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212 Pages·2017·6.53 MB·English

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ISBN: 978-90-393-6928-9
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Measurement of the prompt photon
production cross section in proton proton
√
collisions at s = 7 TeV with ALICE
Meting van de productiedoorsnede van
prompte fotonen in botsingen van protonen
√
met s = 7 TeV met ALICE
(met een samenvatting in het Nederlands)
Proefschrift
ter verkrijging van de graad van doctor aan de Universiteit Utrecht op
gezag van de rector magnificus, prof. dr. G.J. van der Zwaan, ingevolge het
besluit van het college voor promoties in het openbaar te verdedigen op
maandag 29 januari 2018 des middags te 4.15 uur
door
Davide Francesco Lodato
geboren op 22 juli 1984 te Enna, Italië
Promotor: Prof.dr. T.Peitzmann
Copromotor: Dr.ir. M. v. Leeuwen
lines
to
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down
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desired
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Vi Veri Veniversum Vivus Vici
The Vision and the Voice, shift fo
Aleister Crowley shift for name in

Contents
1 Heavy Ion Physics 1
1.1 Quantum Chromo Dynamics . . . . . . . . . . . . . . . . . . . 2
1.1.1 QCD Phase Diagram . . . . . . . . . . . . . . . . . . . 2
1.2 QGP phenomenology and experimental observables . . . . . . 4
1.2.1 Nuclear modification factor . . . . . . . . . . . . . . . 5
1.2.2 Direct photons . . . . . . . . . . . . . . . . . . . . . . 6
1.2.3 Azimuthal anisotropy of particle yields . . . . . . . . . 7
1.3 Probing initial conditions with p-Pb collisions . . . . . . . . . 9
2 Photons as a probe of nuclear matter 13
2.1 Photon production in hadron-hadron collisions . . . . . . . . . 14
2.1.1 QCD in the low-x regime, limits of applicability . . . . 17
2.2 The Colour Glass Condensate
effective theory . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2.1 CGC and observables . . . . . . . . . . . . . . . . . . . 21
2.3 Measuring direct photons:
isolation techniques . . . . . . . . . . . . . . . . . . . . . . . . 26
3 The A Large Ion Collider Experiment 29
3.1 General overview . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.2 The Inner Tracking System . . . . . . . . . . . . . . . . . . . 31
3.3 The Time Projection Chamber . . . . . . . . . . . . . . . . . . 32
3.4 The V0 detector . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5 The Electro-Magnetic Calorimeter . . . . . . . . . . . . . . . . 35
3.5.1 Selecting rare events with EMCal: triggering . . . . . . 37
3.5.2 Clustering algorithm . . . . . . . . . . . . . . . . . . . 38
i
CONTENTS
4 Data analysis 41
4.1 Data sample, event selection . . . . . . . . . . . . . . . . . . . 41
4.1.1 Event selection . . . . . . . . . . . . . . . . . . . . . . 42
4.1.2 EMCal data quality assurance studies . . . . . . . . . . 43
4.2 Charged Particle Veto . . . . . . . . . . . . . . . . . . . . . . 45
4.2.1 Multi-contribution clusters . . . . . . . . . . . . . . . . 48
4.3 Photon cluster identification . . . . . . . . . . . . . . . . . . . 50
4.3.1 Transverse shower shape σ2 . . . . . . . . . . . . . . 51
long
4.3.2 Isolated photon clusters . . . . . . . . . . . . . . . . . 54
4.4 Contamination estimation for isolated photon clusters . . . . . 55
4.4.1 The ABCD method . . . . . . . . . . . . . . . . . . . . 56
5 Monte Carlo studies and corrections 59
5.1 Simulation samples . . . . . . . . . . . . . . . . . . . . . . . . 59
5.2 Validation of the Monte Carlo samples. . . . . . . . . . . . . . 61
5.3 Validation of the analysis procedure . . . . . . . . . . . . . . . 61
5.4 Reconstruction efficiency for isolated prompt photons . . . . . 64
5.5 ABCD method closure test . . . . . . . . . . . . . . . . . . . . 66
5.5.1 ABCD method on MC background sample . . . . . . . 69
5.6 A more realistic scenario:
the effect of signal . . . . . . . . . . . . . . . . . . . . . . . . . 72
5.6.1 ABCD Method on MC-Mixed Sample:
the α factor . . . . . . . . . . . . . . . . . . . . . . . . 72
5.7 Non factorisation in MC and comparison to data . . . . . . . . 75
5.7.1 σ2 distributions . . . . . . . . . . . . . . . . . . . . . 76
long
5.7.2 Isolation activity distributions . . . . . . . . . . . . . . 77
5.8 Non-factorisation of σ2 and Eiso. . . . . . . . . . . . . . . . 82
long T
5.9 "Correcting" the MC . . . . . . . . . . . . . . . . . . . . . . . 85
5.9.1 Smearing of σ2 distributions . . . . . . . . . . . . . . 85
long
5.9.2 Same rejection in MC as in data . . . . . . . . . . . . . 88
6 Corrected yield and systematic uncertainties 95
6.1 Corrected yield as a function of the transverse energy . . . . . 96
ii
Contents
6.2 Systematic uncertainties in data:
triggering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
6.2.1 Out-of-time (bunch) triggered events . . . . . . . . . . 99
6.2.2 Efficiency and stability of the triggering algorithm . . . 101
6.2.3 In-bunch pile up events . . . . . . . . . . . . . . . . . . 103
6.3 Systematic uncertainties from MC:
the choice of the Mixing Ratio . . . . . . . . . . . . . . . . . . 104
6.4 Systematic uncertainties from data and MC . . . . . . . . . . 105
6.4.1 Residual hadronic contamination . . . . . . . . . . . . 105
6.4.2 Cluster definition via shower shape selection . . . . . . 109
6.5 Uncertainty from different isolation
probability in data and MC . . . . . . . . . . . . . . . . . . . 117
6.5.1 Isolation probability and smearing . . . . . . . . . . . . 118
6.5.2 Anti isolation criterion . . . . . . . . . . . . . . . . . . 125
6.5.3 In-cone activity with charged particles . . . . . . . . . 126
6.5.4 Determination of the central value
for the corrected yield . . . . . . . . . . . . . . . . . . 134
6.6 Total systematic uncertainty for the measurement . . . . . . . 137
7 Results, outlook and conclusions 141
7.1 Integrated luminosity . . . . . . . . . . . . . . . . . . . . . . . 142
7.2 Isolated photon cross section and
comparison with NLO pQCD calculation. . . . . . . . . . . . . 144
7.3 Isolated photons at forward rapidity . . . . . . . . . . . . . . . 145
7.3.1 2 → 2 process kinematics . . . . . . . . . . . . . . . . . 148
7.3.2 Forward π0 and prompt photon production at LHC. . . 150
7.3.3 Inclusive prompt photons vs. Drell-Yan process . . . . 151
7.3.4 Forward-mid γ-hadron azimuthal correlations . . . . . 153
7.4 A Forward Calorimeter: FoCal . . . . . . . . . . . . . . . . . 157
8 Conclusions and outlook 161
A Isolation activity and underlying event estimators. 165
iii
CONTENTS
B Studies on isolation probability in data and simulated sam-
ple. 173
Bibliography 189
Samenvatting 195
Acknowledgements 199
Curriculum Vitae 201
iv