from low light intensities to high intensities is performed.
The LED test is performed in laboratory. The LED driver gives the bias voltage to the LED, then the LED outputs
a narrow blue light pulse. The SiPM detects the LED light coming through the strip. The data is taken by theforced-triggering from the driver. The scan with several light intensities can be done by changing the bias voltage
from the driver. The LED test is performed once a day over a month to check the stability of each parameter.

5.1 Calibration and commissioning test

5.1.3 Cosmic-ray test
For the forth and ﬁfth calibration steps, cpedstal and cM IP are determined by the calibration using cosmic-ray
muons. In order to determine these factors and check the their stabilities, the long-term cosmic-ray test over 3
months is performed.
The longterm cosmic-ray test is performed in laboratory. The prototype is rotated by 90◦ as shown in Fig. 5.1.
The cosmic-ray data is taken by the coincidence of Layer 1 and Layer 29, whose layers are located at the top andbottom of the prototype.

Figure5.1 Prototype is rotated by 90◦ for cosmic-ray test

The threshold is set for each SPIROC2E chip as ∼0.5 MIP ADC counts. When a channel exceeds the threshold,the data of 36 channels belonging to the same chip are stored in one memory cell. Usually, if the 16 memory cells
equipped in a SPIROC2E chip are full, the data is extracted from the chip and sent to the PC. However, the rate ofcosmic-ray events is very low ∼ 0.25 Hz, so the memory cells are refreshed every 4 ms. The master clock sends
the time origin and clock to each layer. If there are hits beyond the threshold at the trigger layers of Layer 1 and
29 in 4 ms refresh period, the data stored at the memory cell at that time are extracted from all chips with the hitsbeyond the threshold. The data includes the bunch-crossing ID, ADC counts in the high gain and low gain mode,
TDC counts, temperature, and so on.
The cosmic-ray tests are carried out over 3 months. The event rate is ∼ 16 events per minute. ∼ 2000 hits arecollected at each channel. The temperature is monitored during the cosmic-ray tests by the temperature sensors
equipped on the EBU.

69

Chapter 5 Commissioning and Reconstruction

70

5.1.4

Test beam experiment

The detailed calibration and performance of the prototype must be evaluated by the test beam experiment. The
MIP calibration is also performed using the muon beam, and the conversion from the signal in units of MIP toabsolute energy scale can be calibrated using the electromagnetic shower. The energy linearity can be evaluatedby the electron beam with several energies, and the energy resolution is evaluated by the deviation of the detectedenergy with high-energy electron.
The test beam experiment for the Sc-ECAL prototype was planned in August 2020 at Deutsches ElektronenSynchkrotron (DESY), but postponed to February 2021 due to the COVID-19 pandemic, and the test beam in
February 2021 was also canceled due to the pandemic. The test beam experiment is currently planned using theelectron beam at the Beijing Synchrotron Radiation Facilities (BSRF) [47], but the schedule and beam quality are
not clear.
The performance is evaluated using the electromagnetic showers induced by the cosmic-rays. The shower events
are searched for in the cosmic-ray data, and some properties of the showers such as the proﬁle and the total energies
are compared with the Monte Carlo simulation.

5.2 Reconstruction for straight track
The reconstruction algorithm for the straight track is developed. The straight track can be used to eliminate thenoise hits and calibrate the MIP response. The straight-track reconstruction for the cosmic-ray is performed in four
steps:• Pre-selection• Strip Splitting Algorithm (SSA)• Cone clustering• Track ﬁtThis section describes each step in detail. After the reconstruction, the signal ADC counts are corrected using theangular information of the track.

5.2.1

Pre-selection

At the pre-selection step, the cuts for the total number of layers and channels with his are performed. Fig. 5.2
shows the cut of the noise events and the cosmic-ray events. The peak around 3 layers is caused by the dark noiseof the SiPM and the accidental trigger. The events with more than 22 layers with hits are selected, because theevents, whose total hit layers is small, may not come from the cosmic-ray events, but the dark noise from the SiPMs
or the accidental triggered events. The events with more than 64 channels with hits are eliminated, because theevents with many hits more than 3 hits per layer have too many noise hits.

5.2.2

SSA

As discussed in Section 4.2.1, the SSA is used for the analysis of the prototype data. The pitch of each channel is
5.3 mm × 5.3 mm, which is slightly larger than the size of the strip, due to the gap between the strips for machining5.2 Reconstruction for straight track71

Figure5.2 Distribution of the total number of the hit layers

accuracy and reﬂector. The edge pop oﬀ due to 5.3 × 9 = 47.7 > 45.4, and the strip cannot be split by just 9 cells.
Then the edge processing is implemented.
As shown in Fig. 5.3, the orthogonally aligned strips have partially overlapped area at the strip edge. This areais split as one independent cell. The position of the cell is set as the center of the overlapped area, and the energy
weight from the upper or lower layer is weighted according the overlapped length. The strip is split by 10 cells
including the edge, and the implementation of the SSA to the prototype is done.
Overlapped length

5.3 mm45.4 mmCenter of the cell

3

Figure5.3 Edge processing of the SSA

5.2.3 Cone clustering
The cone-based clustering algorithm is used to ﬁnd the cosmic-ray hits and eliminate the noise. The overview
of the cone clustering is shown in Fig. 5.4. The clustering starts from the top layer, and the cone is spread from theinitial hit to the next layer or the layer after that. The cone is spread in the initial direction of the injection particle.

Chapter 5 Commissioning and Reconstruction

72

If the hits lie within the cone, the hits are added to the cluster. The next cone is spread from new cluster hits tothe next layer or the layer after that, then ﬁnd the next cluster hits within the cone. The cone algorithm repeats thisprocess. The isolated hits due to the random noise are eliminated by this algorithm.

Figure5.4 Overview of the cone algorithm [48]5.2.4Track ﬁt

A track ﬁtting is performed for the hits after the SSA and the clustering in x and y axis using TMinuit, and thetrack information such as the slope and intercept is obtained. The clustering hits still have noise hits, so the track ﬁt
is performed iteratively. First, the all hits are ﬁtted linearly, and the track is obtained. If the residual of the hit, thediﬀerence between the hit position and the track, is smaller than the threshold, the hit is regarded as the cosmic-ray
hit. If the residual is larger than the threshold, the hit is regarded as the noise. Then, the ﬁt is performed using
the hits regarded as the cosmic-ray hit, and the procedure is repeated lowering the threshold step-by-step. The
threshold is changed from 47.5 mm to 7.5 mm in 5 mm pitch.
Fig. 5.5–5.7 show the event display of the cosmic-ray after the pre-selection, after the SSA, after the clusteringand track ﬁt, respectively. The SSA works properly and the strip is split by the small cells. The noise hits still
remain after the SSA, while the noise hits are subtracted after the clustering and track ﬁt. The hits belonging thecosmic-ray track are successfully clustered and the track is obtained.

5.2.5

Angular correction

For the MIP response calibration, the signal ADC count at each hit is corrected by the injection angle using
the track information. When the cosmic-ray is incident on the strip with an angle, the energy deposit increases
compared to the case of perpendicular incidence. The path length in the strip can be calculated with the track angle,
and the ADC count is corrected by the path length to the strip thickness (2 mm). Fig. 5.8 shows the distributionsof the signal ADC counts with and without the angular correction. The peaks of the distribution are shifted tolower ADC counts, and the spreads become smaller after the correction. The angular correction is applied at each5.3 Reconstruction for shower event

73

0

0

50

50
Layer position [mm]

150

200

250

100

150

200

250

50

0
−50
X position / mm

−100

iti

100

on

/m

100
50
050
−−100

po
s

−100

iti

0
−50
X position / mm

po
s

50

Y

100

on

/m

100
50
050
−−100

m

300

m

300

Y

Layer position [mm]100

Figure5.5 Event display of the cosmic-ray after the pre-selection

0

0

50

50
Layer position [mm]

150

200

150

200

250

m

300

100
50
−050
−100 −100

/m

50

0
−50
X position / mm

n

100

tio

tio

si

0
−50
X position / mm

po

50

Y

100

n

/m

100
50
−050
−100 −100

si

m

300

po

250

100

Y

Layer position [mm]100

Figure5.6 Event display of the cosmic-ray after the SSA

hit and each event.

5.3 Reconstruction for shower event
The test beam experiment was cancelled, so the performance of the Sc-ECAL for the electromagnetic showers
is evaluated using the cosmic-ray showers. The reconstruction for shower events is performed in three steps:• Calibration• SSA• Shower searchChapter 5 Commissioning and Reconstruction

74

0

0

50

50
Layer position [mm]

150

200

150

200

250

50

0
−50
X position / mm

on

/m

100
50
050
−100
−
−100

iti

iti

100

po
s

0
−50
X position / mm

50

Y

100

on

/m

100
50
050
−100
−
−100

m

300

m

300

po
s

250

100

Y

Layer position [mm]100

Chip0_ Chn0
No correction

220

Angular correction

200

EntriesMean
Std Dev

4200
786.6
345.2

EventsEventsFigure5.7 Event display of the cosmic-ray after the clustering and track ﬁt

Chip1_ Chn080

EntriesMean
Std Dev

No correction
Angular correction70

Chip0_ Chn1

180

EntriesMean
Std Dev

160

4200
712.1
317.9

140
120

865
179.1
98.18

Chip1_ Chn160

EntriesMean
Std Dev

50

865
169.8
93.08

40

100
30

80
60

20

40
10
20
0

0

500

1000

1500

2000

2500

3000
ADC

0

0

200

400

600

800

1000
ADC

Figure5.8 The distribution of the signal ADC counts at one channel of 15 µm-pitch SiPM (right) and 10 µmpitch SiPM (left). The black shows the distribution without any correction, and the red shows the distribution
after the angular correction.

5.3.1

Calibration

The calibration procedure follows Section 5.1.1, but in case of the cosmic-ray shower, the saturation correctionof the SiPM is not implemented because the light yield is too low to be aﬀected by the saturation. The temperaturecorrection is implemented in each hit, and the calibration is performed as:
)
(
1
Acorr
[MIP] = Ai [ADC](T ) − cpedestal inter M IP
i
(T )
ci
ci

(5.3)

corr
Atemp
[MIP] = (1 + (Ti − Tref )dM IP )Acorr[MIP](T )
i
i

(5.4)

where the temperature correction described in the second line is discussed in Section 6.6.3.
The SSA is the same as the track ﬁnding discussed in 5.2.2.

5.3 Reconstruction for shower event75

5.3.2 Shower search
The shower search is performed by combining the cone clustering and applying cuts to the cluster hits. The
angle of the incident particle is important to search for the shower event, so the ﬁrst few layers are used to calculate
the incident angle. The procedure of the shower search is as follows:• Cone clustering with no incident angle• Shower identiﬁcation• Linear ﬁt before the shower start• Cone clustering with incident angle• Shower identiﬁcation
Fig. 5.9 shows the scheme of the shower identiﬁcation. At ﬁrst, the cone clustering with no injection angle (thezenith angle is 0 degree, vertical to Prototype) is performed. Using the cluster hits, the number of hits and theenergies are summed by each layer. If 9 or more hits and 1.5 MIP or more energy are detected in three consecutive
layers, the event is recognized as the shower event. The shower start layer is set as the one layer before the cut of
the three consecutive layers.
After the ﬁrst shower identiﬁcation, the linear ﬁt is performed using the hits before the shower start. In order tocalculate the incident angle, the events that the ﬁrst 6 layers are always linear (the sum of hits is less than 9) areselected and ﬁtted by the TMinuit. Then, the cone clustering with the incident angle is performed using the angleof the ﬁtted linear track. The shower identiﬁcation is performed again, then the shower events are extracted.
Shower start
Shower start

Linear track

Shower(<9 hits)(>=9 hits)
Linear track

Shower(<3 strips)(>=3 strips)

Figure5.9 Scheme of the shower search after the SSA (left), and before the SSA (right) for comparison.

Fig. 5.10 shows the event display of the shower events found by the shower search algorithm. The same shower
search is performed by the simulation with the same setup of cosmic-ray test. Fig. 5.11 shows the the event displayof the shower events by the simulation. About 5 thousand shower events are obtained in the cosmic-ray data, andabout 13 thousand events are obtained in the simulation. The performance evaluation using the cosmic-ray shower
is discussed in Sec. 7.4

Chapter 5 Commissioning and Reconstruction

76

CR data

CR data
8

4.5
0

0
50

3

150

2.5
2

200
1.5

Layer position [mm]Layer position [mm]100

Layer position [mm]

3.5

250

6

100

5

150

4

200

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250

2

300

1
100
50
0
m
0
−50
n/m
−100−100 positio
Y

1
300
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50
0
X position

−50
/ mm

0.5
100
50
0
m
0
−50
n/m
−100−100 positio
Y

100

50
0
X position

−50
/ mm

Layer position [mm]

7

4
50

Figure5.10 Event displays of the shower events in the cosmic-ray data. The color bar shows the number of MIPs.

26

Simulation

Simulation
5

8

0

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7

50

6

100

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150

4

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300

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n/m
−100−100 positio
Y

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150
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200
250

Layer position [mm]Layer position [mm]100

Layer position [mm]

50

1
300
100

100

50
0
X position

−50
/ mm

50
0
m
−50
n/m
−100−100 positio
Y

0

100

50
0
X position

−50
/ mm

Figure5.11 Event displays of the shower events in the simulation. The color bar shows the number of MIPs.

32

Layer position [mm]477

Chapter 6

Calibration
According to the calibration procedure discussed in section 5.1, the key parameters for the Sc-ECAL are calibrated
in the LED test and cosmic-ray test. The calibrations in the LED test are as follows:• Gain calibration for SiPMs• Inter-calibration for electronics• Cross-talk and after-pulse calibration for SiPMs
The calibrations in the cosmic-ray test are as follows:• Pedestal calibration• MIP calibration
The temperature is monitored during the LED test and cosmic-ray test using the temperature sensors on the
EBU. The temperature correction for the MIP calibration is performed to eliminate the eﬀect of the temperaturedependence of the SiPM.
This chapter gives the results of the calibrations and temperature monitoring.

6.1 Gain
The signal ADC count is converted to the number of photoelectrons using the single photoelectron gain of the
SiPM. The ADC-photoelectron conversion factor, cgain , is determined by the gap of peaks of the ADC spectrumsat several photoelectrons using the LED light. After the calibration, the SiPM saturation at the large signal canbe corrected. The SiPM saturation, discussed in Chapter 8, is a function of the number of photoelectrons, so thesignal converted by the cgain can be used to the correction of the saturation.

6.1.1 Gain calibration
Fig. 6.1 and 6.2 show the typical ADC distributions with low LED intensity for 15 µm-pitch and 10 µm-pitch
SiPM respectively. The peaks of pedestal, one photoelectron, two photoelectrons are clearly separated, and ﬁtted
by the multi-gaussian. The gain calibration factor, cgain , is the interval of the peaks of the gaussians.
Fig. 6.3 shows the distributions of all channels for 15 µm-pitch (left) and 10 µm-pitch (right) SiPM. The
diﬀerence of the pixel capacitance of the SiPM causes the diﬀerence of the gain between 15 µm-pitch and 10 µmgain
pitch SiPM. The ratio of the gain (cgain
15µm /c10µm = 25.4/15.36 = 1.65) is consistent with the catalogue value

Chapter 6 Calibration

78
Entries

High-gain distribution (chn0, layer40, DAC2340)
t1_0_40_1
Entries
2934
Mean
477
Std Dev
36.53

120

100

80

60

40

20

0
300

350

400

450

500

550

600

650

700
ADC

Figure6.1 ADC distribution with low LED intensity for 15 µm-pitch SiPM. The red line is the ﬁt function
with the multi-gaussian.

Entries

High-gain distribution (chn1, layer44, DAC2380)
t0_1_44_2
Entries
2921
Mean
419.9
Std Dev
14.58

160
140
120
100
80
60
40
20
0
300

350

400

450

500

550

600

650

700
ADC

Figure6.2 ADC distribution with low LED intensity for 10 µm-pitch SiPM. The red line is the ﬁt function
with the multi-gaussian.

(2.30/1.35 = 1.70), so the per-channel cgain calibration is succeeded. The signal ADC counts can be converted to
the number of photoelectrons, and the correction of the SiPM saturation at high light yields can be applied.

6.2 Inter-calibration
The high-gain signal is necessary to measure the cgain using the well separated photoelectron peaks, whereas
physics data acquisition uses a low-gain signal due to the wide dynamic range required. The inter-calibration factor,
cinter , is used to convert the low-gain signal to the unit of high-gain. The cinter is measured for each channel as

the ratio of the amplitudes of the response to the signal with the high-gain to the low-gain settings.
The inter-calibration is performed with the three methods:• LED: LED scan with several light intensities• Cosmic-ray: Cosmic-ray data recording both the low gain and high gain6.2 Inter-calibration

79
Gain for 10um SiPM
gain15120

Entries

1680

Mean

25.39

Std Dev

2.646

100

Channels

Channels

Gain for 15um SiPM

gain10

500

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200

20

100

0

16

18

20

22

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26

28

30

32 34
Gain [ADC]

0

6

8

10

12

14

16

18

20

Entries

5040

Mean

15.36

Std Dev

1.345

22 24
Gain [ADC]

Figure6.3 Distribution with the gains for 15 µm-pitch (left) and 10 µm-pitch (right) SiPM.

• DAC: Directly injecting the test charge from the digital-to-analogue converter (DAC) to the SPIROC2E
This section gives the results of the inter-calibration with the three methods and the comparison between threemethods.

6.2.1 Inter-calibration for high-gain and low-gain
LED
The LED data is taken with varying the intensities of the LED light. The data with each intensity stores the ADC
counts with high-gain and low-gain settings. The inter-calibration factor, cinter , can be obtained by the ratio of the
ADC counts of high-gain to low-gain. Fig. 6.4 shows the typical 2D plot of the ratio of high-gain to low-gain. Eachpoint shows the mean of the gaussian of the ADC distribution for high-gain and low-gain at each LED intensity.
The high-gain preampliﬁer saturates over 3500 ADC counts, so the linear ﬁr is taken below 3500 ADC counts.
The slope of the linear function is the cinter .
Fig. 6.5 shows the distribution of the inter-calibration factors for all the channels. The per-channel cinter isobtained. The pitch of the LED light intensity is set as the ﬁnest setting, but the ﬁtting error is large due to few
ﬁtting points. 5 points can be used for the ﬁtting at Fig. 6.4, but some channels have fewer ﬁtting points. This
problem can be solved by updating the LED system with ﬁner pitch.
Cosmic-ray
In the cosmic-ray data, both the signal with high-gain and low-gain settings are recorded, and Fig. 6.6 shows
the typical plot of the ratio of high-gain to low-gain. The cinter is obtained in the same way as the LED method.
Fig. 6.7 shows the distribution of the inter-calibration factors for all the channels with cosmic-ray method. The
per-channel cinter is also obtained.
DAC
At the DAC method, the test charge from the DAC is directly injected into the SPIROC2E, and both the datawith high-gain and low-gain are recorded. Fig. 6.8 shows the typical plot of the ratio of high-gain to low-gain.
The cinter is obtained in the same way as the LED method. Fig. 6.9 shows the distribution of the inter-calibration
factors for all the channels with DAC method. The per-channel cinter is also obtained.

Chapter 6 Calibration

80
Low gain [ADC]

Ratio channel:0 layer:44
1000

900

800

700

600

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400

300

500

1000

1500

2000

2500

3000

3500
4000
High gain [ADC]

led

3000

Entries

6720

Mean

0.02635

Std Dev0.004057

Entries

EntriesFigure6.4 Typical 2D plot for ADC counts of high gain vs. low gain at one channel. The red line shows thelinear function ﬁtted until the ADC counts of high gain saturate.

3000

2500

2500

2000

2000

1500

1500

1000

1000

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500

0
0

0.005 0.01 0.015 0.02 0.025 0.03

000.035 0.04 0.045 0.05
LvH ratio

0.005 0.01 0.015 0.02 0.025

Entries

EntriesFigure6.5 Distribution of the inter-calibration factors for all channels with LED method.
1800
1600

Cosmic-ray
DAC

Entries

1200

LED
2500

cos
1400

3000

6720

Mean

0.02813

Std Dev

0.002042

1000

2000

1500

800
1000

600
400

500

Figure6.6 Typical200 2D plot for ADC counts of high gain vs. low gain with the cosmic-ray method.
000.005 0.01 0.015 0.02 0.025 0.03

0.035 0.04 0.045 0.05
LvH ratio

000.005 0.01 0.015 0.02 0.025

1000

1000

500

500

0
0

0.005 0.01 0.015 0.02 0.025 0.03

000.035 0.04 0.045 0.05
LvH ratio

0.005 0.01 0.015 0.02 0

6.2 Inter-calibration
Entries

Entries

81

1800
1600

Cosmic-ray
DAC

Entries

1200

LED
2500

cos
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6720

Mean

0.02813

Std Dev

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2000

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800
1000

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400

500
200
0
0

0.005 0.01 0.015 0.02 0.025 0.03

0.035 0.04 0.045 0.05
LvH ratio

000.005 0.01 0.015 0.02 0

Figure6.7 Distribution of the inter-calibration factors with cosmic-ray method.

Figure6.8 Typical 2D plot for ADC counts of high gain vs. low gain with the DAC method.

6.2.2 Comparison with three methods
Fig. 6.10 shows the cinter distributions with three methods. The mean values of the distributions with the LED
and cosmic-ray methods almost match, but the mean of the DAC method is apart from the others. The waveform of
the test charge injecting from the DAC to the SPIROC2E is diﬀerent from the SiPM waveform, and the bandwidthof the high-gain circuit depends on the waveform. These diﬀerences lead to a diﬀerence in the ampliﬁcation factor.
The spread of the distribution of LED method is larger than that of the cosmic-ray method, because some of thechannels have only few points in the linear region. Therefore, the results with the cosmic-ray method is suitable,
but the improvement of the LED system and the waveform calibration for the DAC method is necessary toward theoperation at the actual detector.

Chapter 6 Calibration
led
Entries6720

led0.02635

Mean
Entries
Std
Dev
Mean

6720
0.004057
0.02635

Std Dev0.004057

Entries
Entries

82
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3000

2500
2500

2000
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dac

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1500

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Entries
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Mean

6720
0.001172
0.03348

1000

Std Dev0.0011726720

dac 0.03348

1000

500
500

0
0
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0

25 0.03

0.035 0.04 0.045 0.05
LvH ratio
25 0.03 0.035 0.04 0.045 0.05
LvH ratio

0.005 0.01 0.015 0.02 0.025 0.03
0.005 0.01 0.015 0.02 0.025 0.03

0.035 0.04 0.045 0.05
LvH ratio
0.035 0.04 0.045 0.05
LvH ratio

Entries
EntriesFigure6.9 Distribution of the inter-calibration factors with DAC method.

cos

3000

2500

6720

2500

Mean
Entries
Std Dev
Mean

0.028136720
0.002042
0.02813

2000

Std Dev

0.002042

Entries

cos

led

3000

LED

EntriesLED
Cosmic-ray

Mean
Entries
Std Dev
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Cosmic-ray
DAC

Std Dev cos
0.004057

DAC
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led

Entries

6720
0.026356720
0.004057
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cos

6720

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0.028136720
0.002042
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Std Dev

0.002042

dac

1500

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1500

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Entries
Std Dev
Mean

0.033486720
0.001172
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1000

Std Dev0.001172

dac

6720

1000

500
500

25 0.03

0.035 0.04 0.045 0.05
LvH ratio
25 0.03 0.035 0.04 0.045
0.05
LvH ratio

00000.005 0.01 0.015 0.02 0.025 0.03
0.005 0.01 0.015 0.02 0.025 0.03

0.035 0.04 0.045 0.05
LvH ratio
0.035 0.04 0.045 0.05
LvH ratio

Figure6.10 Distributions of the inter calibration factor with the LED method (blue), cosmic-ray method (red),and DAC method (black).

6.3 Cross-talk and after-pulse
The combined probability of cross-talk and after-pulse, PCT AP , is measured using the LED data. The SiPM
saturation is aﬀected by some SiPM properties including the cross-talk and after-pulse. By determining the CTAP
probability in each channel using the LED light, the correction for the saturation can be made more accurately.

6.3.1

Probability of CTAP

The CTAP probability, PCT AP , can be measured using the data with low LED intensity [49] like Fig. 6.1 and6.2. It is assumed that the distribution of LED light at low light intensity follows a Poisson distribution. The

6.4 Pedestal

83

probabilities for 0 photon (pedestal) and 1 photon at Poisson are written by:
P (0) = e−µ P (1) = µe−µ(6.1)

The cross-talk and after-pulse don’t aﬀect the P (0), but decrease the P (1). The actual probability of 1 photon is:
P ′ (1) = (1 − PCT AP )µe−µ
Gain: One photo-electron charge (15-um SiPM)(6.2)

Gain: One photo-electron charge (10-um SiPM)

1680
25.4
2.756

EntriesMean
Std Dev

entries

entries

Using theseequations, the CTAP probability PCT
gain15H
AP can be written by:120

gain10H

P ′ (1)PCT AP = 1 −400
P (0) log P (0)

100

5040
14.54
1.739

EntriesMean
Std Dev

500

(6.3)

80

The ADC distribution at low LED intensity is ﬁtted by the multi-gaussian,and the P (0) and P ′ (1) are calculated
300
60
by the integralof the gaussian of 0 and 1 photon. Then, the PCT AP calibration can be done by analyzing the LED

data with40low light intensity.

200

Fig. 6.11 shows the PCT AP distributions with 15 µm-pitch and 10 µm-pitch SiPM. The measured PCT AP of
100

20

25% at 15 µm-pitch SiPM and 12% at 10 µm-pitch SiPM is in agreement with the catalogue value of the cross-talk
0
0SiPM, and the typical after-pulse probability of lessprobability;
15 µm
and
0 14%
5 at 1015 -pitch
20 SiPM2530 5%
35 at 1040 µm-pitch 0
5
10
15
20
25
30
35
40

Eventsctap15H
350

EntriesMean
Std Dev

1680
0.25220.0209300

gain [ADC]

Eventsgain [ADC]

than 10%.

ctap10H
1200

EntriesMean
Std Dev

5040
0.11530.01848

1000

250
800
200
600
150
400
100
200

50
0
0

0.05

0.1

0.15

0.2

0.25

0.3

0.35
0.4
P_CTAP

0
0

0.05

0.1

0.15

0.2

0.25

0.3

0.35
0.4
P_CTAP

Figure6.11 Distribution of the probability of cross-talk and after-pulse for 15 µm-pitch (left) and 10 µm-pitch (right) SiPM.

6.4 Pedestal
The signal pedestals is calibrated because the ADC counts with the pedestals subtracted can be used to the MIP
calibration and the analysis using the cosmic-ray. The cosmic-ray data contains no-hit channels because the data
is taken per chip including the hit beyond the threshold and no-hit just belonging the chip.

6.4.1 Pedestal calibraiton
Fig. 6.12 gives the typical pedestal spectrum ﬁtted by a gaussian. The peak value of the gaussian is set as thepedestal calibration factor, cpedestal , and the sigma of the gaussian is set as the error of the pedestal. Fig. 6.13
and Fig. 6.14 shows the distributions of the mean and the sigma of the pedestal spectrum with 15 µm-pitch and10 µm-pitch SiPMs respectively. There are no dependence on the types of SiPMs, and the typical pedestal valueis 422 ADC with about 5% variance for all channels. The pedestals are subtracted from the signal per channel, soChapter 6 Calibration

84

this variance has no problem after the subtraction. The typical sigma of the pedestal is quite small, about 3.3 ADC
with about 16% variance, less than 1% of the pedestal value.
Times_layer0_chip0_chan0
EventsTimes_layer0_chip0_chan0

EntriesMean
Std Dev

250

1967
455.5
4.713

200

150

100

50

0

430

440

450

460

470

480
ADC

pedH15140

Entries

1680

Mean

426.8

Std Dev

29.15

120

ChannelChannelFigure6.12 ADC distribution of the signal pedestal

sigH15
400
350

1680

Mean

3.374

Std Dev0.5299

300

100

250

80

200

60

150

40

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0
300

Entries

350

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500

550
600
Pedestal [ADC]

0
0

1

2

3

4

5

6

7

8
9
10
Sigma [ADC]

Figure6.13 Distribution of the pedestal (left) and the sigma of the ADC distribution (right) with 15 µm-pitch SiPM

6.5 MIP calibration
When a high-energy charged particle passes through a material, it loses a certain amount of energy due to the
Coulomb interaction with the atoms in the material. Such a particle is called a Minimum Ionizing Particle (MIP).
In the experiments using scintillators, the analogue signal for the detector is converted to the energy in units of thenumber of MIPs using the MIP calibration factor cM IP .
This section gives the results of the MIP calibration.

85

pedH10450

Entries

5040

Mean

422.7

Std Dev

27.26

ChannelChannel

6.5 MIP calibration

sigH101000

Entries

5040

Mean

3.287

Std Dev

0.5889

400
350

800

300
600

250
200

400
150
100

200

50
0
300

350

400

450

500

0
0

550
600
Pedestal [ADC]

1

2

3

4

5

6

7

8
9
10
Sigma [ADC]

Figure6.14 Distribution of the pedestal (left) and the sigma of the ADC distribution (right) with 10 µm-pitch SiPM

6.5.1 MIP calibration
The cM IP is obtained per channel using all the cosmic-ray events. The angular correction, discussed in Section
5.2.5, and the temperature correction as the reference temperature of 20 ◦ , discussed in Section 6.6, are performedat each MIP hit. Fig. 6.15 and 6.16 show the typical ADC distributions of the MIP response with 15 µm-pitch and10 µm-pitch SiPM respectively, ﬁtted with a Gauss-convoluted Landau function. The most probable value (MPV)of the function is taken to be the MIP calibration factor, cM IP .
Layer0_Chip0_ Chn0
EventsLayer0_Chip0_ Chn0

EntriesMean
Std Dev

180
160

4200
693.1
308

140
120
100
80
60
40
20
0

0

500

1000

1500

2000

2500

3000
ADC

Figure6.15 ADC distribution for the MIP response with 15 µm-pitch SiPM

The Landau distribution of the MIP is obtained for all channels. Fig. 6.17 shows the distribution of the cM IP .
The signal ADC counts can be converted to the number of MIPs using this results.

Chapter 6 Calibration

86
Layer4_Chip0_ Chn8
EventsLayer4_Chip0_ Chn8220

EntriesMean
Std Dev

200

4371
168.9
94.17

180
160
140
120
100
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0

0

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400

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800

1000
ADC

lyH15
50

Entries

1260

Mean

562.4

Std Dev

129.9

40

Channels

ChannelsFigure6.16 ADC distribution for the MIP response with 10 µm-pitch SiPM

lyH10
300

Entries

5040

Mean

112.8

Std Dev

27.79

250

200

30

150
20
100
10
50

0
0

100 200 300 400 500 600 700 800 900 1000
MIP [ADC]

0
0

50

100

150

200

250

300

350
400
MIP [ADC]

Figure6.17 Distribution of cM IP for 15 µm-pitch (left) and 10 µm-pitch (right) SiPM

6.5.2

Light yield

The MIP light yield in units of the number of photoelectrons is calculated by dividing the cM IP by the cgain .
Fig. 6.18 shows the distribution of the MIP light yields in units of the number of photoelectrons for 15 µm-pitch(left) and 10 µm-pitch (right) SiPM. The average light yield is 22.6 p.e. for 15 µm-pitch SiPM and 7.6 p.e. for10 µm-pitch SiPM. The MIP light yield contains the eﬀects of the cross-talk and after-pulse, The light yield after
subtracting the eﬀects of the cross-talk and after-pulse is about 18 p.e. for 15 µm-pitch SiPM and 7 p.e. for10 µm-pitch SiPM. The diﬀerence of the light yield is caused by the diﬀerence of the photon detection eﬃciency(PDE). The PDE at the catalogue is 25% for 15 µm-pitch SiPM and 10% for 10 µm-pitch SiPM, so the diﬀerenceof measured light yields replicate the diﬀerence of the PDE.

87

lyH15

100

Entries

1260

Mean

22.66

Std Dev

5.435

80

Channels

Channels

6.6 Temperature

lyH10
1000

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Mean

7.602

Std Dev

1.87

800

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600

40

400

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200

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0

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5

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20

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0

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40
Lightyield [p.e.]

Figure6.18 Distribution of MIP light yields in units of p.e. for 15 µm-pitch (left) and 10 µm-pitch (right) SiPM

6.6 Temperature
The temperature is monitored during one month LED run and three months cosmic-ray run using the temperature
sensors on the EBU. The temperature at each channel is reconstructed by the inverse distance weighting [50]. The
temperature dependence of the gain and MIP can be obtained, and the temperature correction is performed using
these results. This section describes the method of the temperature correction.

6.6.1 Temperature distribution
The temperature is monitored at each event during the LED run and the cosmic-ray run. Sixteen temperature
sensors are equipped in one EBU. The temperature at each channel is reconstructed by the inverse distanceweighting:W (x, y) = Σni=1 Qi Wi Qi =

1
Li
Σ L1i

(6.4)

where, W (x, y) is the temperature at (x,y), Qi is the weight, Wi is the temperature at each sensor, and Li is thelength form (x,y) to each sensor. Fig. 6.19 shows the temperature distribution before and after the reconstruction.
Fig. 6.20 shows the temperature variation during one month LED run at each layer. The temperature changes
from 19 ◦ C to 22 ◦ C . Fig. 6.21 shows the temperature transition during three months cosmic-ray run at each layer.
The temperature changes from 16 ◦ C to 25 ◦ C . The temperature variation in the cosmic-ray run is larger thanthat in the LED run, because the air conditioning doesn’t work properly sometimes and the outside temperaturechanges during the long run.

6.6.2 Temperature dependence
The SiPM has a high temperature dependence. If the temperature increases, the crystal lattice in the SiPM pixel
vibrates more heavily. The accelerated carriers may collide with the lattice before reaching an energy threshold,Chapter 6 Calibration

88

Figure6.19 The left shows the temperatures measured at the temperature sensors, and the right shows thetemperature distribution reconstructed by the inverse distance weighting.

24

Layer_0
Layer_1
Layer_2
Layer_3

23

Layer_4
Layer_5
Layer_6
Layer_7

22

Layer_8
Layer_9

Temperature [oC]

Layer_10
Layer_11

21

Layer_12
Layer_13
Layer_14
Layer_15

20

Layer_16
Layer_17
Layer_18
Layer_19

19

Layer_20
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Layer_22
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18

Layer_24
Layer_25
Layer_26
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17

Layer_28
Layer_29
Layer_30

160

Layer_31

5

10

15

20

25

Date
Figure6.20 Temperature variation during one month LED run at each layer. Each plot shows the averagetemperature reconstructed by the inverse distance weighting at each layer.

6.6 Temperature

8930

Layer_0
Layer_1
Layer_2
Layer_3
Layer_4
Layer_5
Layer_6
Layer_7
Layer_8
Layer_9
Layer_10
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Layer_12
Layer_13
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Layer_29

28

24

o

Temperature [ C ]

26

22
20
18
16
14
12

0

20

40

60

80

100

Date

Figure6.21 Temperature variation during three months cosmic-ray run at each layer. Each plot shows theaverage temperature reconstructed by the inverse distance weighting at each layer.

and the ionization is diﬃcult to happen. Then the breakdown voltage increases. If the operation voltage is constant,the over voltage decrease. This temperature dependence aﬀects some properties of the SiPM such as the gain,
PDE, cross-talk and after-pulse. In the temperature range from ∼ −20◦ C to ∼ 80◦ C , the gain, PDE, CTAP isalmost proportional to the breakdown voltage.
The temperature dependence needs to be corrected at the reconstruction. Especially the gain and MIP ADC
counts are aﬀected by the temperature dependence, so they should be corrected at each hit in order to calibrate
correctly. The temperature dependence for some calibration parameters is measured.
Fig. 6.22 shows the correlation between the average temperature and the gain. The temperature dependence isdetermined by the slopes of the ﬁtted linear function. Fig. 6.23 shows the results of the temperature dependence
at each layer. The average temperature dependence is estimated to be −1.22%/◦ C for 15 µm-pitch SiPM andGain [ADC]

Gain [ADC]−0.73%/◦ C for 10 µm-pitch SiPM.

26
25.9
25.8

15.6

15.5

15.4

25.7
15.3
25.6
25.5

15.2

25.4
15.1
25.3
19.4 19.6 19.8

20

20.2 20.4 20.6 20.8

21 21.2 21.4
Temperature [ oC ]

19.5

20

20.5

21
21.5
Temperature [ oC ]Figure6.22 Correlation between the temperature and gain.

The MIP ADC counts are calculated per layer and per day. Fig. 6.24 shows the sum distribution over all thechannels in each layer, ﬁtted with a Gaussian-convoluted Landau function. The most probable value (MPV) of
the function is taken to be the MIP calibration factor. The 6 belts shown in Fig. 6.25 have the large temperature
diﬀerence in short periods during the cosmic-ray run, these short 6 periods are selected for the calculation of thetemperature dependence of the MIP response. The reason for setting short periods is to avoid the eﬀect of theChapter 6 CalibrationoTemperature dependence [%/ C]

90

0
− 0.2
− 0.4
− 0.6
− 0.8
−1
− 1.2
− 1.4
− 1.6
0

5

10

15

20

25

30
layer

Figure6.23 Temperature dependence for the gain at each layer.

decrease in MIP response described in section 7.1.
EventsLayer0Layer07403
Entries
799
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344.6
Std Dev

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300
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200
150
100
50
0

0

500

1000

1500

2000

2500

3000
ADC

Figure6.24 The sum distribution over all the channels in each layer. The red line shows the ﬁtted Gaussianconvoluted Landau function.

Fig. 6.26 shows the correlation between the average temperature and the Landau MPV. The temperaturedependence of the MIP response is determined by the mean value of the slopes of the ﬁtted linear functions at
6 periods. Fig. 6.27 shows the results of the temperature dependence at each layer. The average temperaturedependence is estimated to be −3.23%◦ C for 15 µm-pitch SiPM and −3.70%◦ C for 10 µm-pitch SiPM.
The diﬀerence of the temperature dependence between the gain and MIP response is caused by the diﬀerence in
SiPM properties that each contains. The temperature diﬀerence of the gain is caused only by the gain variation,
while the temperature diﬀerence of the MIP response is caused by the variations such as the gain, PDE, cross-talkand after-pulse. Therefore, the temperature dependence of the MIP response is larger than that of the gain.

6.6.3

Temperature correction

The typical MIP calibration factor cM IP is obtained by the cosmic-ray muon. The cosmic-ray test is performed
during the 3 months to accumulate the statistics and check the stability, but the temperature changes during the test.

6.6 Temperature

91

Figure6.25 Six short periods during the cosmic-ray run. Each period contain 6 data points which have large
temperature diﬀerence.

600
580
560

Period 2
LandauMPV [ADC])

Period 1
LandauMPV [ADC])

LandauMPV [ADC])

Period 0
620

560
540
520

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520

480

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460
17

18

19

20

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23
temp [degree]

21.5

22

22.5

23

23.5

24

24.5
25
temp [degree]

17.5

18

18.5

620
600
580

600
580
560

20.5

21
21.5
temp [degree]

18.5

19
temp [degree]

600
580

540

520

540

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520

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20

620

540

500

19.5

640

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19

Period 5
LandauMPV [ADC])

Period 4
LandauMPV [ADC])

Period 3

560

480

460

460

460
18

18.5

19

19.5
temp [degree]

18

18.5

19

19.5

20

20.5

21
temp [degree]

16.5

17

17.5

Figure6.26 Correlation between the temperature and MPV value.

o

17.5

temp factor [%/ C]

LandauMPV [ADC])

620

2

0

−2

−4

−6

−8
0

5

10

15

20

25

30
layer

Figure6.27 Temperature dependence for the MIP response at each layer.

18

Chapter 6 Calibration

92

The temperature correction is performed at each MIP hit using the monitoring temperature and the temperaturedependence. After the temperature correction, the typical cM IP at the reference temperature can be obtained.
The temperature correction for the signal ADC counts is performed by:
corr
corr
[ADC] = (1 + (Ti − Tref )dM IP )Ano
Atemp
[ADC](T )
i
i

(6.5)

corr
corr
where, Atemp[ADC] and Ano[ADC](T ) is the signal ADC count at each hit after the temperature correctioniiand without correction respectively. Ti is the temperature at each hit, and Tref is the reference temperature, which
is set as 20 ◦ C. dM IP is the temperature dependence for the MIP response.
Fig. 6.28 shows the ADC distributions before and after the temperature correction. The ADC distributions forthe two periods with large temperature diﬀerence (average temperature is 17 ◦ C and 22 ◦ C) have large deviation
without the correction. After the correction, the distributions match well.
mip0

raw0
raw0
raw1

0.05
0.045

17 degree

Entries

7044
5114

22 degree

Mean

718.3
800.1

Std Dev

357.7
324

0.045

0.04

0.04

0.035

0.035

0.03

0.03

0.025

0.025

0.02

0.02

0.015

0.015

0.01

0.01

0.005

0.005

0

0

500

1000

1500

2000

2500

3000
ADC

mip0
mip1

0.05

0

0

500

1000

1500

17 degree

Entries

7044
5114

22 degree

Mean

748.8
737

Std Dev

328.4
336.5

2000

2500

3000
ADC

Figure6.28 ADC distributions without the temperature correction (left) and after the temperature correction(right). The two days with large temperature diﬀerence are selected. The temperature in the legend is the meanvalue of all hits, but the temperature correction is performed at each hit.

The temperature dependence is evaluated and the method of the temperature correction is established, then thetemperature correction is applied to the measurement using the actual detector. This makes it possible for the ﬁrst
time to evaluate the performance on the actual detector.

93

Chapter 7

Performance
The performance of the Sc-ECAL is evaluated using the technological prototype in the following methods:• Stability of the calibration parameters• Performance evaluation using the cosmic-ray tracks• Performance evaluation using the showers induced by the cosmic-ray
The stability of the key parameters is measured to verify that the detector is operating stably. As a performance
evaluation using the cosmic-ray tracks, the eﬃciency and the position resolution is evaluated to check the requirements of the Sc-ECAL, and compared with the Monte Carlo simulation. The performance of the Sc-ECAL for theelectromagnetic showers is evaluated by comparing the showers induced by the cosmic-ray and simulation. This
chapter gives the results of the performance evaluation.

7.1 Stability
Since the actual detector is required to operate stably over a long period of time, the stabilities of key parameters
are evaluated during long-term commissioning runs. The stabilities for the gain, inter-calibration factor, and CTAP
probability are evaluated using one-month long LED run. The stabilities for the pedestal and MIP response are
evaluated using three-months long cosmic-ray run. This section gives the measured stabilities of the key calibration
parameters.

7.1.1 Gain stability
Fig. 7.1 shows the cgain stability of one channel at each layer. The cgain is found to be quite stable at per-channel
level, although a weak correlation with the temperature variation is seen. In order to store the statistics to reduce
the error and to check the correlated time-dependence in the performance between channels in a certain layer or
ASIC, which shares services such as power supply, the stability per layer is checked. Fig. 7.2 shows the stabilityof the cgain averaged over all the channels at each layer. The average cgain at each layer is found to be quite stable
and no layer correlation is seen, although a weak correlation with the temperature variation is still seen.
Fig. 7.3 shows the cgain stability after the temperature correction. The stability is found to be even further
improved by the temperature correction. An excellent long-term stability of the cgain is achieved.

Chapter 7 Performance

94

30

30

30

30

28

28

25

25

layer 0layer 1layer 2layer 3layer 28
layer 29
layer 30
layer 31

5

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layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 15

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Date

15

layer 16
layer 17layer 18
layer 19layer 20layer 21layer 22layer 23
layer 24
layer 25
layer 26
layer 27

20

20
18

o

20

Temperature [ C ]20
10Gain [ADC/p.e.]

22
15

26
o

24

Temperature [ C ]Gain [ADC/p.e.]

26
20

16
14
12
25

Date

Figure7.1 Stability of one-channel gain at each layer for 15 µm-pitch (left) and 10 µm-pitch (right) SiPM. The
red line shows the temperature during the LED run.

30

30

30

30

28

28

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20
10

layer 0layer 1layer 2layer 3layer 28
layer 29
layer 30
layer 31

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layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 15

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Date

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layer 16
layer 17layer 18
layer 19layer 20layer 21layer 22layer 23
layer 24
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20

20
18

o

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Temperature [ C ]15

Gain [ADC/p.e.]

22

o

24

26
Temperature [ C ]Gain [ADC/p.e.]

26
20

16
14
12
25

Date

Figure7.2 Stability of the gain averaged over all the channels at each layer for 15 µm-pitch (left) and 10 µmpitch (right) SiPM. The red line shows the temperature during the LED run.

30

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layer 16
layer 17layer 18
layer 19layer 20layer 21layer 22layer 23
layer 24
layer 25
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layer 27

20

20
18

o

20

Temperature [ C ]22

Gain [ADC/p.e.]

24

o

20

26
Temperature [ C ]Gain [ADC/p.e.]

26

16
14
12
25

Date

Figure7.3 Stability of the average gain at each layer after temperature correction for 15 µm-pitch (left) and10 µm-pitch (right) SiPM.

7.1 Stability

95

7.1.2 Inter-calibration stability
Fig. 7.4 shows the cinter stability of one channel at each layer. the per-channel cinter is almost stable, but some
ﬂoundering can be seen on some days due to the rough pitch of the LED intensities. In order to store the statistics
to reduce the error and to check the correlated time-dependence in the performance in a certain layer or ASIC,
the stability per layer is also checked. Fig. 7.5 shows the stability of the cinter averaged over all the channels at
each layer. The average cinter at each layer is found to be quite stable during one month LED run and no layer
correlation is seen. The temperature dependence is not seen because the dependence is cancelled by taking theratio.
There is a limit to the measurement precision at the per-channel level due to the rough pitch of the LED light.
The LED data is taken by the ﬁnest pitch of the LED intensity, but the ﬁtting plots are sometimes too few tomeasure the cinter . However, the precision becomes higher at the per-layer level due to the error reduction by thelarge statistics. The cinter is set as the mean of all runs in the current setup. The update of the LED system withthe ﬁne pitch of the LED intensities makes the inter-calibration more precise.
0.04

30

0.04

30

0.035

28

0.035

28

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0.015

18
layer 0layer 1layer 2layer 3layer 28
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layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 15

0.015
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layer 17layer 18
layer 19layer 20layer 21layer 22layer 23
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20

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C]
o

C]

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0.025
LvHratio

LvHratio

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26

0.03

Temperature [0.03

Temperature [

26

16
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2512

Date

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350
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150
0.025
100
0.02
50

LvHratiolayer 0layer 1layer 2layer 3layer 28
layer 29
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0.015
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layer 0layer 1layer 2layer 3layer 28
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LvHoffset

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0.025
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LvHratio200
0.03

Temperature
[
C
]

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250

0.015
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layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 144
layer
layer 155layer
layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 1515

20

layer 16
layer 17layer 18
layer 19layer 20layer 21layer 22layer 23
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C]

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o

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Temperature
[
C
]

28

26

o

450

Temperature [

28

400

C]

450

Temperature [LvHoffset

Figure7.4 Stability of one-channel cinter at each layer for 15 µm-pitch (left) and 10 µm-pitch (right) SiPM.
500
30
500
30
The red line shows the temperature during the LED run.

16
14
2512

Date

Figure7.5
Stability of the cinter averaged over all
the channels
at each layer for 15 µm-pitch (left) and 10 µm
500
30
500
30
pitch
(right)
SiPM.
The
red
line
shows
the
temperatureduring
the
LED
run.
450
450
28

250
20

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18
layer 0layer 1layer 2layer 3layer 28
layer 29
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C]

LvHoffset

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350

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Temperature [400

Chapter 7 Performance

96

7.1.3

CTAP stability

Fig. 7.6 shows the PCT AP stability of one channel at each layer. The per-channel PCT AP is almost stable, butsome ﬂoundering can be seen on some days. In order to store the statistics to reduce the error and to check thecorrelated time-dependence in the performance in a certain layer or ASIC, the stability per layer is also checked.
Fig. 7.7 shows the stability of the PCT AP averaged over all the channels at each layer. The average PCT AP at eachlayer is found to be quite stable during one month LED run, and no layer correlation is seen.
The measurement precision of this method become worse due to the ﬂuctuation of the LED especially at the
per-channel level. This method uses the LED data with low light intensity which has rather larger ﬂuctuation of
the LED intensity. Moreover, if the separation of 0 and 1 photon distribution is diﬃcult due to the low single
photoelectron gain especially in 10 µm-pitch SiPM, the calculations of P (0) and P (1) have large uncertainties andthe PCT AP is wrongly calculated. It is not a problem by taking the average of all runs to suppress the eﬀects ofthe measurement precision. The PCT AP is set as the mean of all runs in the current setup. The update of the LED
system with the more stable LED or the SiPM with more high gain makes the CTAP calibration more precise.

22
0.25
20

0.2

18

0.15

layer 0layer 1layer 2layer 3layer 28
layer 29
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layer 16
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layer 24
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layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 15

Temperature [26
CTAP probability

28

0.4

C]

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Temperature [0.5

CTAP probability

30

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2512

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day 180.15

CTAP probability

CTAP probability

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C]

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layer 0layer 1layer 2layer 3layer 28
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Temperature [

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layer 16
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layer 24
layer 25
layer 26
layer 16
layer 27
layer 17layer 18
layer 19layer 20layer 21layer 22layer 23
layer 24
layer 25
layer 26
layer 27o25layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 4layer 15
layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 15

Temperature [gain [ADC]

gain [ADC]Single-photoelectron gain stability
Single-photoelectron gain stability
Figure7.6
Stability of one-channel PCT AP at each layer for3015 µm-pitch(left) and 10 µm-pitch (right) SiPM.
30
The red line shows the temperature during the LED run.

2512

20

Date

25

layer 0layer 1layer 2layer 3layer 28
layer 29
layer 30
layer 31

gain [ADC]

gain [ADC]

gain stability
Single-photoelectron gain stability
Figure7.7 Single-photoelectron
Stability of the PCT
AP averaged over all the channels at each layer for 15 µm-pitch (left) and3030
10 µm-pitch (right) SiPM. The red line shows the temperature during the LED run.
25

20

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0

0

layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 15

layer 16
layer 17layer 18
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layer 24
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layer 27

7.1 Stability

97

7.1.4 Pedestal stability
Fig. 7.8 shows the cpedestal stability of one channel at each layer. The cpedestal can be obtained per channel
with less than 1% variance, and the cpedestal is found to be quite stable at per-channel level. In order to check thecorrelated time-dependence in the performance in a certain layer or ASIC and conﬁrm the pedestal stability at the
per-layer level , the stability per layer is checked. Fig. 7.9 shows the stability of the cpedestal averaged over all thechannels at each layer. The cpedestal is found to be quite stable during three months run at all layers, and no layer
correlation is seen
When performing test beam experiments or extending the system to the actual detector, cpedestal can be calibrated
for each channel by acquiring pedestals from channels with no hits or by acquiring data with random triggers for

Pedestal [ADC]pedestals.

500
480
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360

layer 0layer 1layer 2layer 3layer 28
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Pedestal [ADC]

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100
day

Figure7.8 Stability of one-channel pedestal at each layer with 15 µm-pitch (top) and 10 µm-pitch (bottom) SiPM.

7.1.5 MIP stability
The cM IP stability of one channel cannot be evaluated per day due to the poor statistics, although it is necessary
to calibrate and check the stability of each channel and make corrections if necessary. In the operation of theactual detector, the statistics can be stored from the charged particle track events and the per-channel calibrationand stability check can be done, which allows the correction per channel.

Chapter 7 Performance

Pedestal [ADC]

98

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layer 0layer 1layer 2layer 3layer 28
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Pedestal [ADC]

Date

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100
Date

Figure7.9 Stability of the pedestal averaged over all the channels for each layer with 15 µm-pitch (top) and10 µm-pitch (bottom) SiPM.

For a discussion of the stability, the cM IP stability is checked using the per-layer calibration. Fig. 7.10 shows
the stability of the cM IP which is calibrated by ﬁtting the sum distribution of all the channels at each layer before
the temperature correction, discussed in Section 6.6.2. A weak correlation between the cM IP and the temperature
can be seen. Fig. 7.11 shows the stability after the temperature correction. The temperature dependence is notseen, and the cM IP is almost constant day by day. However, some decrease of the cM IP is seen, and the decrease
rate varies between 5–13% over 3 months depending on layer.
The temperature correction is successfully done at the MIP calibration. The 5–10% accuracy is required forthe determination of the cM IP , and the larger variation than this requirement aﬀects the calorimeter and physics
performance such as the energy linearity and jet energy resolution. The temperature variation causes at most the
10% variation of the MIP response, but the temperature correction turns oﬀ this eﬀect and almost no variationis seen day by day. The temperature correction allows the accurate calibration of the MIP response so that theperformance is not aﬀected.
The reason of this decrease of the cM IP is under investigation, but it could be due to the aging of the scintillation
light emission or the instability of the electronics or SiPMs. It is found in the one-month long LED run that the
SiPM gain is quite stable, but the LED run isn’t taken during three months cosmic-ray run, so the decrease of the
SiPM gain during the cosmic-ray run is not known. A cosmic ray test with frequent LED calibration should be
performed to better understand this instability of the cM IP . The possible approaches to solve this problem are the7.2 Simulation of cosmic-ray

99

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Figure7.10 Stability for the cM IP with the calibration per layer before the temperature correction with 15 µmpitch (top) and 10 µm-pitch (bottom) SiPM

frequent MIP calibration and the voltage adjustment of SiPMs.

7.2 Simulation of cosmic-ray
The cosmic-ray test using the technological prototype is simulated using a GEANT4 [51]. A reference physics
list of QGSP_BERT is selected in the Geant4 version 4.10.06 p03. The Sc-ECAL simulation model consists of 30
layers of the absorbers, detection layers, and readout PCBs. The detection layers are aligned in the same way as
the prototype.
The cosmic-ray shower library (CRY) [52] is used to simulate the cosmic-ray. The CRY software librarygenerates the cosmic-ray particle shower. Fig. 7.12 shows the distribution of the energy and the zenith angle
for each particle type generated by the CRY. The cosmic-ray particles generated by the CRY have wide range ofenergies of 1 MeV to 100 TeV, and several particles such as muons, electrons, gamma, and hadrons are generated.
The CRY can disable a certain particle, but in this setup, all the particle types are used to simulate. The CRY has
the setups of three elevations, and the sea level is set at this time. The CRY also sets the latitude of 32 degreein China. The discontinuity of the energy distribution is a speciﬁcation of the CRY. The cosmic rays produced
by CRY are injected from the top of the prototype randomly within the angles detectable by the prototype, where
the cut of the zenith angle of 60 degree is applied. The cosmic-ray test is conducted indoors, so a material that
replicates a building around the prototype is placed on the top of the prototype. The building material is replacedChapter 7 Performance

100

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Figure7.11 Stability for the cM IP with the calibration per layer after the temperature correction with 15 µmpitch (top) and 10 µm-pitch (bottom) SiPM

by the SiO2 , and 15 pieces of 12 cm thickness plates are placed with 4.2 m pitch, which reproduces the situation

1

Events [a.u.]

Events [a.u.]of the cosmic-ray test with 15 ﬂoors above the prototype.
Muon: 35.8
Electron: 8.9
Gamma: 49.6
Others: 5.8

10− 1

0.1
0.09

Muon: 35.8
Electron: 8.9

0.08

Gamma: 49.6
Others: 5.8

0.07
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× 10
160 180200
Energy [MeV]

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90
Theta angle [degree]

0.09

Electron: 8.9

0.08

Gamma: 49.6
Others: 5.8

Events [a.u.]

Events [a.u.]

Figure7.12 Distribution of the primary energy at each particle type (left) and the zenith angle (right) The
0.1
0.1
numbernext to the particle type means
the content of the particle.
Muon: 35.8
Muon: 35.8
0.09Electron: 8.9

0.08

Gamma: 49.6
Others: 5.8

251 million
cosmic-rays are generated by the CRY, and injectedto the simulation setup. Only muons reach the
0.07
0.07
setup for0.06
the straight track events, while some types of particles0.06cause the showers. The same tracking algorithms
0.05

0.05

0.04

0.04

0.03

0.03

0.02

0.02

0.01

0.01

7.3 Performance evaluation using the cosmic-ray straight track101

as in the cosmic-ray analysis are applied to the simulation data. However, at the ﬁrst step of the track ﬁnding, thechannel characteristics obtained in the prototype calibration such as the cM IP , decline of cM IP , and threshold areapplied to each channel in the simulation. Assuming that the cM IP decrease linearly, the rate of the decrease foreach layer calculated in the prototype is also applied to each layer at the simulation. The average threshold of thesignal is set to the 0.5 MIP, but the threshold is diﬀerent from each ASIC same as the prototype.

7.3 Performance evaluation using the cosmic-ray straight track
This section gives the performance such as the eﬃciency and position resolution measured with the straight trackof the cosmic-ray, and the comparison with the simulation.

7.3.1 Eﬃciency
The detection eﬃciency is measured as the ratio of events that have hits in a layer to all cosmic-ray events.
The denominator of the ratio (all cosmic-ray events) only contains the events whose cosmic-ray track can bereconstructed, and the numerator only contains the hits in the reconstructed cosmic-ray track. The blue plots in
Fig. 7.13 show the detection eﬃciency at each layer using all the cosmic-ray data. The eﬃciency is measured to
be 84% on average.
The red plots in Fig. 7.13 show the detection eﬃciency per layer using the simulation. The both results in thedata and simulation show a good agreement with each other. The eﬃciency in the simulation is a slightly larger
than that in the cosmic-ray data. This is considered because the simulation doesn’t contain the eﬃciency variationby the temperature change, found in the cosmic-ray data and discussed as below.
1
0.9
0.8

Efficiency

0.7

Cosmic-ray data
Simulation

0.6
0.5
Cosmic-ray data

0.4

Simulation

0.3
0.2
0.1
20

25

30

0
0

5

10

15
LayerID

20

25

30

Figure7.13 Detection eﬃciency at each layer with the cosmic-ray data (blue) and simulation (red).

The ineﬃciency comes from the threshold of 0.5 MIP and dead space between the strips. The cosmic-rays thatpass across the two strips lose energy as they split into their respective channels and also pass through dead areas.
Such events are not detected because they have less energy deposit than the threshold of 0.5 MIP, and thus cause
the ineﬃciency. The fraction of the dead channel is less than 1% (66 out of 6,300 channels). The eﬀect of the deadchannel is, therefore, negligible.

Chapter 7 Performance

102

The stability of the detection eﬃciency is evaluated in the cosmic-ray data. Fig. 7.14 and Fig. 7.15 shows thestability of the eﬃciency at each layer with 15 µm-pitch SiPM and 10 µm-pitch SiPM respectively. It can be seenthat the eﬃciency changes in response to temperature changes. The temperature dependence of the SiPM aﬀects
the eﬃciency. The increase of the temperature leads to the increase of the breakdown voltage of the SiPM, while
the operation voltage is constant, so the over voltage decrease and the SiPM gain decrease. The gain decrease leads
to more events below the threshold. The eﬃciency gradually decrease as time goes on, because the decline of thecM IP causes the decline of the eﬃciency. However, the all layers still have reasonably high eﬃciency of about80%.
The decline of the eﬃciency and the MIP response have no signiﬁcant eﬀect on the detector performance. Ifthey are caused by a ﬂuctuation in the electronics, the gain can be adjusted in online. For the test beam experiments
and actual detector operations, the MIP calibration is taken at the time and the threshold is set as lower by taking
the external trigger.

30

layer 0layer 2layer 3layer 28

1.2

28
26

Efficiency

1.1

24
22

1
20
0.9

18

Temperature [ oC ]

1.3

16
0.8
14
0.7

0

20

40

60

80

100

12

Date

Figure7.14 Stability of the detection eﬃciency for each layer with 15 µm-pitch SiPM. Red line shows theaverage temperature.

7.3.2

Position resolution

The position resolution is estimated at each layer in the following way. The track ﬁtting is performed using thehits reconstructed by the SSA in all the layers except the target layer. The distance between the intersection of thereconstructed track on the target layer and the SSA hit in the target layer is calculated. Fig. 7.16 shows the distance
distribution. The position resolution is calculated by the RMS of the distribution of the distance.
As described in Section 4.2, the SSA can give multiple hits along the long side of the strip. The position
resolution can, therefore, be a little worse in the long-side (45 mm length) direction than in the short-side (5 mmwidth) direction. The position resolution is evaluated in x-axis and y-axis, which are the axes parallel to thedetection layer. The long side and short side of the strips are aligned orthogonally in each axis. The blue plots
in Fig. 7.17 show the results of the position resolution at each layer in x-axis (left) and y-axis (right). In x-axis,
the results in odd layers correspond to the short-side (5 mm width) direction of the strip, the results in even layers
correspond to the long-side (45 mm length) direction of the strip. In y-axis, the results in even layers correspondto the short-side direction of the strip, the results in odd layers correspond to the long-side direction of the strip.

7.3 Performance evaluation using the cosmic-ray straight track103

layer 4layer 5layer 6layer 7layer 8layer 9layer 10layer 11layer 12layer 13layer 14layer 15

1.2

Efficiency

1.1

30

layer 16
layer 17layer 18
layer 19layer 20layer 21layer 22layer 23
layer 24
layer 25
layer 26
layer 27

28
26
24
22

1
20
0.9

18

Temperature [ oC ]

1.3

16
0.8
14
0.7

0

20

40

60

80

100

12

Date

Figure7.15 Stability of the detection eﬃciency for each layer with 10 µm-pitch SiPM. Red line shows theaverage temperature.

yerID : 0x_LayerID : 1
×10

x_LayerID : 0
Entries
Mean

581003

Events3100− 0.03171

Std Devx_LayerID : 1

2.131

Entries1377999

Mean−0.002316

Std Dev

1.687

80

60

40

20

0

2

4

6

8

0
−10

10

−8

X Residuals [mm]

−6

−4

−2

0

2

4

6

8

10

X Residuals [mm]Figure7.16 Distribution of the residual at a single
layer in short-handed(5 mm width) direction of the strip.
x_LayerID:7
x_LayerID : 6
Entries953892Mean

0.005543

×10

3

EventsyerID : 6120

x_LayerID : 7
Entries1193017Mean−0.000198

The red plots in Fig. 7.17 show the position resolution measured by the simulation in x-axis (left) and y-axis(right). The both results in100
the data and simulation show a good agreement with each other.
Std Dev

2.238

Std Dev

1.596

The position resolution in the short-side direction is estimated to be 1.5–1.8 mm, which is more or less
80 width of 5.3 mm, where the variance of the uniform distribution of 5.3 mm is
consistent with the strip pitch√
5.3 mm/ 12 = 1.53 mm. The position resolutions at the central layers are around 1.53 mm, so the prototype
60

realizes the cell segmentation of 5.3 mm in the short-side direction. The position resolution at outer layers is worse
than the inner layers. This is because the ﬁt track has some extensional errors, i.e. the error in inner layers are40

smaller than the error in outer layers. However, the position resolution of 1.8 mm at the outer layer is equivalent
to the strip pitch width of 6 20mm, which doesn’t have a large eﬀects on the granularity of the whole detector.
The position resolution in the long-side direction is estimated to be 2.3 mm, which is equivalent to the strip pitch
0

2

4

0
width
of
The worse resolution
direction
to10the SSA. The SSA splits the
6
8 8 mm.
10−10−8 compared−6−4 to−2the short-side
0
2
4
6 is due
8
X Residuals [mm]

X Residuals [mm]Chapter 7 Performance

3

3

2.5

2.5
Position resolution [mm]Position resolution [mm]

104

2

1.5

1

2

1.5

1

Cosmic-ray data
0.5

0Cosmic-ray data
0.5

Simulation

0

5

10

15
LayerID

20

25

30

0

Simulation

0

5

10

15
LayerID

20

25

30

Figure7.17 Position resolution at each layer with the cosmic-ray data (blue) and simulation (red) in x-axis(left) and y-axis (right).

strip based on the hit information of the previous and next layers, and if the hit positions are diﬀerent in the upperand lower layers, two cells are formed. Since the track is likely to be reconstructed to pass between two cells, theresidual between the track and the cell becomes large. Although there are events across the strips in the short-side
direction as well, the resolution is worse in the long-side direction because there are more such events.

7.3.3

Sum of hits and energies

The sum of the number of hits and the energy in the cosmic-ray track are compared between cosmic-ray data andsimulation. Fig. 7.18 shows the distribution of the sum of the number of hits (left) and the energy (right). The bothresults show a good agreement with each other. The slight diﬀerence is caused by the slightly higher eﬃciency inthe simulation as shown in Fig. 7.13 because the simulation doesn’t have the eﬀect of the temperature variation.
Fig. 7.19 shows the distribution of the total energy divided by total hits, that is, the average energy deposit in asingle cell. The both results also show a good agreement with each other. The energy deposit in a cell is the sameas the cosmic-ray data and simulation.

7.4 Performance evaluation using the cosmic-ray shower
The detailed study of the calorimeter using the electromagnetic showers is usually taken by the test beam
experiment, but unfortunately the test beam experiment is cancelled due to the COVID-19 pandemic. The
performance of the Sc-ECAL is evaluated by looking for shower events induced by the cosmic-ray and comparing
the shower properties with the simulation. A few examples of the event displays of the shower events from thecosmic-rays are shown in Fig. 5.10 and 5.11 This section gives the shower study using the cosmic-ray and thecomparison with the simulation.

105

Events [a.u.]

Events [a.u.]

7.4 Performance evaluation using the cosmic-ray shower

Cosmic-ray data
Simulation

0.05

0.1

Cosmic-ray data
Simulation

0.09
0.08
0.07

0.04

0.06
0.03

0.05
0.04

0.02
0.03
0.02

0.01

0.01
0
0

10

20

30

40

50

60

70

80

0
0

90 100# of hit

5

10

15

20

25

30
MeV

Events [a.u.]

Figure7.18 Comparison of sum of hit cells (left) and energies (right) in the cosmic-ray track. The distribution
shows the sum of hits and energies for all the cosmic-ray events.

0.1

Cosmic-ray data
Simulation

0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9
1
MeV

Figure7.19 The comparison of the average energy deposit in a single cell.

Chapter 7 Performance

106

7.4.1

Comparison with data and simulation

Fig. 7.20 shows the energy distribution at each type of the cosmic-ray particle in the simulation. The showers
induced by the cosmic-ray are electromagnetic showers caused mainly by the muon with various energies, butsome electrons and gamma-rays inject to the prototype through the building and cause the EM shower. A few

pdgH11

89652.1647313.600845
44773

Entries

7897

Mean

2.883e+04

Std Dev

3.054e+04

Events [a.u.]

hadrons also inject to the prototype through the building and cause the hadronic showers.
pdgH210.5
0.45

Muon: 83.59
Electron: 2.14

0.4

Gamma: 13.40
Others: 0.86

Entries

10646

Mean

3.053e+04

Std Dev

3.18e+04

0.35
0.3
0.25
0.2
0.15
0.1
0.05
3

120

140

3

× 10
160 180200
Energy [MeV]

0
0

20

40

60

80

100

120

140

× 10
160 180200
Energy [MeV]

ontainedr escape

Entries

9470

Mean

2.398e+04

EventsFigure7.20 Distribution of the energy at each type of injected cosmic-ray particle in the simulation. The
numbernext to the particle in the legend means the ratio of each particle.
energyH1
enecompH1
Entries

12736

Shower escapeMean
1.078e+04
Std Dev
8785
Fig.Std Dev
7.212.985e+04
shows the distributionsof the shower start layer for cosmic-ray
data andsimulation. Both the2000
After suppression
energyH2
enecompH2
distributionsforlayers are12736
used for the linear ﬁt to
1800 data and simulation match well. The ﬁrst 5 Entries
Entries12736cosmic-ray
2200

Mean
2.546e+04
Mean
1.078e+04
1600 so the shower events are not found. The shower events are searched for by taking
determinetheinjection angle,
Std Dev 3.117e+04
Std Dev8785

the cut of the many hits in1400
consecutive 3 layers, so that it is diﬃcult to ﬁnd the shower events in last 3–4 layers.
1200
of the injection angle at x-axis (left) and y-axis (right). Both the distributions
Fig. 7.22 shows the distribution
1000
for cosmic-ray data and simulation
match well, although some ﬂuctuations can be seen due to the small statistics.
800
Fig. 7.23 shows the longitudinal
shower proﬁle for the number of hits and the energy at each layer. The simulation
600
almost agrees with the cosmic-ray
data, but a slight deviation is observed especially after the shower maximum.
400

Fig. 7.24 and 7.25 show the transverse shower proﬁles for the number of hits and the energy respectively. All200

the proﬁles almost
match with the data and simulation, but a slight deviation is also observed. Fig 7.26 shows the
3
120

140

× 10
0
160 180200
5000
15000 at20000
25000The simulation
30000
distributionofthe sum of the0 numberof hits10000
and the energy
each event.
also agrees with theEnergy [MeV]
Energy [MeV]

data, but the simulation has less low-energy events compared to the data. To understand the deviation in moredetail, the comparison using the events with fully contained shower and with shower escape is performed in thefollowing sections.

7.4.2

Fully contained shower

The prototype may not contain the full shower depending on the shower start position and the energy of theincident particle. The comparison between the data and the simulation is performed for the fully contained showers.

0.04

0.04

0.02

0.02

0

−40

−20

0

0

20
40
Theta angle (x-axis) [degree]−40

Events [a.u.]

7.4 Performance evaluation using the cosmic-ray shower

107
startH1

Cosmic-ray data
Simulation

0.14

5163
14.71
5.815

EntriesMean
Std Dev

startH2

0.12

EntriesMean
Std Dev

0.1

12736
14.69
5.876

0.08
0.06
0.04
0.02
0
0

5

10

15

20

25
30
Shower start layer

phiXH1

Cosmic-ray data
Simulation

0.1

5155
−1.945
17.48

EntriesMean
Std Dev

phiXH2
EntriesMean
Std Dev

0.08

Events [a.u.]

Events [a.u.]

Figure7.21 Distribution of the shower start layer.

0.12

12736
− 0.2709
15.61

0.04

0.02

0.02

0

EntriesMean
Std Dev

020
40
Theta angle (x-axis) [degree]5155− 0.4184
16.55

phiYH2
EntriesMean
Std Dev

0.08

0.04

−20

Cosmic-ray data
Simulation

0.1

0.06

−40

phiYH1

0.12

0.06

0

−40

−20

0

12736
− 0.5031
14.79

20
40
Theta angle (y-axis) [degree]

startH1

Cosmic-ray data
Simulation

EntriesMean
Std Dev

5163
14.71
5.815

Entries
12736
Mean
14.69
Cosmic-ray data
Std Dev
5.876

40
0.1

Simulation

35

0.08

30
0.06

Energy [MeV]startH2

0.12# of hits

Events [a.u.]

Figure7.22 Distribution of the injection angles at x-axis (left) and y-axis (right)
0.14

12

Cosmic-ray data
Simulation

10

8

0.04
25
0.02

20

6

0
0

5

15

10

15

20

25
30
Shower start layer

4

10
2
5
0

0

5

10

15

20

0

25
layer

−20

0

5

10

15

20

25
layer

Figure7.23 Longitudinal shower proﬁle of the number of hits (left) and the energy (right) from the shower start layer.

Chapter 7 Performance45# of hits

50
35

Cosmic-ray data
Simulation

50# of hits# of hits

50# of hits

108

50
35

40

40

Cosmic-ray data
Simulation

45
30

40
25

35
20

35
20

30
15

30
15

25
10

25
10

20
5

20
5
−1000

− 500

0

500

15
0

1000
x [mm]

10

Cosmic-ray data
Simulation

45
30

40
25

15
0

Cosmic-ray data
Simulation

45

−1000

− 500

0

500

1000
y [mm]

105

5

25−1000

− 500

0

500

1000

Energy [MeV] Energy [MeV]

Energy [MeV] Energy [MeV]

Figure7.24
Transverse hit proﬁle for x-axis (left) and y-axis (right).
The origin is set as the shower start point.
00
Cosmic-rayxdata[mm]
Simulation

20
25

Cosmic-ray data
Simulation

15
20

25−1000

Cosmic-ray data
Simulation

20
10

5

5

10

10

− 500

0

500

0

−1000

− 500

0

0

1000
x [mm]

500

1000

Cosmic-rayydata[mm]
Simulation

15

15

−1000

500

20

10

0

0

25

15

5

− 500

−1000

− 500

0

500

1000
y [mm]

−1000

− 500

0

500

1000
y [mm]

501000
x [mm]

hitsumH1

0.3

Cosmic-ray data

Entries

5155

Simulation

Mean

133.3

Std Dev

88.86

0.25

hitsumH2

0.2

Entries

12736

Mean

144.2

Std Dev

99.43

Events [a.u.]

Events [a.u.]

Figure7.25 Transverse energy proﬁle for x-axis (left) and y-axis (right). The origin is set as the shower start point.

0.1

0.1

0.05

0.05

200

300

400

500

600
# of hit

Entries

5155

Simulation

Mean

43.93

Std Dev

39.64

enesumH2

0.2

0.15

100

Cosmic-ray data

0.25

0.15

0
0

enesumH1

0.3

0
0

50

100

150

200

Entries

12736

Mean

47.03

Std Dev

43.41

250
300
Energy [MeV]

Figure7.26 Distribution of the sum of the number of hits (left) and energies (right)

7.4 Performance evaluation using the cosmic-ray shower

109

The track and converged shower are within 4 hits (2 strips × 2 strips), but the non-converging shower has more
hits. The fully contained shower events are selected by taking a selection that the sum of hits at the last layer (Layer
29) is less than 4. Fig. 7.27 and 7.28 shows the event displays after the selection using the cosmic-ray data andsimulation respectively. Fig. 7.29 shows the distributions of the shower start layers after the selection. The shower
events at latter layers decrease, and only the shower events fully contained in the prototype are selected.
CR data

CR data
7

8
0

6

4
150
3
200
2
250

Layer position [mm]Layer position [mm]

5

100

50

Layer position [mm]

50

100

100

50
0
X position

−50
/ mm

50
0
−50
/ mm
n
io
−100−100 posit
Y

5

100
4
150
3
200
2

250

1

300

6

1

300

0

Layer position [mm]

7

0

100

100

−1

50
0
X position

−50
/ mm

50
0
−50
/ mm
n
io
−100−100 positY

0

Figure7.27 Event displays of the fully contained shower events in the cosmic-ray data. The color bar shows
the number of MIPs, and the hit above 10 MIPs is colored red to make it easier to see the diﬀerence in color.

Simulation

Simulation

28

8
7
0

7

0

50

6

50

100

5

150

4

200

3

250
300
50
0
X position

−50
/ mm

5

100

4

150
200

3

2

250

2

1
100
50
0
m
0
−50
n/m
−100−100 positio
Y

300

1
100
50
0
m
0
−50
n/m
−100−100 positio
Y

100

50
0
X position

−50
/ mm

Layer position [mm]Layer position [mm]Layer position [mm]100

Layer position [mm]6

Figure7.28 Event displays of the fully contained shower events in the simulation. The color bar shows thenumber of MIPs, and the hit above 10 MIPs is colored red to make it easier to see the diﬀerence in color.

Fig. 7.30 shows the distribution of the injection angle at x-axis (left) and y-axis (right). Both the distributions
34
for cosmic-ray data and simulation match well, although some ﬂuctuations can be seen due to the small statistics.
Fig. 7.31 shows the longitudinal shower proﬁle for the number of hits and the energy at each layer. The simulationagrees with the cosmic-ray data much better without the selection. The proﬁles for the simulation have a bit higher

0.04

0.04

0.02

0.02

0

−40

−20

0

0

20
40
Theta angle (x-axis) [degree]−40

Chapter 7 Performance
Events [a.u.]

110
startH1

Cosmic-ray data
Simulation

0.14

3746
12.9
5.102

EntriesMean
Std Dev

startH2

0.12

9470
13.02
5.304

EntriesMean
Std Dev

0.1
0.08
0.06
0.04
0.02
0
0

5

10

15

20

25
30
Shower start layer

phiXH1

0.12

Cosmic-ray data
Simulation

0.1

EntriesMean
Std Dev3742−2.04417.81

phiXH2
EntriesMean
Std Dev

0.08

9470− 0.3266
15.9

Events [a.u.]

Events [a.u.]

Figure7.29 Distribution of the shower start layers for fully contained showers.

0.04

0.04

0.02

0.02

−20

0

0

20
40
Theta angle (x-axis) [degree]

EntriesMean
Std Dev3742− 0.5272
16.84

phiYH2
EntriesMean
Std Dev

0.08

0.06

−40

Cosmic-ray data
Simulation

0.1

0.06

0

phiYH1

0.12

−40

−20

0

9470
− 0.5758
15.01

20
40
Theta angle (y-axis) [degree]

Events [a.u.]

Figure7.30 Distribution of the injection angles for fully contained showers at x-axis (left) and y-axis (right)
startH1
0.14

Cosmic-ray data
Simulation

EntriesMean
Std Dev

3746
12.9
5.102

startH2

0.12

at the central layers than the cosmic-ray data.Entries
This is9470because the low energy particles can not be detected by the
Mean
Std Dev

13.02

5.304
prototype0.1due to the threshold and decline of the MIP
response. The transverse proﬁles for hits and energies and0.08
sum of thenumber of hits and the energy for the fully contained showers also match with the data and simulation

as shown0.06in Fig. 7.32, 7.33, and 7.34. In summary, the simulation reproduces the behavior of the prototype very
0.04 fully contained showers.
well for the
0.02

7.4.3

Showerescape
0
0
5
10
15

20

25
30
Shower start layer

Studies with the cosmic-ray shower event are performed also for the event with a shower escape where a part ofthe shower tail escapes from the prototype. The selection that the sum of hits at the last layer (Layer 29) is morethan 4 is applied. Fig. 7.35 and 7.36 show the examples of the event displays for the selected events using thecosmic-ray data and simulation respectively. Fig. 7.37 shows the distribution of the shower start layer for showerescape events. It can be seen that the shower tends to start at later layers for the shower escape events.
Fig. 7.38 shows the distribution of the injection angle at x-axis (left) and y-axis (right) for midway showers.
Both the distributions for cosmic-ray data and simulation match well, although some ﬂuctuations can be seen due

−20

0

40

Cosmic-ray data
Simulation

35
30

111

Energy [MeV]# of hits

7.4 Performance evaluation using the cosmic-ray shower

12

Cosmic-ray data
Simulation

10

8
25
20

6

15
4
10
2
5
0

0

5

10

15

20

0

25

0

5

10

15

20

25

layer

layer

# of hits

50

40

40

50
35

# of hits# of hits# of hits

Figure7.31 Longitudinal shower proﬁle for fully contained showers of the number of hits (left) and the energy (right)

50

50
35

Cosmic-ray data
Simulation

45

Cosmic-ray data
Simulation

30
45

40
25

35
20

35
20

30
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30
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25
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− 500

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Cosmic-ray data
Simulation

30
45

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Cosmic-ray data
Simulation

45

−1000

− 500

0

500

10

5

1000
y [mm]

5

Energy [MeV]

Simulation

20
25

Cosmic-ray data
Simulation

15
20

Energy [MeV]

Energy [MeV]

Energy [MeV]

Figure7.32 Transverse hit proﬁle for fully contained showers for x-axis (left) and y-axis (right). The origin is
0
0
25
−1000
− 500start point.
0
500
1000
−1000
− 500
0
500
1000
Cosmic-ray data
Cosmic-ray data
set25asthe showerx [mm]y [mm]
Simulation

20
25

20

10

10

15

15

5

5

10

10

0

−1000

− 500

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500

5

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x [mm]

1000
x [mm]

Cosmic-ray data
Simulation

15

0

−1000

− 500

0

500

1000
y [mm]

−1000

− 500

0

500

1000
y [mm]

50

Figure7.33 Transverse energy proﬁle for fully contained showers for x-axis (left) and y-axis (right). The origin
is set as the shower start point.

Chapter 7 Performance

hitsumH1

0.3

Cosmic-ray data

Entries

3742

Simulation

Mean

125

Std Dev

76.53

0.25

Events [a.u.]

Events [a.u.]112

hitsumH2

0.2

Entries

9470

Mean

134.9

0.15

0.1

0.1

0.05

0.05

100

200

300

400

500

Entries

3742

Simulation

Mean

38.29

Std Dev

30.6

enesumH2

0.2

0.15

0
0

Cosmic-ray data

0.25

86.95

Std Dev

enesumH1

0.3

0
0

600
# of hit

50

100

150

200

Entries

9470

Mean

39.97

Std Dev

33.73

250
300
Energy [MeV]

Figure7.34 Distribution of the sum of the number of hits (left) and the energy (right) for fully contained showers.
CR data

CR data0750

Layer position [mm]Layer position [mm]Layer position [mm]

6

0

6

50

5

100

4

150

3

200

2
1

100

5

150

4

200

3

250

2

250

1

300

300

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100

100

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0
X position

−50
/ mm

50
0
−50
/ mm
n
io
−100−100 posit
Y

Layer position [mm]

7

8

100

0

100

50
0
X position

−50
/ mm

50
0
−50
/ mm
n
io
−100−100 positY−1

Figure7.35 Event displays of the shower escape events in the cosmic-ray data. The color bar shows the numberof MIPs, and the hit above 10 MIPs is colored red to make it easier to see the diﬀerence in color.

to the small statistics.

30

Fig. 7.39 shows the longitudinal shower proﬁles for the shower escape events, and Fig. 7.40 and 7.41 show thetransverse proﬁles for the shower escape events. A much larger deviation between the data and the simulation forthe proﬁles of the shower escape events is observed. This is discussed in the next section.
Fig. 7.42 shows the distribution of the sum of the number of hits and the energy for the shower escape events.
The simulation also agrees with the data, but the simulation has less low-energy events compared to the data. To
understand the deviation in more detail, the comparison with the primary energy in the simulation is performed in
the next section.

7.4 Performance evaluation using the cosmic-ray shower

113

Simulation

Simulation

Simulation
7

0.1

50

Layer position [mm]Layer position [mm]

6
100

0.08

5

150
4

0.06

200

3
250

0.04

100

50
0
X position

0.02
−50
/ mm

0

−20

EntriesMean
Std Dev

100

3266− 0.1097
14.76

9

0.12

0.1

7
6

0.08
5
4

0.06

200

3

0.04

100

0

50
0
X position

20

−50
/ mm

40

2

1
100
0.0250
0
m
0
−50
n/m
−100−100 positio
Y
0−40

Events [a.u.]

Figure7.36 Event displays of the shower escape events in theTheta
simulation.
The[degree]
color bar shows the number ofangle (x-axis)
MIPs, and the hit above 10 MIPs is colored red to make it easier to see the diﬀerence in color.
startH1

Cosmic-ray data
Simulation

0.14

EntriesMean
Std Dev

36

1417
19.49
4.779

startH2

0.12

3266
19.5
4.679

EntriesMean
Std Dev

0.1
0.08
0.06
0.04
0.02
0
0

5

10

15

20

25
30
Shower start layer

phiXH1

Cosmic-ray data
Simulation

0.1

EntriesMean
Std Dev1413−1.684
16.57

phiXH2
EntriesMean
Std Dev

0.08

3266− 0.1097
14.76

Events [a.u.]

Events [a.u.]

Figure7.37 Distribution of the shower start layers for shower escape events.
0.12

0.04

0.02

0.02

0

0

20
40
Theta angle (x-axis) [degree]

EntriesMean
Std Dev

−40

−20

0

Events [a.u.]

startH1

0.12
0.1
0.08

Cosmic-ray data
Simulation

EntriesMean
Std Dev

1417
19.49
4.779

startH2
EntriesMean
Std Dev

3266
19.5
4.679

3266
− 0.2923

20
40
Theta angle (y-axis) [degree]

Figure7.38 Distribution of the injection angles for midway showers at x-axis (left) and y-axis (right)
0.14

1413
− 0.1302
15.76

phiYH2
EntriesMean
Std Dev

0.08

0.04

−20

Cosmic-ray data
Simulation

0.1

0.06

−40

phiYH1

0.12

0.06

0

C
S

8

150

300

1
100
50
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m
0
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n/m
−100−100 positio
Y−40

phiXH2

250

2

300

1413
−1.684
16.57

EntriesMean
Std Dev

Layer position [mm]50phiXH1data
8Cosmic-ray
0

Events [a.u.]0Layer position [mm]Events [a.u.]

9

0.12

14.14

−20

Chapter 7 Performance

40

Cosmic-ray data
Simulation

35
30

Energy [MeV]# of hits

114

12

Cosmic-ray data
Simulation

10

8
25
20

6

15
4
10
2
5
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0

5

10

15

20

0

25

0

5

10

15

20

25

layer

layer

50

Cosmic-ray data
Simulation

45# of hits# of hits

Figure7.39 Longitudinal shower proﬁle for shower escape events of the number of hits (left) and the energy (right)

Cosmic-ray data
Simulation

45
40

50
35

Cosmic-ray data
Simulation

45
30# of hits# of hits

40

50

50
35

40
25

40
25

35
20

35
20

30
15

30
15

25
10

25
10

20
5

20
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15
0
−1000
10

− 500

0

500

Cosmic-ray data
Simulation

45
30

15
0
−1000
10

1000
x [mm]

5

− 500

0

500

1000
y [mm]

5

Simulation
20
25

Cosmic-ray data
Simulation

15
20

Energy [MeV] Energy [MeV]

Energy [MeV] Energy [MeV]

Figure7.40 Transverse hit proﬁle for shower escape events for x-axis (left) and y-axis (right). The origin is set
00
25 −1000−1000− 500 point. 0
500
1000
− 500
0
500
1000
as25theshower startCosmic-ray xdata
Cosmic-ray ydata
[mm]
[mm]
Simulation
20
25

20

10

10

15

15

5

5

10

10

0

−1000
5

− 500

0

500

1000
x [mm]

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− 500

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500

1000
x [mm]−1000

Cosmic-ray data
Simulation

15

0

−1000
5

− 500

0

500

1000
y [mm]

0

− 500

0

500

1000
y [mm]−1000

Figure7.41 Transverse energy proﬁle for shower escape events for x-axis (left) and y-axis (right). The origin
is set as the shower start point.

hitsumH1

0.3

Cosmic-ray data

Entries

1413

Simulation

Mean

156.1

Std Dev

113.2

0.25

hitsumH2

0.2

Entries

3266

Mean

173.6

Std Dev

Events [a.u.]

enesumH1

0.3

Cosmic-ray data

Entries

1413

Simulation

Mean

59.32

Std Dev

54.62

0.25

enesumH2

0.2

126.7

0.15

Entries

3266

Mean

68.85

Std Dev

59.69

0.15

Events [a.u.]

0.1

0.05

0
0

115

100

0.45

Muon: 83.389652
Electron: 2.164731

0.4

Gamma: 13.600845
Others: 0.844773

200 0.35300

pdgH11

0.1

0.5

0.05

400

500

0
0

600
# of hit

50

Entries

7897

Mean

2.883e+04

Std Dev

3.054e+04

100

150

200

Events [a.u.]

Events [a.u.]

7.4 Performance evaluation using the cosmic-ray shower

0.5
0.45

Muon: 8
Electron

0.4

Gamma
Others:250 0.35 300
Energy [MeV]

0.3

0.3

Figure7.42 Distribution
0.25 of the sum of the number of hits (left) and energies (right) for shower escape
0.25 events
0.2

0.2

0.15

0.15

7.4.4 Comparison of0.1
primary energy in simulation

0.1

0.05

0.05

and the shower escapeFig. 7.43 shows the comparison of the primary energy for the fully contained showers
3
× 10
0

0

0
20
60
80
100 120160 180200
02040events. The shower escape events
have40more
highenergyevents.140The
diﬀerence
Energy[MeV] between the fully contained

60

80

1

energyH1

0.25

Fully contained
Shower escape

0.2

Entries

9470

Mean

2.398e+04

Std Dev

2.985e+04

EventsEvents [a.u.]

showers and shower escape events may be due to this diﬀerence in primary energy of the incident particle.

Show
500

After

energyH2
Entries

3266

Mean

2.981e+04

Std Dev

3.439e+04

400

0.15
300
0.1
200

0.05

100

3

0
0

20

40

60

80

100

120

140

× 10
160 180200
Energy [MeV]

0
0

5000

Figure7.43 Distribution of the primary energy for the fully contained shower (blue) and shower escape events (red)Fig. 7.44 shows examples of the event displays in the simulation with the lower primary energies, and Fig. 7.45
shows the events with the higher primary energies. The shower events from the high-energy particles create larger
showers and have more high-energy hits compared to the events from the low-energy particles.
The distribution of the primary energy in the simulation is adjusted by hand for better agreement with the shower
proﬁles in data. Fig. 7.46 shows the distribution of the primary energy after the energy suppression (green) and

10000

15

Chapter 7 Performance

116
Simulation

Simulation

8

7

0

0
7

6

6
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4
200

3

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300
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X position

−50
/ mm

−100−100

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it
s
o
p
Y

Layer position [mm]Layer position [mm]

100

5

100

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150

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200

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250

1

300

Layer position [mm]50

Layer position [mm]

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2
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−50
/ mm

−100−100

50
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m
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n/m
io
it
s
o
p
Y

0

Figure7.44 Event displays of the shower escape events in the simulation with the energy of 1 GeV (left) and 9 GeV (right).
Simulation

Simulation
38
9

9
0

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8
50

6

150

5
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Layer position [mm]Layer position [mm]100

Layer position [mm]

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X position

−50
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Y

Layer position [mm]

0

300
100

50
0
X position

−50
/ mm

1
100
50
0
m
0
−50
n/m
−100−100 positio
Y

Figure7.45 Event displays of the shower escape events in the simulation with the energy of 89 GeV (left) and
112 GeV (right).

for all shower escape events for comparison (red). The shower escape events are suppressed linearly depending on
the primary energy, i.e., suppressed by 3 × (energy)%.
Fig. 7.47, 7.48, and 7.49 shows the shower proﬁles after the energy suppression in the simulation, where all the
shower escape events are used in the cosmic-ray data. Fig. 7.50 shows the distributions of the sum of the numberof hits and the energy after the suppression in the simulation. All the distributions in the simulations show a muchbetter agreement with the cosmic-ray data.
In summary, the observed deviation in the shower distributions between the simulation and the data is likely due
to a problem of the energy distribution in the high energy region in the simulation. The discontinuous distributionof the cosmic-ray energy shown in Fig. 7.12 may not reproduce the actual cosmic-ray energy spectrum, and thismay cause the deviation between the data and simulation. However, in the adjusted environment such as the fully

0.2
0.15
0.1
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3

100

120

140

3

× 10
160 180200
Energy [MeV]

0
0

20

40

60

80

100

120

× 10
160 180200
Energy [MeV]140

7.4 Performance evaluation using the cosmic-ray shower

y contained

wer escape

9470

Mean

2.398e+04

Std Dev

2.985e+04

EventsenergyH1
Entries117
enecompH1

Shower escape
500

Entries

3266

Mean

1.127e+04

Std Dev

After suppression

energyH2
Entries

3266

Mean

2.981e+04

Std Dev

3.439e+049042

enecompH2
EntriesMean
Std Dev

400

1357
7445
7814

300

200

100

3

140

× 10
160 180200
Energy [MeV]

0
0

5000

10000

15000

20000

25000
30000
Energy [MeV]

Figure7.46 Distribution of the primary energy after the suppression (green) and all shower escape events (red)contained shower and the shower escape with the energy suppression, the data and simulation match well. At leastin such an environment, the Sc-ECAL can measure the showers successfully.

40

Cosmic-ray data
Simulation

35
30

Energy [MeV]120# of hits

100

12

Cosmic-ray data
Simulation

10

8
25
20

6

15
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10
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0

5

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15

20

0

25
layer

0

5

10

15

20

25
layer

Figure7.47 Longitudinal shower proﬁle for midway showers of hits (left) and energies (right) after the selection.

Chapter 7 Performance

Cosmic-ray data
Simulation

45# of hits

40
50
35
45
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50# of hits

118

Cosmic-ray data
Simulation

− 500

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x [mm]

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Cosmic-ray data
Simulation

45
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Cosmic-ray data
Simulation

− 500

0

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1000
y [mm]

5

−1000
25

− 500

0

500

1000

Energy [MeV] Energy [MeV]

Energy [MeV] Energy [MeV]

Figure7.48
Transverse hit proﬁle for midway showers for x-axis(left) and y-axis (right) after the selection.
00[mm]
Cosmic-ray xdata
Simulation

20
25

Cosmic-ray data
Simulation

15
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Cosmic-ray data
Simulation

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Cosmic-ray data
Simulation

10
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hitsumH1

0.3

Cosmic-ray data

Entries

1413

Simulation

Mean

156.1

Std Dev

113.2

0.25

hitsumH2

0.2

Entries

1366

Mean

165.6

Std Dev

121.7

Events [a.u.]

Events [a.u.]

Figure7.49 Transverse energy proﬁle for midway showers for x-axis (left) and y-axis (right) after the selection.

0.1

0.1

0.05

0.05

200

300

400

500

600
# of hit

Entries

1413

Simulation

Mean

59.32

Std Dev

54.62

enesumH2

0.2

0.15

100

Cosmic-ray data

0.25

0.15

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enesumH1

0.3

0
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50

100

150

200

Entries

1366

Mean

62.16

Std Dev

54.11

250
300
Energy [MeV]

Figure7.50 Distribution of the sum of the number of hits (left) and energies (right) after the selection.

119

Chapter 8

New method for the saturation correction
A new method for the measurement and correction of the saturation of the SiPM is developed. The saturation
is an issue for the detector using SiPMs involving the Sc-ECAL, which have many pile-up hits. The saturation
curve is usually measured by directly injecting fast visible light pulse to SiPM [53][54], but this method doesn’t
consider the crucial eﬀects of the time constant of the emission of the scintillation light. New idea is to measure
the SiPM saturation with the scintillation light excited by the UV light pulse. This allows to measure the saturationin the real situation including the eﬀect of the time constant of the scintillation emission. A new modeling of the
SiPM saturation containing the eﬀect of the new method is developed, and the model is validated by comparing
the results with measurements.
This chapter describes the new method and the modeling of the SiPM saturation.

8.1 Saturation
The SiPM is widely used in high energy experiments. The SiPM has many advantages such as the high gain
with a bias voltage lower than 100 V, small size and so on. One disadvantage is the non-linear response at highinput light intensities. When a large number of photons are injected to a SiPM, the output of the SiPM can besaturated due to the limited number of pixels. The saturation of the SiPM can be an issue for calorimeters using
SiPMs, especially for the electromagnetic calorimeter involving the Sc-ECAL, because the narrow and dense EM
shower creates many pile-up hits.
The non-linear response of the SiPM, called saturation curve, is usually measured by directly injecting fastvisible light pulse (∼400 nm) to a SiPM. However, this conventional method doesn’t include the eﬀect of the time
constant of the emission of the scintillation light (few ns), which is not negligible compared to the recovery timeof the SiPM pixel (dozens ns). New idea is to measure the SiPM saturation with the scintillation light excited by
the UV light pulse. The saturation curve measured by this method includes the eﬀect of the pixel recovery during
the scintillation emission, and can directly be used for the saturation correction in calorimeters using scintillators
and SiPMs.

8.2 Saturation measurement
The saturation curve is measured using the UV light. This section gives the experimental setup, analysis process,calibration, the results of the saturation measurement.

Chapter 8 New method for the saturation correction

120

8.2.1

Setup

A sub-nanosecond UV pulse LED with a wavelength of 255 nm, PLS-255 produced by PicoQuant [55], is used
to excite the scintillation light. Fig. 8.1 shows the wavelength spectrum of the PLS-255. Scintillation can be
excited in the typical plastic scintillator by injecting the UV light with the wavelength below 300 nm, while the
SiPM is not sensitive to the UV light below 300 nm as shown in Fig. 8.2.

Figure8.1 Wavelength spectrum of the PLS-255 [55]Figure8.2 Photon detection eﬃciency against wavelength for S12571-025P [37]

8.2 Saturation measurement

121

A scintillator, EJ-200 produced by Eljen [56], of 2 mm × 2 mm × 2 mm coupled to a SiPM is used. The EJ-200
is a commercial PVT scintillator, which is equivalent to the BC-408 used for the Sc-ECAL prototype, as shown in
Table 8.1. The SiPM used in the measurement is Hamamatsu S12571-025P. The S12571-025P is the same series
as the SiPMs used in the prototype (S12571-010P and S12571-015P), but with a large pixel (25 µm-pitch) because
the light intensity of the PLS-255 is too low for the saturation measurement with the SiPM of the prototype withthe small pixel (10 µm-pitch and 15um µm-pitch).
Table8.1 Performance parameters of BC-408 and EJ-200

Parameter

BC-408

EJ-200Light output

64%

64%

Rise time

0.9 ns

0.9 ns

Decay time

2.1 ns2.1 nsWavelength of maximum emission

425 nm

425 nmLight Attenuation length

210 cm380 cmFig. 8.3 shows the experimental setup for the saturation measurement. The UV light is focused by a convex
lens, passes through a variable ND ﬁlter and a band-pass ﬁlter, and then enters the scintillator. The variable ND
ﬁlter controls the light intensity, and the band-pass ﬁlter allows only the wavelength from 250 nm to 270 nm topass through. The scintillator is excited by the injected UV light, and the SiPM detects the scintillation light.
The operating voltage of the SiPM is the recommended voltage by Hamamatsu Photonics. The photomultipliertube (PMT), which has a much wider dynamic range, is used to conﬁrm that the linear relationship between the
excited scintillation light and the incident light intensity. The temperature of the SiPM is monitored by a Pt-100
temperature sensor placed behind the SiPM.
Variable ND lter
Convex lensBand pass lter

PMT

UV LED

Temperature sensor
Scintillator

SignalSiPM S12571-025P

Figure8.3 Experimental setup for the saturation measurement using the UV light
Shading

Convex lens

8.2.2 Measurement
PMT

Band pass lter

UV LED

Fig. 8.4 shows the typical saturation curve measured by the visible light pulse. Nseed is the expected numberof photoelectrons when assuming no saturation, and Ndet is the number of photoelectrons detected by the SiPM.
The saturation curve can be obtained by scanning the light intensities. In this measurement, the Nseed is measured
3by the photodiode, and the Ndet is measured by the
SiPM. They
usually
expressed in units of the number of
Scintillator
2 2 are2 mm

photoelectrons, but in this measurement, they are measured as current because it is not possible to analyze the
PCB

SiPM S12571-025P

Light shieldby black paper& aluminumfifi

1Chapter 8 New method for the saturation correction

122

whole range in units of the number of photoelectrons. The current is converted to the number of photoelectronsby simultaneously measuring the number of photoelectrons at the low light intensities, as explained in the next

Ndet [p.e.]section.

Nseed [p.e.]

Figure8.4 Saturation curve measured by the visible light pulse [40]18

The new method is composed of three types of measurements as shown in Fig. 8.5;
• The signal from the SiPM is monitored at low light intensity in units of the number of photoelectrons by awaveform digitizer. (The signal from the PMT is also monitored by the waveform digitizer)• The signal from the SiPM is read by a picoammeter over the whole light intensity range• The light intensity is monitored by a photodiodeThe saturation curve is measured by performing the three sets of the measurements at each light intensity.
At the ﬁrst measurement, the signal from the SiPM is measured in units of the number of photoelectrons. The
waveform digitizer, DRS4 produced by the Paul Scherrer Institute [57], is used. The charge by integrating thesignal waveform is converted to the number of photoelectrons using the single photoelectron charge measured by
the dark noise spectrum. However, the dynamic range of the DRS4 is limited, so this measurement using the DRS4
is performed only in the region of low light intensity. The signal from the PMT is also measured by the DRS4 to
conﬁrm the linearity of the scintillation emission. The scintillation light which injects to the PMT is very small
due to the material between the scintillator and PMT, so the signal from the PMT can be measured by the DRS4
at the whole range of the light intensities.
At the second measurement, the signal from the SiPM is measured by the picoammeter in the whole range of thelight intensities. The model 6487 picoammeter, produced by the Tektronix [58], onboards the feedback ammeterand double-Integrating analogue-to-digital converter. The signal from the SiPM is integrated and converted to the8.2 Saturation measurement

123
Scintillator SiPMUV LED

PMT

Signal→Amp

Switching

Waveform digitizer

Signal→PMT←HV
Signal→PhotodiodeWaveform
Picoammeter
digitizer←HV

Picoammeter

Signal→Figure8.5 Readout method for the saturation measurement

current. The dynamic range of the DRS4 is too small to measure the saturation curve at the whole range, but thepicoammeter has enough dynamic range.
At the third measurement, the UV light intensity is monitored by the photodiode. The photodiode, S12689-02
produced by Hamamatsu Photonics is used. The S12689-02 is a UV-sensitive photodiode and has large dynamic
range enough to monitor the whole range of the light intensities. The signal from the photodiode is measured as
current by the picoammeter.

16

8.2.3 Calibration
The current of the SiPM and photodiode is converted to the number of photoelectrons using the linearity of
the SiPM response at the low light intensity. Fig. 8.6 shows the correlation between the current and the numberof photoelectrons. The signal from the SiPM is monitored in units of the number of photoelectrons at low lightintensity by dividing the measured charge by the single photoelectron gain. The signal is linear against the injected
light intensity at low light intensity. The current of the SiPM signal is converted to the Ndet by multiplying theslope of the correlation by the current. The current of the photodiode is also converted to the Nseed .
sipm current vs sipm p.e.

photodiode current vs sipm current

χ2 / ndf
p0

50

SiPM current [A]

SiPM photoelectron [p.e.]−6

213.4 / 15
4.392e+07 ± 4.264e+04− 1.335 ± 0.02622

p1

×10
3.5

χ2 / ndf

3

0.7333 / 30

p02.789e+04 ± 523.3

p1−7.755e−08 ± 3.072e− 08

2.5

40

2

30
1.5

20
1

10
0.5
−6

×10
0.2

0.4

0.6

0.8

1

1.2
SiPM current [A]

−9

×10
0

0.02

0.04

0.06

0.08

0.1
0.12
photodiode current [A]Figure8.6 Correlation between the SiPM current and the number of photoelectrons (left), and correlation
between the photodiode current and SiPM current (right).

Fig. 8.7 shows the results of the linearity of the scintillation light emission. The signal from the PMT increases
linearly as the intensity of the UV light increases. Then, the linearity of the scintillation light emission is conﬁrmed.

Chapter 8 New method for the saturation correction

124
PMT [p.e.]

relation of UVLED intensity and scintillation emission
χ2 / ndf
7697.1 / 93

p0

1.735e+09 ± 1.189e+06

p1− 0.1582 ± 0.0007987

6
5
4
3
2
1
0

−9

×10
0

0.5

1

1.5

2

2.5

3

3.5
4
4.5
photodiode current [A]Figure8.7 Linearity of the scintillation light emission measured by the PMT as a function of the photodiode current.

Fig. 8.8 shows the stability of the temperature of the SiPM. The temperature is quite stable during the measurement.
temperature [C]MPPC temperature
30

25

20

15

10

5

0
0

5000

10000

15000

20000

25000

30000

35000

40000
time [sec]Figure8.8 Stability of the temperature of the SiPM during the measurement.

Fig. 8.9 shows the comparison of the signal waveform derived by the UV light, visible light, β -ray from 90Sr.
The waveform with the UV light and β -ray matches well because both the UV and β -ray excite the scintillation
light. The waveform with the visible light is diﬀerent from the others, because the visible light directly injects to
the SiPM and makes the waveform sharp. This results show that the UV light excites the scintillation light.

8.2.4

Results

The black plots in Fig. 8.10 show the measured saturation curve using the UV light. A large over-saturation isobserved. For comparison, the same measurement is performed with the conventional method using the visible
light pulse, as shown in the red plots in Fig. 8.10. There is the signiﬁcant diﬀerence between the saturation curves
with the UV light and visible light, and the saturation recovery can be seen at the new method. This shows that the[a.u.]

8.2 Saturation measurement

125

waveform comparison

0.14

UV light

0.12

Visible light
0.1

Sr90

0.08
0.06
0.04
0.02
0

−6

×10
0.3

0.31

0.32

0.33

0.34

0.35
[sec]

Figure8.9 Comparison of the signal waveform with the UV light (red), visible light (blue), and β -ray from 90Sr.

N_det [p.e.]eﬀect of the time constant of the scintillation light emission has a big eﬀect on the saturation curve.

2000

17

1800
1600
1400
1200
1000

UV
Visible

800
600
400
200
0
0

1000

2000

3000

4000

5000
6000
N_seed [p.e.]

Figure8.10 Saturation curves measured with the UV light (black) and the visible light (red). The number ofpixels of the S12571-025P is 1600.

A PLS-500, a similar LED to the PLS-255 with the wavelength of around 500 nm, is used in the conventional
method. The pulse widths of the PLS-255 and PLS-500 are about 0.4 ns and 0.9 ns respectively. The eﬀect ofthe pulse width is not crucial for the new method using the PLS-255, because the pulse width of 0.4 ns is smaller
than the recovery time of the SiPM pixel (dozens ns) and the time constant of the scintillation light emission (fewns), and the eﬀect of the pulse width can be convoluted by the scintillation light emission. On the other hand, theeﬀect of the pulse width is crucial to the conventional method using the PLS-500. The pulse width of 0.9 ns israther larger than the fast laser pulse used in the previous studies [53][54] with the pulse width of few ps to dozens
ps. The eﬀect of the pulse width may aﬀect the saturation curve, and is one of the causes of the over-saturation at
the conventional method using the PLS-500. However, the diﬀerence between the saturation curves with the new
method and conventional method is clearly seen, so it’s not a problem.
This results can be a big impact on the saturation correction for the detectors using the scintillators and SiPMs.

Chapter 8 New method for the saturation correction

126

The conventional method using the visible light pulse doesn’t consider the time constant of the scintillation lightemission. It doesn’t measure the accurate saturation curve, and the saturation correction is not perfect. The new
method can provide the saturation curve in the same way in a real situation, and the measured saturation curve
can be directly applied to the saturation correction of the Sc-ECAL. This new method can be applied to the otherdetectors using the scintillators and SiPMs.
The actual saturation curve contains the eﬀect of the time constant of the scintillation light emission, but in
usual, the modeling of the saturation including this eﬀect is not suﬃciently validated, and the saturation is notcorrected accurately. The eﬀect of the scintillation light emission is rather big, so the modeling and correction of
the saturation should be validated thoroughly.

8.3 ModelingA new modeling of the saturation curve is needed for the validation of the new method and for the simpliﬁcationof the saturation correction. The accurate modeling of the saturation makes it easy to apply to the other detectors
using the scintillators and SiPMs. The modeling of the saturation involving the eﬀect of the time constant of thescintillation light emission is not validated. The modeling with the cross-talk and after-pulse and the modelingthe response of a recovering SiPM was suggested [53] [59]. However, there is no model that includes all theeﬀects such as the time constant of the scintillation light emission, recovery time of the SiPM, and cross-talk andafter-pulse.
A new modeling of the saturation, involving all the eﬀects of the time constant of the scintillation light emission,
recovery time of the SiPM, and cross-talk and after-pulse, is developed. Since it is diﬃcult to include time
information in statistical methods, the analytical method is used for the modeling. The number of detected photons
relative to the number of incident photons is calculated at each event, and the saturation curve is obtained byscanning the number of incident photons. The calculation procedure in the new model is summarized as follows:• Divide the time periods at 1 event• Calculate the number of incident photons ∆I at each period• Calculate the number of detected photons Ndet at each period• Sum the Ndet at all the time periods

8.3.1

Scintillation light emission

The scintillation light emission has the time constant. In case of the EJ-200, the rise time is τrise = 0.9 ns andthe decay time is τdecay = 2.1 ns. The time-dependent function of the scintillation light emission is described as:∫
I(t) = I0 (t) × (e−u/τdecay − e−u/τrise )du(8.1)
t

where, I(t) is the number of incident photons as a function of the time, and I0 (t) is the initial value dependingon time due to the time-dependent function of the UV-LED. The full width at half maximum of the light pulse(FWHM) of the UV-LED is about 0.5 ns as shown in Fig. 8.11. The light pulse is approximated by the Gause
function with the FWHM of 0.5 ns:(t−1.5[ns])2

I0 (t) = I0 e

− 2(0.5/2.35)2(8.2)

8.3 Modeling127

where the Gause function is shifted by 1.5 ns to start the analysis from the beginning of the pulse. Then, the timedependent function of the incident photons are described like the convolution of the latter exponential term ofFunction 8.1 and Function 8.2.

Figure8.11 Light pulse of the UV-LED [55].

The time range for the calculation of the incident photons and detected photons is set from 0 to 100 ns. The time
range is divided by 0.1 ns pitch. The number of incident photons is calculated at this time period, and the function
at the time of t is written by:∆I(t) =t∑i =t(t −1.5[ns])2

I0 e

i− 2(F W
HM/2.35)2

ti =0∫ t+∆t∆t ×(e−(u−ti )/τdecay − e−(u−ti )/τrise )du

(8.3)

t

where ∆t is the pitch of the time period (0.1 ns).

8.3.2 Recovery time for SiPM pixel
When the incident light has a time constant, there is a possibility that a photon will be injected again while theﬁred pixel is recovering, and this eﬀect must be considered. In that case, an avalanche occurs at a reduced gain.
The over-voltage Vover of the ﬁred pixel drops to zero, and recovers exponentially with a time constant:
Vover (t) = V0 (1 − e−t/τrec )(8.4)

where t is the time from the ﬁrst pixel trigger, τrec is the recovery time of the pixel, and V0 is the initial over-voltage
with no photon injection. While the pixel is recovering, the PDE εrec (t) and gain qrec (t) depend on the Vover (t)almost linearly:
Vover (t)V0Vover (t)qrec (t) = q0
V0εrec (t) = ε0

(8.5)
(8.6)

where ε0 and q0 are the PDE and gain with the over-voltage of V0 .
In this model, ε0 = 1 and q0 = 1. The number of incident photons at a short time period, ∆I(t), are incident on
the SiPM at all, so ε0 = 1. If a photon injects to the pixel with the over-voltage of V0 , the pixel detects just one

Chapter 8 New method for the saturation correction

128

photon, so q0 = 1. Then, the number of photons injected to the SiPM, Nin (t), and the number of photons detectedby the SiPM, Ndet (t), can be written by:
Nin (t) = ∆I(t) × εrec (t) = ∆I(t) × (1 − e−t/τrec )Ndet (t) = ∆I(t) × εrec (t) × qrec (t) = ∆I(t) × (1 − e

8.3.3

(8.7)
−t/τrec 2

(8.8)

)

Calculation of number of detected photons

The calculation of Ndet (t) is performed for each time period. The number of incident photons, ∆I(t), is
calculated at each period, and the number of detected photons are calculated using the ∆I(t). The pixels which
detect photons at t, Nt , and the pixels with no photon injection until t, Nempty , is stored at each period. For
example, at the ﬁrst time period of t = t0 = 0 ns,(8.9)(8.10)(8.11)(8.12)Nin (t0 ) = ∆I(t0 )Ndet (t0 ) = ∆I(t0 )Nempty (t0 ) = Npixel − ∆I(t0 )Nt0 (t0 ) = ∆I(t0 )where Npixel is the number of pixels of the SiPM.
At the second time period of t = t1 = 0.1 ns, the ∆I(t1 ) injects to the SiPM, and the empty pixels (Nempty )can detect the injected photons, but the ﬁred pixel (Nt0 ) must consider the eﬀect of the pixel recovery. The pixels
which detect photons at t1 , Nt1 , is stored apart from Nt0 . The Nempty and Nt0 are updated by subtracting thenumber of photons injected at t1 . Then, at t = t1 = 0.1 ns,
Nt (t0 )Nempty+ ∆I(t1 ) × 0
× (1 − e−(t1 −t0 )/τrec )NpixelNpixelNemptyNt (t0 )Ndet (t1 ) = ∆I(t1 ) ×+ ∆I(t1 ) × 0
× (1 − e−(t1 −t0 )/τrec )2
NpixelNpixelNemptyNempty (t1 ) = Nempty (t0 ) − ∆I(t1 ) ×
NpixelNt (t0 )Nt0 (t1 ) = Nt0 (t0 ) − ∆I(t1 ) × 0
× (1 − e−(t1 −t0 )/τrec )NpixelNt1 (t1 ) = Nin (t1 )Nin (t1 ) = ∆I(t1 ) ×(8.13)(8.14)(8.15)(8.16)(8.17)
Nt0
is the probability that ∆I(t1 ) injects to the empty pixels, and Npixelis the probability that ∆I(t1 )where NNempty
pixel

injects to the pixels ﬁred at t0 .

8.3 Modeling129

The gradual expression at the time period t, where t′ is the time period just before t, t′ = t − 0.1, is described as:∆I(t) =t∑i =t(t −1.5[ns])2

I0 e

i− 2(F W
HM/2.35)2∫ t+∆t∆t ×(e−(u−ti )/τdecay − e−(u−ti )/τrise )du(8.18)

t

ti =0
′

t∑
i =t
NemptyNt (t′ )Nin (t) = ∆I(t) ×+∆I(t) × i
× (1 − e−(t−ti )/τrec )Npixel
N
pixel
t =0

(8.19)i′

Ndet (t) = ∆I(t) ×t∑
i =t
Nt (t′ )Nempty+∆I(t) × i
× (1 − e−(t−ti )/τrec )2
Npixel
N
pixel
t =0

(8.20)i′

Nempty (t) = Nempty (t ) − ∆I(t) ×
Nti (t) = Nti (t′ ) − ∆I(t) ×

Nempty× (1 − e−(t−ti )/τrec )NpixelNti (t′ )× (1 − e−(t−ti )/τrec )Npixel(8.21)(8.22)(8.23)Nt (t) = Nin (t)These steps are repeated to calculate Ndet (t) at each time period. As a result, the total number of incident
photons and detected photons are written by:
Nint =

ti =100∑ ns∆I(ti )

(8.24)

Ndet (ti )(8.25)

ti =0

Ndet =

ti =100∑ ns
ti =0

The saturation curve is obtained by scanning the initial value of the incident photons, I0 . The saturation curveconsidering the eﬀect of the time constant of the scintillation light emission and the SiPM recovery can be obtainedby this method.

8.3.4 Cross-talk
The eﬀect of the cross-talk is implemented to this model. The SiPM causes a crosstalk with a certain probability,
PCT , resulting in a state where infrared photons are detected in surrounding pixels. The number of infrared photons

caused by the cross-talk depend on the number of photons injected by the scintillation emission. The detected
photons by the scintillation emission and those by the cross-talk are calculated separately and summed up. For
example, at t = t0 = 0 ns,
Nin (t0 ) = ∆I(t0 )(8.26)

2
9∆ICT (t0 ) = Nin (t0 ) × (PCT + PCT+ · · · + PCT)(8.27)(8.28)

Ndet (t0 ) = (Ndet Calculation using ∆I(t0 )) + (Ndet Calculation using ∆ICT (t0 ))2
where ∆ICT (t0 ) is the number of incident photons caused by the cross-talk, and (PCT + PCT+ · · · ) considers thesecond-, third-, · · · , ninth-order eﬀects of the cross-talk.
At t = t1 = 0.1 ns,
Nin (t1 ) = ∆I(t1 ) ×

NemptyNt (t0 )+ ∆I(t1 ) × 0
× (1 − e−(t1 −t0 )/τrec )NpixelNpixel2∆ICT (t1 ) = Nin (t1 ) × (PCT + PCT+ ···)

Ndet (t2 ) = (Ndet Calculation using ∆I(t1 )) + (Ndet Calculation using ∆ICT (t1 ))(8.29)(8.30)(8.31)

Chapter 8 New method for the saturation correction

130

The gradual expression of the model at the time period t, where t′ is the time period just before t, t′ = t − 0.1, is
described as:
′

t∑
i =t
NemptyNt (t′ )Nin (t) = ∆I(t) ×+∆I(t) × i
× (1 − e−(t−ti )/τrec )Npixel
N
pixel
t =0

(8.32)

i

′

t∑
i =t
NemptyNt (t′ )Ndet (t) = ∆I(t) ×+× (1 − e−(t−ti )/τrec )2∆I(t) × i
Npixel
N
pixel
t =0

(8.33)i

Nempty (t) = Nempty (t′ ) − ∆I(t) ×
Nti (t) = Nti (t′ ) − ∆I(t) ×

Nempty× (1 − e−(t−ti )/τrec )NpixelNti (t′ )× (1 − e−(t−ti )/τrec )Npixel2∆ICT (t) = Nin (t) × (PCT + PCT+ ···)(8.34)(8.35)(8.36)′Nin (t) = Nin (t) + ∆ICT (t) ×t∑i =tNemptyNt (t)+∆ICT (t) × i× (1 − e−(t−ti )/τrec )Npixel
N
pixel
t =0

(8.37)

i

′

t∑
i =t
Nt (t)
Nempty∆ICT (t) × i
Ndet (t) = Ndet (t) + ∆ICT (t) ×+× (1 − e−(t−ti )/τrec )2
Npixel
N
pixel
t =0

(8.38)i

Nempty (t) = Nempty (t) − ∆ICT (t) ×
Nti (t) = Nti (t) − ∆ICT (t) ×

Nempty× (1 − e−(t−ti )/τrec )NpixelNti (t)× (1 − e−(t−ti )/τrec )Npixel(8.39)(8.40)(8.41)Nt (t) = Nin (t)In this way, the eﬀect of the cross-talk is implemented to the model by adding the Ndet calculation at each time
period using the number of infrared photons caused by the cross-talk.

8.3.5

After-pulse

The eﬀect of the after-pulse is also implemented. The after-pulse occurs with a certain probability PAP and time
period τAP :NAP (t) = PAP

1 −t/τAPe
τAP(8.42)

where NAP (t) is the number of photons (avalanches) caused by the after-pulse. The number of photons caused by
the after-pulse depend on the number of ﬁred photons and the time diﬀerence from the ﬁrst photon injection. For
example, at t = t0 = 0 ns, there is no after-pulse. At t = t1 = 0.1 ns,
1 −(t1 −t0 )/τAPe
τAP
1 −(t1 −t0 )/τAP
Nt0 (t1 ) = Nt0 (t0 ) − Nt0 (t0 ) × PAPetAP
Ndet (t1 ) = (Ndet Calculation using ∆I(t1 )&Nt0 (t1 )) + NAP (t1 ) × (1 − e−(t1 −t0 )/τrec )2
NAP (t1 ) = Nt0 × PAP(8.43)(8.44)(8.45)

Since NAP (t1 ) is treated as pixels ﬁred at t1 , Nt0 is updated by subtracting NAP (t1 ). The number of detected
photons by after-pulse is also aﬀected by the pixel recovery, so the PDE and gain dependence is considered. Thenthe total number of detected photons at t1 is sum of the Ndet calculated by the ∆I(t1 ) using updated Nt0 , and theNdet calculated by the NAP (t1 ).

8.3 Modeling131

The gradual expression of the model at the time period t, where t′ is the time period just before t, t′ = t − 0.1, is
described as:
NAP (t) =

′
t∑
i =t

Nti × PAP

ti =0

1
τAP

e−(t−ti )/τAP(8.46)

Nempty (t) = Nempty (t′ )(8.47)

Nti (t) = Nti (t′ ) − Nti (t′ ) × PAP

1 −(t−ti )/τAPetAP(8.48)

′

′

t∑
t∑
i =t
i =t
NemptyNti (t)−(t−ti )/τrec
Nin (t) = ∆I(t) ×+× (1 − e)+∆I(t) ×
NAP (ti ) × (1 − e−(t−ti )/τrec )Npixel
N
pixel
t =0
t =0
i

i

(8.49)′

Ndet (t) = ∆I(t) ×

′

t∑
t∑
i =t
i =t
NemptyNt (t)+∆I(t) × i
× (1 − e−(t−ti )/τrec )2 +NAP (ti ) × (1 − e−(t−ti )/τrec )2
Npixel
N
pixel
t =0
t =0
i

i

(8.50)
Nempty (t) = Nempty (t) − ∆I(t) ×
Nti (t) = Nti (t) − ∆I(t) ×

NemptyNpixelNti (t)× (1 − e−(t−ti )/τrec )NpixelNt (t) = Nin (t)(8.51)(8.52)(8.53)In this way, the eﬀect of the after-pulse is implemented to the model by adding the Ndet calculation at each time
period using the number of photons caused by the after-pulse.

8.3.6 Model
The new saturation model is completed combining all the eﬀects described in the previous sections. The time
period for the calculation can be adjusted according to the SiPM types. In case of the comparison with themeasurement using the S12571-015P, it is set as 100 ns divided by 0.1 ns pitch. The gradual expression of theChapter 8 New method for the saturation correction

132

model at the time period t, where t′ is the time period just before t, t′ = t − 0.1, is described as:∆I(t) =t∑i =t(t −1.5[ns])2

I0 e

i− 2(F W
HM/2.35)2∫ t+∆t∆t ×

ti =0

NAP (t) =(e−(u−ti )/τdecay − e−(u−ti )/τrise )du(8.54)

t

′
t∑
i =t

Nti × PAPti =0

1 −(t−ti )/τAPetAP(8.55)

Nempty (t) = Nempty (t′ )(8.56)

Nti (t) = Nti (t′ ) − Nti (t′ ) × PAP

1tAP

e−(t−ti )/τAP(8.57)

′

′

t∑
t∑
i =t
i =t
NemptyNt (t)Nin (t) = ∆I(t) ×+∆I(t) × i
× (1 − e−(t−ti )/τrec ) +NAP (ti ) × (1 − e−(t−ti )/τrec )Npixel
N
pixel
t =0
t =0
i

i

(8.58)′

Ndet (t) = ∆I(t) ×

′

t∑
t∑
i =t
i =t
NemptyNt (t)+∆I(t) × i
× (1 − e−(t−ti )/τrec )2 +NAP (ti ) × (1 − e−(t−ti )/τrec )2
Npixel
N
pixel
t =0
t =0
i

i

(8.59)
NemptyNempty (t) = Nempty (t) − ∆I(t) ×
NpixelNti (t)Nti (t) = Nti (t) − ∆I(t) ×× (1 − e−(t−ti )/τrec )Npixel2∆ICT (t) = Nin (t) × (PCT + PCT+ ···)(8.61)(8.62)′t∑i =tNemptyNt (t)+∆ICT (t) × i× (1 − e−(t−ti )/τrec )Npixel
N
pixel
t =0

Nin (t) = Nin (t) + ∆ICT (t) ×(8.60)(8.63)

i

′

t∑
i =t
NemptyNt (t)
Ndet (t) = Ndet (t) + ∆ICT (t) ×+∆ICT (t) × i× (1 − e−(t−ti )/τrec )2
Npixel
N
pixel
t =0

(8.64)i

Nempty (t) = Nempty (t) − ∆ICT (t) ×
Nti (t) = Nti (t) − ∆ICT (t) ×

NemptyNpixelNti (t)× (1 − e−(t−ti )/τrec )NpixelNt (t) = Nin (t)(8.65)(8.66)(8.67)

Then, the total number of incident photons by the scintillation emission I and detected photons by the SiPM
Ndet are described as:
I=

ti∑
=100

∆I(t)

(8.68)

ti =0

Ndet =

ti∑=100

Ndet (t)(8.69)

ti =0

The saturation curve can be obtained by scanning the initial value of the scintillation emission I0 . The new
saturation model including all the eﬀects of the time constant of the scintillation emission, recovery time, crosstalk and after-pulse is developed.

8.4 Comparison between measurement and model

133

8.4 Comparison between measurement and model
The comparison between the measurement and the model is performed to conﬁrm the validity of the new method
for the saturation measurement. The key parameters of the model are obtained by separate measurements for theaccurate comparison. This section gives the measurements of the parameters of the SiPM, and the results of thecomparison.

8.4.1 Measurements of the cross-talk, after-pulse, and recovery time
In order to complete the saturation model, the properties of the SiPM used in the measurement should bemeasured and applied to the model. The parameters of the SiPM used in the saturation measurement are measured
using dark noise events. The measurement uses the waveform digitizer, and Fig. 8.12 shows a typical waveform ofa dark noise as the ﬁrst pulse, and an after-pulse as the second pulse. The probability of the cross-talk is measured
by the height distribution of the ﬁrst pulse where the height is calculated in the range of the fast component of theﬁrst signal as represented by the red arrow. The after-pulse and recovery time is calculated using the height of theafter-pulse and the time diﬀerence between the ﬁrst pulse and the after-pulse, so the slow component of the ﬁrst
pulse as represented by the blue arrow is also analyzed.

Figure8.12 Waveform of a dark noise of the SiPM with an after-pulse.

Fig. 8.13 shows the distribution of the height of the ﬁrst pulse. The probability of the cross-talk PCT is calculated
by:
PCT =

N>1.5 p.e.
N>0.5 p.e.

(8.70)

where N>0.5 p.e. and N>1.5 p.e. is the number of events more than 0.5 p.e. and 1.5 p.e. respectively. The probabilityof the cross-talk of the SiPM used in the saturation measurement is PC T = 33.7 ± 1.7%.
Fig. 8.14 shows the distribution of the time diﬀerence between the ﬁrst pulse and after-pulse. The time diﬀerenceis calculated by the peak times for each pulse. The after-pulse probability PAP and time constant τAP are calculatedby:
NAP = PAP1
τAP

e−t/τAP ∗ Nevent ∗ tbin

(8.71)

where the total number of events Nevent and bin width tbin is multiplied by the function of the after-pulse. Thereis eﬀect of the dark noise, but it can be ignored because it is small enough compared to the after-pulse. The
distribution of the time diﬀerence is ﬁtted by this function. The probability of the after-pulse is PAP = 4.0 ± 0.4%,
and the time constant of the after-pulse is τAP = 10.3 ± 1.0 ns.

Event3×10

heightH
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1204415540.1117
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Chapter 8 New method for the saturation correction

134

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scatH
are clearly separated,0.08
and ﬁtted by the multi-gaussian.
0.08

Event

heightH
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−9

Figure8.14 Distribution of the diﬀerence of the peak time between the ﬁrst pulse and after-pulse. The
distribution
is ﬁtted by0.08
the function for the after-pulse.
scatH_pfx
scatH

Entries

13487

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4456

Mean xMean y1.603e−08

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0.07

0.05557

Std Dev x 9.534e−09
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0.01425

0.05556

Std Dev 9.532e−09
Std Dev y
0.01426

Fig. 8.15 shows the 2D scatter plot of the time diﬀerence and the height of the after-pulse. The recovery time is
0.06

calculated by:
0.05

h1 p.e. (1 − e−t/τrec(8.72))
0.04

where h1 p.e. is the height of0.03
the 1 p.e. spectrum. The scatter plot is ﬁtted by this function using the h1 p.e. obtained
by Fig. 8.13. The recovery time is τrec = 7.38 ± 0.05 ns.
0.02

8.4.2

0.01
Comparison withmeasured saturation curve
−9

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35

×10
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Time difference [ns]

0

−9

×10

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15
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25
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35
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A comparison between the saturation
curve
measuredin Section
8.2 Timeandthe45new[ns]model
is performed. The timedifference

constants of the scintillator is used as the catalogue value, the rise time is τrise = 0.9 ns, and the decay time is

800
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8.4 Comparison between measurement and model
scatH

0.07

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Std Dev x 9.534e−09
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0
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10

15

Figure8.15 Scatter plot of the peak time diﬀerence between the ﬁrst pulse and after-pulse vs. the height of the after-pulse.

τdecay = 2.1 ns. Fig. 8.16 shows the comparison with the measurement and model. A slight deviation can be seen,

so the time constants are adjusted since the time constants can change due to the characteristics of the scintillator.
The time constants are optimized by taking the minimum of the sum of the chi square at each measurement point.
Fig. 8.17 shows the saturation model with the optimized time constants with τrise = 1.3 ns and τdecay = 2.6 ns.
The saturation model match well with the measured saturation curve. Therefore, taking into account the possible
uncertainty of the time constant of the scintillation emission, the new saturation model describes very well the

N_det [p.e.]measured saturation curve.

2000
1800
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Model
Measured (UV)

800
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N_seed [p.e.]

Figure8.16 Saturation curves measured with the UV light (red) and the model (black) using the catalogue value
as the time constants of the scintillator. The gray belt shows the eﬀects of the errors of the SiPM parameters

The same comparison is performed with the saturation curve using the visible light. The new saturation model
can describe the saturation curve measured by the visible light by turning oﬀ the eﬀect of the scintillation lightemission. In order to check the validity of the new method for the saturation measurement and modeling in moredetail, the comparison of the saturation curve with visible light between the measurement and model is performed.

Chapter 8 New method for the saturation correction

N_det [p.e.]

136

2000
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Model
Measured (UV)

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N_seed [p.e.]

Figure8.17 Saturation curves measured with the UV light (red) and the model (black) using the optimized
time constants of the scintillator.

In case of visible light, the time constant of the scintillation emission is not considered, but the visible light fromthe PLS-500 has the pulse width with the FWHM of the 0.9 ns. Fig. 8.18 shows the comparison with measurement
and model using the visible light. The model matches with the measured saturation curve at low light intensities,
but doesn’t match at high intensities. The pulse width is adjusted to search for the reason of this unmatched result.
Fig. 8.19 shows the saturation model with the optimized pulse width of 2.0 ns. The saturation model match withthe measured saturation curve, so the pulse width of the visible light may cause the over-saturation and mismatch

N_det [p.e.]with the model.

2000
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Model
Measured (Visible)

800
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N_seed [p.e.]

Figure8.18 Saturation curves measured with the visible light (red) and the model (black) using the catalogue
value as the pulse width.

Fig. 8.20 shows the comparison of the saturation curves between the UV light, visible light, and the conventional
method. The saturation curve with the conventional method is obtained by the model without the pulse width ofthe visible light assuming the fast visible light. There is the signiﬁcant diﬀerence between the saturation curves

N_det [p.e.]

8.4 Comparison between measurement and model

137

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Measured (Visible)

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Figure8.19 Saturation curves measured with the visible light (red) and the model (black) using the optimized pulse width.

with the new method using the UV light and with the conventional method, and the larger saturation recovery canbe seen at the new method, compared to the comparison between the saturation curves using the UV light and theN_det [p.e.]visible light from the PLS-500.

2000
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Figure8.20 Saturation curves in the measurement and model with the UV light (black), the visible (red), andthe conventional method.

In summary, the new saturation model describes the measured saturation curve very well. It can correct accurately
the saturation curve at the detector using the SiPM and scintillator, and be possible to develop a new calibration
method, such as directly measuring the saturation curve by injecting the UV light to the actual system. The model
reproduces the actual saturation curve including the time constant of the scintillation emission, recovery time,cross-talk and after-pulse, and turn these eﬀects on and oﬀ. By changing the model parameters for the SiPM andscintillator, the model can be easily applied to various systems with scintillator and SiPM. It has a big impact on
the calibration and saturation correction for the SiPM and scintillator techniques involving the Sc-ECAL.

139

Chapter 9

Evaluation of jet energy resolution
The jet energy resolution is revisited using the full simulation model for the ILD, based on the performance of
the Sc-ECAL studied in this work. The reasonable jet energy resolution is obtained based on the results of thiswork. In addition, the eﬀects of the saturation model and the pixel pitch of the SiPM on the jet energy resolution
are evaluated. This chapter gives the results of the evaluation of the jet energy resolution using the full detector
simulation.

9.1 iLCSoft [60]The iLCSoft is a widely used software suitable for the simulation and analysis of the linear colliders. It is used toprepare for the future linear collider projects such as the ILC. The iLCSoft is used for the performance evaluationof the detector models and physics studies. Based on the actual layout of the detectors, detailed simulations of all
the components and their reactions can be performed using Geant4 and reconstruction algorithms. The full MC
simulation samples can be used to study the performance of the detectors and physics.
The main components of iLCSoft can be divided into the event data model LCIO, the toolkit DD4hep for
describing detector geometry, and the application framework Marlin, as shown in Fig. 9.1. This section gives an
overview of each component and the central algorithm PandoraPFA.

e framework for

ce, LCTPC (and friends:el (EDM)

try description

Figure9.1 The main components of the iLCSoft and their ﬂow [60]Chapter 9 Evaluation of jet energy resolution

140

9.1.1

Linear Collider I/O (LCIO)2

CHEP03 March 24-28, 2003 La Jolla, California

Fig. 9.2 shows the overview of the LCIO data model. The LCIO is a hierarchical data model, from Monte Carlo
information to tracker and calorimeter hits, and from reconstructed particle information to tracks, clusters, andcreate tracks and cluste
ter respectively - in tur
community and in detector test beam experiments.
hit objects. These refer
see that hits may be dr
So called ’particle flow
ReconstructedParticles
is generally done by tak
alone for charged partic
ics for neutral particles
tracks. By combining pof reconstructed particl
type might be added tojets, vertices). Objects
to theFigure9.2 Overview of the data model as deﬁned by LCIO [61]. Each square corresponds to a diﬀerent
data constituent partivertexes. The LCIO event data model is in a common data format that can be used throughout the linear collider

entry or class, and the arrows correspond to the relationships between them.

Figure 2: Overview of the data model defined by LCIO.
3. IMPLEMENTATIOThe boxes correspond to separate data entities (classes)
9.1.2 Detector Description
toolkitfor high
energy physics(DD4hep)
and the arrows
denoterelationships
betweenthese
entities. Not shown are extension objects for additional
As mentioned in the
In high-energy physics
experiments,
it isusers
essential
to describe
theadd.
geometry of the detector and the properties
information
that
might
want tohave a Java, C++ andof its materials in a detailed and realistic manner. This is evident in Monte Carlo simulations, where information

it is good practice nowa
ented design for LCIOable
the development
time toanda minimum.
response of the detector
andtothekeep
underlying
physics. For digitization
reconstruction processes,
it is (API)equally for Java andfaces
important to accurately describe the detector geometry, which should ideally be generated from thesourceis samefeasiblewith the two
to avoid inconsistencies.
we try to map as much
2. DATAThe DD4hep is developed
to meetMODEL
these requirements, and uses the same detector model with the same
ontogeometry
the actual implem
about the location, shape, and composition of each detector component is necessary to accurately understand thefor all simulation, digitization, reconstruction, and analysis. Fig. 9.3 shows the components of the DD4hep. The

Beforegoing
into thethe software
designdetector is described througha C++
constructor,
anddetails
detailed ofparameters
can be set
in xml. The package also

3.1.
Designincludes the lcgeo, a sub-package of the detector model for linear colliders, and the ddsim, a python
programtoand realization of LCIO we need to briefly describe
the data model. One of the main goals of LCIO is therun the full simulation.
Here we give an overunification of software that is used in the international
The DD4hep is a general geometry toolkit based on the ROOT and Geant4, which are widely used in highin
LCIO and how thislinear collider community. Thus the data model has toenergy experiments. The DD4hep is developed primarily for linear accelerator projects, but is designed to support
scribed in section 1.2. O
fulfill the current needs of the diﬀerent groups workexperiments from starttoﬁnish.
This
means
that
it
is
applicablefromthepreparation
stage
of
an
experiment
write
datato from a simu
ing in the field as well as being expandable for future
the running experiment.
back into a reconstructi
requirements. Figure 2 shows the data entities that
der to facilitate the inco
are defined by LCIO. The attributes currently stored
9.1.3 Modular Analysis
Reconstruction
for LINear
Colliderof(Marlin)
data into existing simul
for eachandentitybasically forma superset
the atto have a minimal intertributes used in two simulation software frameworks,
The Marlin is an application framework that uses C++ as the reference language and is used throughout theminimal interface has asnamely the Java based hep.lcd [2] framework, used bythecomponentsoftheDD4hep.
The
processofthedigitization,
reconstruction,iLCSoft. Fig. 9.4 shows
possible,andmaking it easysome U.S. groups and the European framework - conexisting classes. Figure
sisting of the Mokka [3] simulation and Brahms [4]of this minimal interfac
reconstruction program. These two frameworks areuses just this interface t
also the first implementors of LCIO. As other groups
program. The LCEven
join in using LCIO, their additional requirements can9.2 Simulation

141

for HEP) is the
scription for iLCSofted for:sualization and analysis

via a set of:.d.

Geant4ructionFigure9.3 Components of DD4hep and their ﬂow [60]analysis is implemented as a processor, and can be executed in an integrated manner.

http:etector models
The hit information obtained
from the DD4hep is given in the form of an energy deposit that each particle//aidasoft.web.cern.ch/DD4hep
Digitization

drops into its respective detector. The digitization is the process of digitizing the hit information into signals froma full simulation

the detectors, which are output in the same format as the experimental data, including the eﬀects of noise andsaturation.
Then, the simulation andILD
the experimental
areAprcompatible
and can be
and veriﬁed. In
iLCSoft
Tutorial
SW Meeting, data
Lyon,
24-28, 2017
6 /compared30
the digitization of the calorimeter, there are parameters such as the energy fraction in the detection layer among
the total energy deposit and the MIP response of the detector, which are calibrated using gamma-rays, KL0 , andmuons of speciﬁc energy.
Reconstruction
The reconstruction is to reconstruct the events from the hit information of the experimental data or the simulation
data after digitization. In the calorimeter, the energy dropped by the particle is reconstructed from the magnitudeof the signal, and these are reconstructed using the pandoraPFA.
PandoraPFA [24]The PandoraPFA is an event reconstruction algorithm based on the PFA. It makes clustering from tracks andcalorimeter hits to create a list of reconstructed particles called Particle Flow Objects (PFOs). The parameters of
PandoraPFA include "correlation between the detected energy and the number of MIPs", and "correlation between
MIPs and GeV". These parameters are also calibrated using gamma-rays, KL0 , and muons of speciﬁc energy.

9.2 Simulation
The jet energy resolution of the ILD is evaluated using the conﬁguration of the calorimeter option with the
Sc-ECAL and the AHCAL. The impacts of the saturation model and the SiPM types are also evaluated. Thissection gives the setup of the simulation, the results of the evaluation of the jet energy resolution.

Chapter 9 Evaluation of jet energy resolution

142

iLCSoftort collection or

d via XML

inGUI

lin/

LCSoft Tutorial

9.2.1

ILD SW Meeting, Lyon, Apr 24-28, 2017
Figure9.4 Components of Marlin [60]7 / 30Setup

The version of the ILD model at the DD4hep is ILD_l5_o3_v02, which is based on the Sc-ECAL and scintillatorbased analogue HCAL (AHCAL). The conﬁguration of the Sc-ECAL is basically the same as the technologicalprototype, but the only diﬀerence is the strip geometry of 5 mm × 45 mm × 1.5 mm. This is because the ILD
model includes both the scintillator and silicon sensors for the Sc-ECAl and Si-ECAL respectively to compare twomodels, so the sensor thickness is set to be a bit smaller due to the space limit. The energy is corrected to calibrate
the thickness from 1.5 mm to 2.0 mm.
Some parameters at the digitization and PandoraPFA are calibrated using the gamma-rays, KL0 , and muons.
Then, using the ddsim, quark pairs (u, d, s) of 91 GeV, 200 GeV, 360 GeV, and 500 GeV are generated from thecollision point and injected into the ILD model. The events are reconstructed to evaluate the energy resolutionof the jet. Since they are two-jet events, the energy of one jet is half the energy of quark pairs. The resolution isevaluated using the RMS90 method. This method evaluates the resolution by calculating the standard deviation
using only 90% of the total events around the core of the distribution to exclude the extra tail events.

9.2 Simulation

143

9.2.2 Jet energy resolution
The saturation curve is applied to the simulation in the digitization step, and the correction of the saturation
is applied in the reconstruction step. The new model of the saturation curve involving the eﬀects of the time
constant of the scintillation emission, recovery time, and cross-talk and after-pulse, discussed in 8.3, is applied tothe digitization and reconstruction step of the simulation. The S12571-010P is used as the SiPM, and the CTAP
probability is based on the measurements of the technological prototype. The light yield for MIP is set to 7 p.e.
based on the prototype results. The black plots in Fig. 9.5 shows the saturation curve based on the new model inthis setup.

Reconstructed energy [GeV]

JER (RMS90/E) [%]Figure9.5 Saturation curve with all eﬀects (black), and without the time constant of the scintillation emission (red)

5

4.5

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Figure9.6 Jet energy resolution (left) and linearity (right) with S12571-010P using the new saturation model.

Fig. 9.6 shows the jet energy resolution (JER) and linearity using the S12571-010P and the new saturation
model. The JER is less than 3.7% at the whole energy range, which meets the requirement of 3–4% for the PFA.
The reconstructed jet energy is linearly proportional to the injected energy. This result is reasonable and consistentChapter 9 Evaluation of jet energy resolution

144

with previous studies in [25][33]. The quite good resolution and linearity can be achieved using the Sc-ECAL as
the PFA ECAL, and the Sc-ECAL is capable of realizing the precise physics at the ILC.

9.2.3

Eﬀect of saturation correction

For comparison, the JER based on the saturation correction with the conventional method is evaluated. The
SiPM saturation occurs based on the new model including the time constant of the scintillation emission, but thesaturation correction is made with the conventional method where the saturation curve is measured without taking
into account the time constant of the scintillation light emission. The new model is applied to the digitization,and the model without the scintillation emission is applied to the reconstruction. The saturation curve with theReconstructed energy [GeV]

JER (RMS90/E) [%]conventional method is also shown as the red plots in Fig. 9.5.

All effects
5

False reconstruction

4.5

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Figure9.7 Jet energy resolution (left) and linearity (right) with S12571-010P using the new saturation model(black) and the conventional method (red). The red uses the saturation correction with the conventional method
at the reconstruction step.

Energy histo
1800
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default

1000

false reco

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Figure9.8 Distribution of the reconstructed energy at 10 GeV gamma with all eﬀects (black) and without thetime constant (red).

9.2 Simulation

145

The red plots in Fig. 9.7 show the results of the jet energy resolution and linearity based on the saturation
correction with the conventional method at the reconstruction. Both the JER and linearity have no signiﬁcantdiﬀerence from the new model, because the eﬀect of the false reconstruction is normalized at the calibration step.
Fig. 9.8 shows the energy distributions at 10 GeV gamma. The energy scale of the Sc-ECAL is calibrated by taking
a factor to adjust the mean of the energy distribution to 10 GeV. The calibration factors for the energy scale is1.0374 with all eﬀects, and 1.0158 without the time constant. The diﬀerence of the saturation curve can disappear
at the calibration step for the energy scale.
The SiPM characteristics for the CTAP probability is applied to the JER simulation. The CTAP probability has
about 10% variation from sensor to sensor according to the measurement at the prototype, and the 10% variationof the CTAP probability corresponds to the 2% variation of the Ndet at the new saturation model. The eﬀect of
the uncertainty is included in the simulation by smearing the Ndet using a Gause function with a variance of 2%.
The green plots in Fig. 9.9 show the JER and linearity with the variation of the SiPM characteristics for the
CTAP probability. Compared to the results with no variation, the JER is slightly worse at the high energy region,
but the linearity is the same. The deteriorated JER can be restored by per-channel CTAP calibration the same way
as described in Section 6.3. The saturation model can be calculated channel by channel using the measured CTAP

Reconstructed energy [GeV]

JER (RMS90/E) [%]probabilities, and the SiPM characteristics for the CTAP can be corrected.

All effects
5With CTAP error

4.5

4All effects
500

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0
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Jet energy [GeV]

Figure9.9 Jet energy resolution and linearity including the variation of the Ndet caused by the SiPM characteristics of the CTAP (green), and the new saturation model (black) for comparison.

9.2.4 Eﬀect of SiPM types
There are some candidates of SiPMs for the Sc-ECAL discussed in Section 4.5.6, but the detailed comparison
between the SiPM types has not been done. Using the new saturation model and results of the prototype, the JER
with the diﬀerent SiPM types is evaluated. According to the measurements of the prototype, the light yield for
MIP is set as 7 p.e. for the S12571-010P and 18 p.e. for S12571-015P respectively. The light yield for the S14160
series, which are not used in the prototype, is calculated according to the diﬀerence of PDE and sensitive area,
then set as 21 p.e. for the S14160-1310PS and 38 p.e. for S14160-1315PS respectively.
Fig. 9.10 shows the results of the JER and linearity with diﬀerent SiPMs. The results with all types of SiPMs
have similar resolution below 3.7% and meets the requirement of 3–4% for the PFA. The linearity is also good atChapter 9 Evaluation of jet energy resolution

146

all types. In terms of the jet energy resolution, all candidates of the SiPMs for the Sc-ECAL can achieve the quite
good resolution and realize the precision physics at the ILC. The decision of SiPM type will be determined by

Reconstructed energy [GeV]

JER (RMS90/E) [%]examining the eﬀect of the Bhabha scattering, where a large number of particles are incident.

S12571_010P (MIP = 7 [p.e.] & npx = 10000)

5

S12571_015P (MIP = 18 [p.e.] & npx = 4489)
S14160_1310PS (MIP = 21 [p.e.] & npx = 16675)
S14160_1315PS (MIP = 38 [p.e.] & npx = 7296)

4.5

4S12571_010P (MIP = 7 [p.e.] & npx = 10000)

500

S14160_1310PS (MIP = 21 [p.e.] & npx = 16675)
S14160_1315PS (MIP = 38 [p.e.] & npx = 7296)

400

300

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S12571_015P (MIP = 18 [p.e.] & npx = 4489)

0
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Jet energy [GeV]

Figure9.10 Comparison of the jet energy resolution (left) and linearity (right) between diﬀerent types of
SiPMs. In the legend, MIP means the MIP light yield in units of p.e., and npx is the number of pixels.

147

Chapter 10

Conclusion
Conclusion
Future Higgs factories based on the electron-positron collider are planned for the precision Higgs physics. The
precise measurements of the mass and coupling for the Higgs boson would be a key portal to the new physics
beyond the Standard Model. One of the most important advantages for the future Higgs factories such as the
ILC and CEPC is the model-independent measurement of the Higgs coupling constant. Especially the precise
measurement of the Higgs hadronic decay H → W W ∗ /ZZ ∗ /q q̄ is important, because it is diﬃcult in the LHC
because of the huge backgrounds. It requires a precise jet measurement with the jet energy resolution of of 3–4%
at the whole jet energy range. The PFA is a central concept of the detectors at the Higgs factories, which requires
high-granularity calorimeters. Especially the high granularity of the cell size of the 5 mm × 5 mm is required for
the PFA ECAL.
The Sc-ECAL is one of the technology options for the PFA ECAL. It is based on a scintillator strip readout
by a SiPM to realize the 5 mm × 5 mm cell size by aligning the strips orthogonally in x-y conﬁguration. The
number of readout channels can be greatly reduced compared to the genuine 5 mm × 5 mm segmentation without
the degradation of the calorimeter performance. In order to demonstrate the performance of the Sc-ECAL and toprepare for the construction of the actual detector, a full-layer technological prototype with all the technologies
integrated is constructed. This is the ﬁrst ever demonstration with a full technological prototype for the PFA-ECAL.
By calibrating the key parameters of the prototype and checking their stabilities, It is veriﬁed that the Sc-ECAL
can be operated stably. By demonstrating the good performance such as the position resolution, eﬃciency, shower
measurement, and jet energy resolution by simulation, it is conﬁrmed that the Sc-ECAL meets the requirements
as the PFA ECAL for the precision physics at the future Higgs factories. The commissioning of the technologicalprototype is based on long-term tests with LED and cosmic-ray. The calibration scheme and reconstruction
algorithm such as the SSA and cone clustering are developed, which can be applied to the actual detector.
The per-channel calibrations are successfully done for the key parameters of the Sc-ECAL. The gain, intercalibration factor, and probability of the cross-talk and after-pulse are obtained by the LED run. The pedestal and
MIP response are calibrated using the cosmic-ray run. The temperature dependence is evaluated and the methodof the temperature correction is established, then the temperature correction is applied to the measurement using
the prototype. This makes it possible for the ﬁrst time to evaluate the performance on the prototype. It is foundthat the Sc-ECAL can be properly calibrated and operated.
The performance of the Sc-ECAL is evaluated using the long-term commissioning runs. The key parameters are
successfully monitored and it is found that most of the parameters show excellent stability over a long period. The
temperature correction eliminates the eﬀect of the temperature dependence, and allows the accurate calibration ofChapter 10 Conclusion148

the MIP response so that the performance is not aﬀected. A slight degradation of the MIP gain is observed. It is
still under investigation, but it can basically be corrected by the calibration. The detection eﬃciency of ∼ 84% isachieved and found to be consistent with the Monte Carlo simulation. The position resolution of 1.5–1.7 mm isachieved and corresponds to the ∼ 5 mm uniform distribution, which meets the granularity requirement for the
PFA ECAL. The position resolution is also found to be consistent with the simulation. The shower analysis isperformed using the cosmic-ray instead of the test beam experiment. The shower properties with the data andsimulation match well especially in the fully contained shower and the shower escape with the energy suppression.
The showers induced by the cosmic-ray are successfully measured as expected in the simulation. Although moredetailed evaluation of the performance of the Sc-ECAL will require the planned test beam experiments, the basic
performance is successfully demonstrated in this work.
A new method for the measurement and correction of the saturation of the SiPM is developed. The saturation isa crucial issue for the detectors based on the scintillator with the SiPM readout. The new method is to measure
the SiPM saturation with the scintillation light excited by the UV light pulse, then the measured saturation curve
contains the eﬀects of the time constant of the scintillation emission. In the saturation measurement based on
the new method, a large recovery of the saturation is observed at the new method compared to the conventional
method. The new method gives a big impact on the saturation correction for the detectors using the scintillators
and SiPMs. In addition, a new saturation model for the ﬁrst time contains the eﬀects of the time constant of thescintillation emission, recovery time of the SiPM, cross-talk and after-pulse, is developed. The measurement andmodel are found to be consistent. The new method of the saturation measurement and the new saturation model
can be useful to the accurate saturation correction for the Sc-ECAL, and can also be applied to various detectors
and experiments based on the scintillator with the SiPM readout.
The jet energy resolution is evaluated using the current conﬁguration of the Sc-ECAL. Based on the performancemeasured by the prototype and the new saturation model, the jet energy resolution of less than 3.7% over a wide
energy range is found to be achievable, meeting the requirements for the PFA. A comparison of the jet energy
resolution for diﬀerent types of the SiPMs is performed, and it turns out that all types of SiPMs have similar
resolution of less than 3.7% over a wide energy range, meeting the requirement.
In conclusion, the Sc-ECAL is found to be a promising and mature technology for the highly granular calorimeterto achieve the precision physics at the future Higgs factories.
Prospect
The Sc-ECAL is planned to be tested in beam. The possibility is the electron beam at the Beijing Synchrotron
Radiation Facilities (BSRF) [47]. The BSRF provides the 1–2.5 GeV electron beam with about 50 Hz/cm2 . It
is possible to conduct operational tests in an environment similar to that of the actual detector, and the detailed
performance such as the energy scale, linearity, resolution can be demonstrated. We are now preparing a front-end
detector for the calibration of the beam energy and a support structure for the prototype towards the test beam
experiment. Moreover, there is a possibility of a test beam experiment combined with the Sc-ECAL and HCAL.
Detailed performance study such as the shower study and the cluster tagging can be evaluated. Through these test
beam experiments, we will be able to demonstrate the performance of the scintillator-based PFA calorimeter inmore detail.
The ILC is scheduled to begin the construction within the next 5 years and to begin the physical runs within thenext 15 years, to discover the precision Higgs physics. Remaining challenges toward the detector construction will
include the engineering design, which would require R&D for large scale production such as scintillator production(injection moulding) and automated assembly system.

149

Appendix
A SiPM double-side readout
The Sc-ECAL technological prototype includes the additional two layers with the SiPM double-side readout.
This appendix shows the principle of the double-side readout and the construction of the detection layers

A.1

Principle

The SiPM double-side readout method is a newly invented method for the Sc-ECAL, in which two SiPMs aremounted at both ends of the strip to readout the signals, as shown in Fig. A.1. To keep the total number of readout
channels, a strip with a length of 90 mm is used instead of a strip with 45 mm length. The possible advantages ofthe double-side readout method are as follows:• Eliminating a noise by taking coincidence of 2 SiPMs• Higher light yield by summing the signals from 2 SiPMs• Even lower light yield for each SiPM
• Position reconstruction by charge and/or timing diﬀerence between 2 SiPM readouts
The lower light yield for each SiPM compared to the single readout can suppress the saturation. The position
reconstruction can reduce the ghost hits.
45 mm
Scintillator strip

SiPM

90 mm

FigureA.1 Scematic of the SiPM double-side readout.

A.2

Performance test

Two types of strips are produced as shown in Fig. A.2. The position dependence of the light yield is measured
by using the β -ray from 90Sr and scanning the incident position, as shown in Fig A.3. The strip is coupled to theHamamatsu MPPC S12571-015P with the recommended operation voltage (68 V).
Fig. A.4 and A.5 shows the results of the light yield measurements with SiPM single readout and double-side
readout respectively. The sum of the light yields from two SiPMs is about 35 p.e., which is a larger light yieldAppendix

150

FigureA.2 Scintillator strip with SiPM single readout(top) and SiPM double-side readout (bottom).
FigureA.3 Setup for the measurement of the position
dependence of the light yield [62].
ਤ 3.12: ηοτΞοϓͷ໛ࣜਤthan that of the single readout over the entire strip. The light yield with one MPPC is smaller than that of thesingle readout, which results in the less SiPM saturation. By taking the geometric mean, the position dependence
becomes ﬂat.

26

FigureA.4 Position dependence of the light yield with single readout [62].

ਤ 3.21: 45(λΠϓͷޫྔͷҐஔґଘੑ. ϓϩοτͷ্෦ʹରԠ
Fig.mm
A.6 γϯνϨʔλετϦοϓ
shows the position resolution at each
incident1)
position.
The position resolution
is calculated by the͢ΔλΠϓͷγϯνϨʔλετϦοϓͷ໛ࣜਤΛ‫ͨ͠ه‬. position resolution is 32 mm using only thediﬀerence of the light yield and timing between 2 SiPMs. The averagetime diﬀerence, 27 mm using only the light yield diﬀerence, and 22 mm for the weighted average of the diﬀerencesof the time and light yield. The results show that the SiPM double-side38
readout
can reduce ghost hits discussed in 2 ͭͷʹ࿈Ͷͯฒ΂ͨΑ͏ͳ݁Ռͱͳ͍ͬͯΔɻશମͱͯ͠ฏ‫ۉ‬ޫిࢠఔ౓ͷޫྔ͕ಘΒΕɺ
Section 3.2.2.

MPPC Λ༻͍Δ͜ͱͰ
mm γϯάϧ
ϦʔυΞ΢τํࣜͷ৔߹ΑΓ΋ूޫޮ཰্͕͕ͬ
Fig. A.7 shows the45
distributionof the lightSiPM
yield withand without the coincidence of 2 SiPMs. The data istaken by the self-trigger of 2 SiPMs with the lowMPPC
threshold.͔ΒಘΒΕΔޫྔ͸࠷ߴͰThe noise (pedestal) events like the blue
histogram͍ͯΔ͜ͱ͕Θ͔ΔɻҰํͰɺยํͷΈͷ
25 ޫిࢠఔ౓Ͱɺ
can be extracted, and the MIP spectrum like the red histogram can clearly be seen. By lowering the threshold and

MPPC ͔Β཭Ε͍ͯ͘ʹͭΕͯ
10 ޫిࢠఔ౓·Ͱখ͘͞ͳ͍ͬͯΔɻͦͷͨΊ 1 ͭͷ MPPC ʹ
removing the noise events with the coincidence, it is possible to acquire the events with a lower energy.
ऩू͞ΕΔޫྔ͸λΠϓ 1 ͱൺֱͯ͠খ͘͞ɺMPPC ͷανϡϨʔγϣϯ͕‫͜ى‬Γʹ͘͘ͳͬͯ
͍Δͱ‫͑ݴ‬Δɻਤͷ৔߹ΑΓ΋େ͖ͳޫྔԠ౴͕ಘΒΕͨɻҰํͰɺ͜ͷλΠϓͷετϦοϓͰ͸தԝ෇ۙͰͷଌఆͷࡍʹ MPPC ͱ β ઢরࣹҐஔͷؒͷ‫ ͕཭ڑ‬40 mm ఔ౓·Ͱେ͖͘ͳΔͨΊɺ͜Ε·Ͱͷ݁Ռͱൺ΂Δͱதԝ෇ۙͰͷऩूޫྔͷ‫ݮ‬গ͕‫ݦ‬ஶͱͳ͍ͬͯΔɻ͜ͷޫྔͷམͪࠐΈ͸‫ز‬Կฏ‫ۉ‬ΛऔΔ͜ͱͰӈਤͷΑ͏ʹϑϥοτʹ͢Δ͜ͱ͕Ͱ͖ͨɻ·ͨɺλΠϓ 2 ͱಉ༷ʹ MPPC ͷανϡϨʔγϣϯ͸λΠϓ̍ͱൺ΂ͯ཈੍͞Ε͍ͯΔͱ‫͑ݴ‬Δɻ

A SiPM double-side readout

151

xt
xl
σt 2 + σl 2
xmean = 1
1
+
2
σt
σl 2

(3.2)

఺ʹ͓͚ΔՃॏฏ‫ۉ‬ͷώετάϥϜ͓ΑͼϑΟοςΟϯάʹΑΓಘΒΕͨώο

ਤ 3.28 ʹࣔ͢ɻਤ 3.28 ͷӈਤʹ͸ൺֱͷͨΊʹ্ड़ͷ͓࣌ؒࠩΑͼޫྔࠩϓϩοτ΋ࡌͤΔɻ
FigureA.5 Position dependence of the light yield with double-side readout [62]. The Magenta and green plotsin the left ﬁgure show the light yield with each SiPM, and blue plots show the light yield summed by 2 SiPMs.
ਤ 3.23: 90 mm γϯνϨʔλετϦοϓ (λΠϓ 3) ͷޫྔͷҐஔґଘੑ
The black plots in the right ﬁgure show the geometric mean of the light yields.

3.4.2

λΠϓ 3 ετϦοϓʹ͓͚ΔώοτҐஔ࠶ߏ੒
Timing࣌ؒࠩΛ༻͍ͨώοτҐஔ࠶ߏ੒
ChargeλΠϓ 3 ʹؔͯ͠͸ɺ2 ͭͷ MPPC ͕ಘΔޫྔͷࠩ΍৴߸ͷ࣌ؒࠩΛ༻͍ͯώοτҐஔͷ࠶ߏ੒ΛࢼΈͨɻ৴߸ͷ࣌ؒ͸ίϯελϯτϑϥΫγϣϯʢCFʣ๏ʹΑͬͯ‫ٻ‬ΊΔɻCF ๏͸৴߸ͷϐʔΫʹରͯ͠Ұఆͷిѹ·Ͱ೾‫্ཱ͕͕ؒ࣌ͨͬͪܗ‬Λͦͷ৴߸ͷ࣌ؒͱ͢Δํ๏Ͱ͋ΓɺҰఆͷᮢ஋ిѹʹ࣌ؒऔಘͷϑϥάΛஔ͘ϦʔσΟϯάΤοδ๏ͱҟͳΓɺऔಘ͞ΕΔ͕࣌ؒϐʔ
Timing and chargeΫͷେ͖͞ʹґଘ͠ͳ͍ͱ͍͏ಛ௕Λ࣋ͭɻࠓճͷଌఆͰ͸ίϯελϯτϑϥΫγϣϯΛϐʔΫ೾ߴͷ 8%ͱઃఆͯ͠ղੳΛߦͬͨɻώοτҐஔ͝ͱʹ 2 ͭͷ MPPC ͕ड͚औΔ৴߸ͷ࣌ؒࠩͷ෼෍ΛΨ΢εؔ਺ͰϑΟοτͨ͠ɻਤ 3.24 ͸ετϦοϓͷத৺ʹ͓͚Δ࣌ؒࠩͷ෼෍ͱɺετϦοϓશҬʹ౉Δ࣌ؒࠩͷϐʔΫ஋ͷϓϩοτͰ͋ΔʢετϦοϓ྆୺͔Βͷ 3 ఺Λআ֎͍ͯ͠Δʣɻ
ͳ͓ɺ࣌ؒࠩ͸∆t = tMPPC2−resolutiontMPPC1 ͱ͍ͯ͠Δɻ
FigureA.6
Positionwith the double-side readout at each position [62].

ͷՃॏฏ‫ۉ‬஋ͷώετάϥϜʢࠨʣ͓ΑͼώοτҐஔ͝ͱͷ෼ղೳʢӈʣ
A.3

Detection layer

33ώοτҐஔ࠶ߏ੒ͷฏ‫ۉ‬తͳҐஔ෼ղೳ͸ɺ࣌ؒࠩͷΈ: 32 formm
Two detection layers with the SiPM double-side readout are producedtheɺޫྔࠩͷ
Sc-ECAL technological prototype.

Fig. A.8 shows two
optionsof thestrip design; 2 SiPMs in the middle of the strips, and 2 SiPMs at strip ends.
͓ΑͼޫྔࠩͷՃॏฏ‫ۉ‬: 22mm
ͱͳΓɺ࣌ؒࠩͱޫྔࠩͷ྆ํΛ༻͍Δ͜
In order to implement the double-side readout with minimal modiﬁcations using the standard EBU, the option 1ಘΒΕΔ͜ͱ͕Θ͔ͬͨɻ·ͨɺ͜ͷ݁Ռ͔Βલड़ͷΰʔετώοτ໰୊ʹ
with the 2 SiPMs in the middle of the strips is adapted in the detection layers for the technological prototype. The

option 2 will be adapted if the conﬁguration of the SiPM position on the EBU can be20
modiﬁed.
ϦʔυΞ΢τํࣜΛ༻͍Δ͜ͱʹΑΓຊདྷͷώοτҐஔ͔Β͓Αͦ
mm One line contains

5 rows of 45 mm strips at the standard EBU conﬁguration, while one line at the double-side readout layers is set

ΔِͷώοτΛഉআͰ͖ΔՄೳੑ͕͋Δɻ‫ࡏݱ‬ͷϓϩτλΠϓͰ͸ɺಡΈग़
as 90 mm strip + 90 mm strip + 45 mm strip.

The design of the strips and reﬂector (ESR) ﬁlms are based on the standard conﬁguration of the prototype, asͷ࣌ؒ෼ղೳ͕ѱ͍ͨΊ࣮૷͸೉͍͕͠ɺΑΓੑೳͷྑ͍ΤϨΫτϩχΫε

shown in Fig. A.9. 200 pieces of 90 mm strips and 100 pieces of 45 mm strips are produced for two detection͋Ε͹͜ͷΑ͏ͳղੳ͕ϓϩτλΠϓͰ΋ՄೳͱͳΔɻ

τϦοϓʹ͓͚ΔϊΠζ࡟‫ݮ‬ͷ‫ڀݚ‬

20

Charge

Timing and charge

ਤ 3.29: MPPC1 ͓Αͼ 2 ͰಡΈग़͞Εͨ৴߸ͷ࣌ؒࠩͷ෼෍
Appendix152
ਤ 3.28: ώοτҐஔͷՃॏฏ‫ۉ‬஋ͷώετάϥϜʢࠨʣ͓ΑͼώοτҐஔ͝ͱͷ෼ղೳʢӈʣ࠷ऴతʹಘΒΕͨώοτҐஔ࠶ߏ੒ͷฏ‫ۉ‬తͳҐஔ෼ղೳ͸ɺ࣌ؒࠩͷΈ : 32 mmɺޫྔࠩͷΈ : 27 mmɺ͓࣌ؒࠩΑͼޫྔࠩͷՃॏฏ‫ ۉ‬: 22 mm ͱͳΓɺ࣌ؒࠩͱޫྔࠩͷ྆ํΛ༻͍Δ͜ͱͰΑΓྑ͍෼ղೳ͕ಘΒΕΔ͜ͱ͕Θ͔ͬͨɻ·ͨɺ͜ͷ݁Ռ͔Βલड़ͷΰʔετώοτ໰୊ʹ͓͍ͯɺμϒϧ SiPM ϦʔυΞ΢τํࣜΛ༻͍Δ͜ͱʹΑΓຊདྷͷώοτҐஔ͔Β͓Αͦ 20 mm·ͰͷҐஔʹൃੜ͢ΔِͷώοτΛഉআͰ͖ΔՄೳੑ͕͋Δɻ‫ࡏݱ‬ͷϓϩτλΠϓͰ͸ɺಡΈग़͠ΤϨΫτϩχΫεͷ࣌ؒ෼ղೳ͕ѱ͍ͨΊ࣮૷͸೉͍͕͠ɺΑΓੑೳͷྑ͍ΤϨΫτϩχΫε
45 mm

ͷ౥ࡌ͕ՄೳͳͷͰ͋Ε͹͜ͷΑ͏ͳղੳ͕ϓϩτλΠϓͰ΋ՄೳͱͳΔɻ
Without coincidence
Scintillator strip

SiPM

With coincidence
Noise

90 mm

λΠϓ 3 ετϦοϓʹ͓͚ΔϊΠζ࡟‫ݮ‬ͷ‫ڀݚ‬

3.4.3

λΠϓ 3DistributionͷετϦοϓʹ͓͚Δ৴߸ͷίΠϯγσϯεΛऔΔ͜ͱʹΑΓϊΠζࣄ৅ͷ࡟‫ݮ‬ΛࢼΈ
FigureA.7of the sum of light yields of 2 SiPMs with or without the coincidence of 2 SiPMs [62].
ͨɻଌఆʹΑͬͯಘͨશΠϕϯτΛɺ
2 ͭͷ MPPC ͔ΒಡΈग़͞ΕΔ৴߸ͷ͕࣌ؒࠩ͋Δ஋ҎԼ
ਤ 3.30:|∆t| < 2 ns ͷίΠϯγσϯε৚݅Λࢪͨ͠MPPC1 ͓Αͼ 2 ͷޫྔ࿨ͷ෼෍. ॎ࣠͸
45 mmͱͳΔ΋ͷͱͦ͏Ͱͳ͍΋ͷʹ෼཭͢ΔΑ͏ͳղੳΛߦͬͨɻਤ
3.29 ͸ CF ๏ʹΑͬͯಘͨ৴߸ͷStandard EBU
Log εέʔϧͰ͋Δ.
Con guration࣌ؒࠩͷώετάϥϜͰ͋Δɻ͜ͷώετάϥϜΑΓɺઢ‫ݯ‬༝དྷͷΠϕϯτͷ΄ͱΜͲ͸-2 – 2 ns

90 mm
ͷൣғ·Ͱʹऩ·͍ͬͯΔ͜ͱ͕Θ͔Δɻ͜ΕΛ‫ࠩؒ࣌ʹݩ‬ͷίΠϯγσϯε৚݅Λ|∆t| < 2 ns௿ޫྔྖҬͷ੨ͷώετάϥϜ͸ยଆͷ
MPPC ͷΈʹग़ྗ͕͋ͬͨϥϯμϜϊΠζΠϕϯτɺ͢
Option 1

90 Sr ͔Βͷ β ઢʹ͸௿ΤωϧΪʔͷ΋ͷ΋‫·ؚ‬ΕΔͨΊɺ΃σελϧ
ͱઃఆͨ͠ɻਤ 3.30 ͸औಘͨ͠ΠϕϯτΛ͜ͷίΠϯγσϯε৚݅Λຬͨ͢΋ͷͱͦ͏Ͱͳ͍΋ͳΘͪ΃σελϧͰ͋Δɻ

ͷʹ෼཭ͨ͠ώετάϥϜͰ͋Δɻ෇ۙ·ͰςʔϧΛҾ͘͜ͱ͕‫ظ‬଴͞ΕΔɻී௨ɺ͜ͷྖҬͷࣄ৅Λᮢ஋ΛԼ͛ͯଌఆ͠Α͏ͱ͠
Option 2ͯ΋΃σελϧΛरͬͯ͠·ͬͯ៉ྷʹ෼཭͢Δ͜ͱ͸Ͱ͖ͳ͍ɻ͔͠͠ɺμϒϧ SiPM Ϧʔυ
36

FigureA.8 Two options of the 90 mm strip design for the SiPM double-side readout.
Ξ΢τํࣜʹ͓͍ͯ͸ɺ࣌ؒࠩͷίΠϯγσϯεʹΑΓϊΠζΛআ‫͢ڈ‬Δ͜ͱͰɺϖσελϧ෇ۙ·ͰΤωϧΪʔͷ௿͍ࣄ৅Λऔಘ͢Δ͜ͱ͕Ͱ͖ΔΑ͏ʹͳΔɻ
layers.
All the strips are wrapped with the reﬂector ﬁlms
by handas shown in Fig. A.10. The wrapped stripsare19ϥϘͰͷଌఆʹΑΓɺγϯάϧ͓Αͼμϒϧ
SiPM
ϦʔυΞ΢τํࣜͷੑೳ͕࣮ূ͞Εͨɻࠓfisent
to China, and theassemblyon the EBU is performed in theScECAL
same wayͷΧϩϦʔϝʔλੑೳ͕ͲͷΑas the standard detection layers with‫ޙ‬͸͜ͷμϒϧ
SiPM
ϦʔυΞ΢τํࣜͷಋೖʹΑΓɺsingle readout. Then, one super-layer with two EBUs with the double-side readout is completed, and installed into͏ʹվળ͢Δ͔ΛγϛϡϨʔγϣϯʹΑΓ‫͢ڀݚ‬Δ༧ఆͰ͋Δɻ
the back end of the technological prototype.

37

FigureA.9 Scintillator strip (left) and reﬂector ﬁlm (right) for the double-side readout layer.

FigureA.10 Scintillator strip wrapped with the reﬂector ﬁlm by hand.

20

“次世代電子用電子コライダー用高精細シンチレータ電磁カロリメータ -大型技術プロトタイプ建設-”

Naoki Tsuji, The University of Tokyo

Double readout : Light yield test

A SiPM double-side readout

netic Calorimeter”Light yield comparison
A.4 Scintillator material

153

Naoki Tsuji, The University of Tokyo

Standard strip produced by Chinese group (L=45mm, commercial PVT)

The scintillator strips for the double-side readout are produced by the injection moulding. The injection moulding
Strip for double-readout layer by Japanese group (L45mm, injection moulding)ator material
in 4.4.1. A dedicated mould for the strip is not ready, so a large plate with 2 mm thickness is produced by theis suitable for a large scale production, but the light yield is smaller than that of the cast moulding, as discussed
SiPM : S12571-015P

injection moulding, and the strip shape and dimple for the SiPM are machined.
Lightshows
yieldtheforcomparison
injection moulding
20%between
lower asFig. A.11of the lightisyieldtheexpected
45 mm strips produced by the cast moulding

ed by injection
moulding(BC408) and Still
injection
goodmoulding.
enough The light yield with the injection moulding is lower by ∼20% compared to theoncast moulding. However, the scintillator strip produced by the injection moulding has still suﬃcient light yield for

EJ204 (PVT)

the prototype.

Standard 45mm strip for Sc-ECAL prototype

45mm strip produced by injection moulding

mmercial PVT scintillator

Injection moulding(Polystyrene)

ate by injection mouldingy)thickness (mm)is lower by ~20%
to PVT
FigureA.11comparedLight yield of the standard
45 mm strip for the prototype (left) and the 45 mm strip produced by

14 /19the injection moulding (right).

Dedicated mould for Sc-CAL

The dedicated moulds for the scintillator strips with single readout and double-side readout are produced after
the construction of the detection layers, as shown in FIg. A.12. The light yield test is in preparation.

uld
in diﬀerent shapes

FigureA.12 Dedicated mould for the scintillator strips with single readout and double-side readout (andscintillator tile for the AHCAL).

A.5

Analysis plan for double readout layers

13 /26

The additional analysis of the technological prototype is planned using the detection layers with double-side
readout (DR layers). One is the noise reduction with the coincidence of 2 SiPMs. It needs the dedicated run with

Appendix154

the low threshold at the DR layers and with the trigger of the DR layers. The noise reduction can be evaluated bytaking the oﬄine coincidence of 2 SiPMs, because the online coincidence between 2 SiPMs is not possible in thecurrent DAQ system.
The other is the evaluation of the position reconstruction. The hit position of the cosmic-ray can be reconstructedusing the diﬀerence of the light yield between 2 SiPMs. The position resolution can be evaluated by the deviation
between the reconstructed position and the cosmic-ray track obtained by the track ﬁt.
The dedicated run and the performance evaluation of the DR layers are in preparation.

155

Acknowledgements
First of all, I would like to thank Prof. Wataru Ootani who supervised me and gave me an opportunity to join
the project of the future Higgs factories, and whose rigorous research attitude and broad knowledge greatly helped
me in the studies and became a lifelong asset.
I would like to thank all members of the ILD Sc-ECAL group and the CEPC Sc-ECAL group: Prof. Tohru
Takeshita, Dr. Yazhou Niu, Prof. Jianbei Liu, Prof. Yunlong Zhang, Prof. Mingyi Dong, Dr. Zhigang Wang, Dr.
Yong Liu. I am heartily thankful for the supports and advises of Prof. Toshinori Mori, Dr. Toshiyuki Iwamoto, Dr.
Yusuke Uchiyama, and Dr. Kei Ieki. I would like to express my special thanks to my colleagues especially in the
ILD group: Linghui Liu, Tatsuro Torimaru, Ryunosuke Masuda, Tatsuki Murata, and Yuki Ueda. This research
was supported by JSR Fellowship, the University of Tokyo.
Last but not least, I would like to express my deepest gratitude and appreciation to my family and everyone who
has supported and guided me.

157

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