"Design and Use of Anatomical Atlases for - publications LAL

202 Pages·2014·7.57 MB·English

LAL 13-345
Octobre 2013
UNIVERSITÉ PARIS-DIDEROT VII
SORBONNE PARIS CITÉ
École Doctorale : Particules, Nouyaux et Cosmos - ED 517
Laboratoire de l’Accélérateur Linéaire - UMR 8607
Discipline : Physique des particules
THÈSE DE DOCTORAT
soutenue le 25 Octobre 2013
par
TRAN
Huong Lan
Recherche de quarks lourds
avec le détecteur ATLAS
Composition du jury :
Mark Cooke (LBL) - Examinateur
Andreas Hoecker (CERN) - Examinateur
George Wei-Shu Hou (NTU) - Rapporteur
Francois Le Diberder (LAL) - Directeur de thèse
Achille Stocchi (LAL) - Président
Jean-Baptiste de Vivie de Régie (LAL) - Directeur de thèse
Isabelle Wingerter-Seez (LAPP) - Rapporteur

Acknowledgements
As I am sitting here writing these lines today, I feel happy - because I finally understood
how much this PhD means to me. It has given me the chance to learn new things and also
the opportunity to meet so many wonderful people.
I would first like to thank my two advisers, Francois Le Diberder and Jean-Baptiste de
Vivie de Régie, for their advices and support throughout these years. Francois, I am grateful
for having met you seven years ago, when I was still a young mémé. You are my supervisor
and you are my great friend. From you I have learnt so many things, not just about Particle
Physics but also about life. And thank you, Jean-Baptiste, without you this thesis would
have been impossible. You have been patiently teaching me everything from scratch and I
am very thankful for that.
I also thank Emi Kou, my co-supervisor of the Master Program’s Internship, for your
great help and suggestions. Thanks for your caring conversations and your warm host!
I would like to acknowledge all the members of the jury. First of all, I thank Achille
Stocchi for his support and for accepting being the president of the jury. I gratefully thank
Isabelle Wingerter for all the help and the precious advices, especially during my work for
LAr calorimeter. Thanks, Mark Cooke, for being such an attentive convener of the 4GT
group! Thanks for giving me the chance to enjoy the collaboration with the whole group.
Thank you, Andreas Hoecker for all the advices and for your great sense of humour! I am
still trying to find the best way to use the other half of my "Carte Blanche" ;). And George
W. Hou, thanks for accepting to be here today despite an incredibly long flight. Also, thank
you for all the thoughtful conversations at CERN and in Quy Nhon, Vietnam.
My respectful thanks go to all the LAr calorimeter experts for all their help during the
last year! Thanks Nicolas Berger and Walter Lampl, without you I would not be able to
accomplish the Quality factor study, which plays an important part in my thesis. Thank
you Stéphane Simion for all your help and suggestions during my shifts in the LAr team.
And thanks, Benjamin Trocmé, Stephanie Majewski, for your attentive supervision!
I also want to send my special thanks to Mrs. and Mr. Jean Tran Thanh Van for your
support for all the young Vietnamese students including me. No words can express my
emotions and my respect for you when i read about all that you have done for our beloved
country. And I am so grateful for having the chance to help you in a few conferences, where
I enjoyed very much the family atmosphere with the whole secretary group. Thank you,
Jacques Dumarchez, Hady Schenten, Isabelle Cossin, Gérard Dreneau and Christian Bareille
for the beautiful memories in Blois and in Quy Nhon, Vietnam.
It would be a big deficiency not to say thanks to Francois, Sandrine Laplace, Vu Anh
Tuan, Daniel Froidevaux and Patrick Aurenche for your tireless efforts to develop the collab-
oration France-Vietnam, which has given us - the young Vietnamese students - the chance
to continue our study in France.
I thank the Master Program NPAC for accepting me as a student. I thank Achille
Stocchi, Philippe Schwemling, Catherine Bourge and Sylvie Loeffel for helping me through
the administration procedure from the very beginning until now. My sincere thanks also
ii
go to José Ocariz for your kindness. You have been helping me a lot since I was still a
university student in Vietnam.
And of course, I want to acknowledge CNRS/IN2P3 for giving me the fellowship for my
PhD.
I also thank the Group ATLAS at LAL for having me as a member. My sincere thanks
go to the Chefs du groupe, RD Schaffer and David Rousseau for their help during the three
years of my PhD! Je voudrais également remercier Geneviève. Je suis sure que tous les
jeunes de notre groupe vont dire la même chose: "Merci beaucoup pour ta gentillesse!".
Thank you Sophie and Dudu, my physics-sister and brother, for your understanding and for
helping me so so much over the last three years! And thanks Nikola, it has been a pleasure
(and it has been fun) to share the office with you!
Je voudrais également remercier le service mission, service informatique et administratif
du LAL de m’avoir beaucoup aidé pendant ma thèse.
Andmyfriends, howmanypageswouldIneedtosaythankstoallofyou-formakingmy
everyday-life so colorful? I am happy to be a part of this cool generation of PhD students at
LAL ;). Thank you, Narei (et ton copain), Marija, Jana, Marta, Sandra, Samah, Sebastien,
Ali, Driss... for all your support through my difficulties in work and in life. And my non-
LAL friends, I am grateful for having met you all, Natasha, Anna, Marie, Adam, Dmitry,
Leonid, Niraj... as well as Vân, Nguyên, Tú, Gaetano...
My special thanks go to you, Peter, and your whole family for your love during these
years. You have brought me a second family and so many wonderful memories. I am sure
that no matter where life will lead us to, I will always have you there with your best support.
And of course, my warmest thank-you is dedicated to my family with all my heart. I
want to thank you, Dad, for you have always been there in every step of my life since I
was just a little girl lying in your arms on the top terrace of our house to gaze the stars...
You are the greatest Dad, you taught me everything: maths, physics, literature, languages,
singing... and I am so proud to be your daughter. I want to thank you, Mom, for your
unconditional love and for being always caring, I have never felt alone though I am so far
away from home, your long phone calls held me up in my most difficult moments. And
thank you, my Brother, I am sure without you it would have taken me much more time to
adapt to the life here - where it is thousands miles from home. You have been protecting
me and taking care of me in so many ways.
For you all have made my life so beautiful and meaningful...
Contents
1 Introduction 1
2 Theoretical Aspects 5
2.1 The Standard Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.1 The Standard Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.2 The Higgs boson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.3 What is missing and possible extensions . . . . . . . . . . . . . . . . 9
2.2 Theoretical Motivations for Heavy Quarks Searches . . . . . . . . . . . . . . 9
2.2.1 A chiral fourth generation of quarks and its current picture . . . . . . 9
2.2.2 Vector-like quarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3 Phenomenology of Heavy Quarks at LHC . . . . . . . . . . . . . . . . . . . . 16
2.3.1 Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.3.2 Decay modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3 Experimental Aspects 23
3.1 The Large Hadron Collider (LHC) . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 ATLAS: a detector designed for various searches . . . . . . . . . . . . . . . . 25
3.2.1 Inner Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.2.2 Calorimeters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2.3 Muon spectrometer . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.2.4 A "voyage" through the detector space: detection principle . . . . . . 33
3.2.5 Data collection system . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.3 Detector performance in first three years of functioning . . . . . . . . . . . . 35
3.4 The signal in LAr calorimeters . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.5 Validation of the Q-factor computation . . . . . . . . . . . . . . . . . . . . . 39
3.5.1 Definition of the Q-factor . . . . . . . . . . . . . . . . . . . . . . . . 40
3.5.2 Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.5.3 Technicalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.5.4 Choice of pulse shape prediction . . . . . . . . . . . . . . . . . . . . . 42
3.5.5 Validate the official tag . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.5.6 Final results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.5.7 Energy fraction of high Q-factor cells . . . . . . . . . . . . . . . . . . 47
3.5.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4 Object Definition and Event Pre-selection 49
4.1 Data and Monte Carlo samples used in the thesis . . . . . . . . . . . . . . . 50
4.1.1 Data samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.1.2 Monte Carlo Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.1.3 Systematics Uncertainty Samples . . . . . . . . . . . . . . . . . . . . 53
4.2 Event pre-selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
iv Contents
4.2.1 Object, variable definition and preselection . . . . . . . . . . . . . . . 54
4.2.2 Event pre-selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.3 Mass reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.3.1 Definitions & Notations . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.3.2 The Kinematical fit . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.3.3 Result of the kinematic fit . . . . . . . . . . . . . . . . . . . . . . . . 67
4.3.4 Kinematic fit performances . . . . . . . . . . . . . . . . . . . . . . . . 70
5 Fourth Generation Search Strategy 75
5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.2 Control and signal regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.2.1 Control region 1 (CR1) . . . . . . . . . . . . . . . . . . . . . . . . . . 77
5.2.2 Control region 2 (CR2) . . . . . . . . . . . . . . . . . . . . . . . . . . 77
5.2.3 Control region 3 (CR3) . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.2.4 Signal region (SR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.3 Kinematic features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.3.1 t(cid:48) pair production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.3.2 Decay of t(cid:48) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
5.3.3 Decay of W boson . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.3.4 The "top-tag" variable . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.4 Choice of discriminating variables . . . . . . . . . . . . . . . . . . . . . . . . 90
5.5 Likelihood fit and Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
s
5.5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.5.2 Likelihood fit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.5.3 Optimization of the cuts defining the categories . . . . . . . . . . . . 102
5.5.4 Statistical uncertainties on the fractions Fc . . . . . . . . . . . . . . . 106
i
5.5.5 Systematical uncertainties on the fractions Fc . . . . . . . . . . . . . 106
i
5.5.6 The Plot method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
s
5.5.7 Checking the correlation between the discriminating variables and the
control variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
5.5.8 Analysis Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
5.6 Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
5.6.1 Definition of test statistics . . . . . . . . . . . . . . . . . . . . . . . . 125
5.6.2 Test statistics combination using TMVA . . . . . . . . . . . . . . . . 129
5.7 Illustration with pseudo-experiments . . . . . . . . . . . . . . . . . . . . . . 130
6 Data Analysis 135
6.1 Final results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
6.1.1 Control Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
6.1.2 Likelihood fit in the Signal Region . . . . . . . . . . . . . . . . . . . 138
6.1.3 Plot analysis in the Signal Region . . . . . . . . . . . . . . . . . . . 140
s
6.1.4 Combined analysis in the Signal Region . . . . . . . . . . . . . . . . . 141
Contents v
6.1.5 Optimized analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
6.2 Cross checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
6.3 ATLAS analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
7 Vector-like Quarks Searches 151
7.1 Vector-like Quarks Searches . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
7.1.1 Ht+X analysis: Search for heavy top-like quarks decaying to a Higgs
boson and a top quark . . . . . . . . . . . . . . . . . . . . . . . . . . 152
7.1.2 Same-Sign analysis: Search for anomalous production of events with
same-sign dileptons and b-jets . . . . . . . . . . . . . . . . . . . . . . 154
7.1.3 Zb/t + X analysis: Search for pair production of new heavy quarks
that decay to a Z0 boson and a third generation quark . . . . . . . . 158
7.1.4 Wb+X analysis: Search for pair production of heavy top-like quarks
decaying to a W boson and a b quark . . . . . . . . . . . . . . . . . . 159
7.1.5 Limits summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Conclusion and Perspective 167
A List of Criteria for Electron Identification 169
B Event yields in different regions 171
C The computation of the statistical covariance matrix 179
C.1 Sanity Check . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
C.2 Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
C.3 Reduced χ2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
C.3.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
C.3.2 Simple case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
Bibliography 187
Abstract 193

Chapter 1
Introduction
The most beautiful experience we can
have is the mysterious. It is the
fundamental emotion which stands at
the cradle of true art and true science.
Albert Einstein
On March 30th 2010, the world’s largest and highest energy particle accelerator - the
Large Hadron Collider at CERN - began its planned research program with the first colli-
sions between two 3.5 TeV proton beams after more than ten years of construction. The
machine’s successful operation marked an important milestone on the engineering revolution
of mankind. Until its last data collection which took place on the 15th of February 2013
before the first Long Shutdown to maintain the hardware ensemble, LHC has provided an
enormous integrated luminosity for physicists to fulfill their researches. No doubt, one of
the greatest moments of modern particle physics has to be the announcement of the Higgs
Boson discovery on the 4th of July 2012 by the two biggest experiments at LHC - ATLAS
and CMS. Physicists have made a big progress in completing the Standard Model which
also means an important step further in our understanding of the Universe.
Coming to the ATLAS experiment and starting my PhD on November 2010, I had the
great chance to use the first data recorded by the ATLAS detector to perform my study.
This thesis describes all the work that I have done over the last three years, containing the
work contributed to the detector performance, the work contributed to the main analysis
group’s effort in searching for the heavy vector-like quarks model and the most important
part: a complete analysis dedicated to the search for a heavy top-like quark using the full
dataset at 7 TeV collected in 2011.
In the first chapter, an overview of the theoretical framework is presented. The Standard
Model (SM) with its well established three families will be briefly introduced. Despite the
fact that the SM successfully explains what we observe, with all that have been developed
in the model we are still not able to answer many questions, for example, the matter-
antimatter asymmetry or the amount of cold dark matter in the Universe, the neutrino
oscillation ... These problems give motivations for the searches of new physics in general
and heavy quarks in particular. The searches for heavy quarks will be then described in
two main parts. The first part is dedicated to portray the sequential fourth generation of
standard model like quarks (SM4), the simplest scenario among all the possible extensions.
It has the capacity to provide many appealing explications to the unresolved problems in
our understanding of the Universe while remaining just a simple extension of the Standard
Model. All the advantages of a SM4 will be discussed together with the historical reasons
Chapter 1. Introduction
why it was put in a bad shape after the discovery of the Higgs boson. The second part gives
a brief introduction on the heavy vector-like quark models 1. This search eventually takes
advantage from our understanding on the search for a SM4 thanks to the similarity on the
production mode and kinematics. Escaping from the constraint from the Higgs production
cross section, vector-like quarks models preserve its attraction in many ways which will be
explained at the end of the chapter.
As a connecting step towards the experimental search for these new models, all the
necessary experimental aspects will be presented in the second chapter: an overview on
the detector with the sophisticated design of its different parts; a detailed description on
the objects definition and identification; and finally a global view on the data and MC
samples used in this thesis. In this chapter, I also present my contribution on the Q-factor 2
computationfortheLiquidArgon(LAr)ElectromagneticCalorimeterofATLAS.Thisstudy
leads to the understanding of the ionisation pulse shape from the liquid argon calorimeter.
The proper description of the ionisation pulse shape is important to reject instrumental
noise. I have studied a method to quantify the quality of the pulse shape description. The
study has ended up with encouraging result.
The third chapter gives the description of the samples used in the thesis: the data and
Monte Carlo as well as the systematic uncertainties samples. The description contains the
explanationofhowthesampleswereproducedandhowtonormalisethebackgroundsamples
to the data luminosity. In this chapter, the event preselection and the kinematical fit to
reconstruct the signal mass is also described. The mass reconstruction method is developed
such that it is independent of any mass hypothesis: the algorithm imposes the leptonic and
hadronic mass 3 of the signal to be close to each other. The kinematic fit performances
study presented at the end of the chapter has proven the quality of the method.
In the next chapter comes the heart of the thesis: a complete analysis developed to
search for a heavy top-like quark. Aimed to improve the signal reconstruction in case it
exists, the analysis follows an originally different road compared to the standard analysis
in ATLAS. In a first part, all the basics of the signal’s production and kinematic features
will be studied in order to find the best discriminating variables to distinguish the signal
from the backgrounds. Once the choice has been made, the data unfolding method Plot
s
is used to extract the signal from the background. The outputs from the method will be
then used to define a set of test statistics, which will be afterward combined using the
FisherDiscriminant method (from the Toolkit for Multivariate Data Analysis (TMVA)).
Finally the combined distribution given by the FisherDiscriminant will be used at the end
as the final variable to test the hypotheses in which the signal exists or not. The result
of the method is indeed compatible to what has been obtained in the main analysis of the
group.
1Vector-like fermions are defined as those of which the left- and right-handed chiralities belong to the
same representation of the symmetry group G of the underlying theory, for example, the group SU(3) ×
C
SU(2) ×U(1) in the SM case.
L Y
2The quality factor that measures the agreement between the measured pulse shape and the reference
shape of the signal in the Electromagnetic Calorimeter
3Leptonic (hadronic) mass is the mass of the t(cid:48) that decays to a b quark and a W± boson which then
decays leptonically (hadronically).