Universitat Karlsruhe (TH)thesis/data/iekp-ka2008...se angeben. Der LHC erweitert den...

ppppppppppppp Universitat Karlsruhe (TH)

Entwicklung einesMeta Monitoring Systems fur Grid-Zentren

undAuswirkungen der Simulation hadronischer

Jets auf die Rekonstruktionseffizienzim Vektorbosonfusions-Kanal H → ττ

Viktor Mauch

Diplomarbeit

an der Fakultat fur Physikder Universitat Karlsruhe

Referent: Prof. Dr. G. Quast

Institut fur Experimentelle Kernphysik

Korreferent: Priv. Doz. Dr. W. Wagner


17. November 2008

Deutsche Zusammenfassung

Die Neugierde ist eine herausragende Eigenschaft der Menschheit, die in ihr denEhrgeiz hervorruft, die Umwelt und ihre Gesetzmaßigkeiten systematisch zu er-forschen. Die moderne Physik beschaftigt sich hierbei mit den unterschiedlichstenThemen, von der Erforschung der Strukturen des Universums in astronomischenMaßstaben bis hin zu den kleinsten Bestandteilen der Materie und ihren Wechsel-wirkungen.

Aufgrund des enormen technologischen Fortschritts seit dem 19. Jahrhundertkonnte mit dem Bau und der Durchfuhrung komplizierter Experimente unser Wis-sen in der Teilchenphysik deutlich vertieft werden. Neben der Gravitationskraft, diefur die Strukturbildung im Kosmos verantwortlich ist, gibt es drei weitere funda-mentale Wechselwirkungen. Die elektromagnetische Kraft wirkt zwischen geladenenTeilchen, die starke und schwache Wechselwirkung spielen im sub-atomaren Bereichdie dominierenden Rollen. Die drei letztgenannten Krafte und die dazugehorigenAustauschteilchen werden durch das Standardmodell der Teilchenphysik beschrie-ben. Man strebt weiterhin danach, eine gemeinsame Theorie fur die Gravitationund das Standardmodell zu formulieren.

Im Jahre 2009 wird ein neuer Teilchenbeschleuniger, der Large Hadron Collider(LHC) am CERN nahe Genf, in Betrieb gehen. Zu den Hauptzielen der Wissen-schaftler zahlen die Uberprufung der physikalischen Gesetze bei bisher unerreich-ten Energien und der Nachweis des Higgs-Bosons. Dieses Teilchen, das letzte desStandardmodells, das noch nicht beobachtet werden konnte, ist der zugrunde lie-genden Theorie zufolge verantwortlich fur den Ursprung der Masse von Teilchen.Ein Nachweis ware ein herausragender Triumph der Wissenschaft und ein deutli-ches Indiz fur die Richtigkeit des Standardmodells der Teilchenphysik. Die Massedes Higgs-Bosons kann in der Theorie nur vage eingegrenzt werden. Des Weiterenkonnten bisherige Experimente nur eine untere Ausschlussgrenze fur die Higgsmas-se angeben. Der LHC erweitert den erschließbaren Bereich der Suche nach demHiggs-Boson, indem zwei gegenlaufige Protonenstrahlen bei einer Schwerpunkts-energie von 14 TeV zur Kollision gebracht werden. Eines der vier Hauptexperi-mente, welches die Proton-Proton-Kollisionen aufzeichnen wird, ist der CompactMuon Solenoid (CMS) Detektor, der speziell fur die Suche nach einem “leichten”Higgs-Boson konzipiert wurde.

Bevor die Datennahme startet, mussen umfangreiche Simulationen durchgefuhrtwerden, um die Signaturen der verschiedenen Ereignistypen im Detektor abschatzenzu konnen. Die Forschergemeinschaft verwendet hierbei unterschiedliche Monte-Carlo-Verfahren, um verschiedene physikalische Modelle bei den spezifischen Schrit-ten der Kollisionssimulation vergleichen konnen.

i

Aufgrund der immensen Datenrate der vier Hauptdetektoren am LHC hat mansich entschlossen, ein neues Konzept fur die Datenverarbeitung einzufuhren. DasWorldwide LHC Computing Grid (WLCG) ist ein Netzwerk von zahlreichen Re-chenzentren, die den Wissenschaftlern auf der ganzen Welt Rechenleistung, Spei-cherplatz und Zugang zu gemeinsamen Datensatzen ermoglichen. Diese Grid-Zen-tren mussen strenge Auflagen bezuglich der operativen Verfugbarkeit erfullen. Umdie Ausfallzeiten zu reduzieren, sind spezielle Monitoring-Systeme fur die Storungs-erkennung notwendig. Die aktuelle Monitoring-Infrastruktur des WLCG weist je-doch einige konzeptionelle Schwachen auf, die eine regulare Kontrolle eines speziel-len Grid-Zentrums und seiner Dienste unnotig verlangsamen und zudem erschwe-ren.

Im Rahmen dieser Diplomarbeit wurde ein Meta-Monitoring-System namens“HappyFace Project” entwickelt, um eine deutlich einfachere und schnellere Fehler-ermittlung zu gewahrleisten. Diese Anwendung erlaubt es, verschiedenste Monito-ring-Datenquellen miteinander zu korrelieren, und bietet einen zusammenfassenden,aktuellen Uberblick mit allen wichtigen Informationen uber den Betriebsstatus ei-nes Grid-Zentrums und seiner Dienste. In der Zwischenzeit haben weitere deutscheInstitute der WLCG-Kollaboration damit begonnen, dieses System fur ihr eigenesMonitoring zu verwenden. Ein langfristiges Ziel wird es sein, eine standardisierteDatenausgabe fur alle unterstutzen Grid-Zentren zu erarbeiten, um einen globalenUberblick auf den Verfugbarkeitsstatus von jedem Grid-Zentrum bzw. des WLCGzu ermoglichen.

Ein vielversprechender Kanal fur einen Nachweis des Higgs-Bosons in einem Mas-senbereich zwischen 114 GeV und 166 GeV, ist der sogenannte Vektorbosonfusions-Prozess, der sich durch eine klare Signalstruktur auszeichnet. Verschiedene Simu-lationsvorgange des Prozesses pp → Hjj → τ+τ−jj mit einer Higgsmasse vonmH = 120 GeV wurden untersucht. Im Mittelpunkt der Physikanalyse dieser Di-plomarbeit steht der Vergleich verschiedener Monte-Carlo-Generatoren fur diesenProzess.

Ein Vektorbosonfusions-Prozess ist gekennzeichnet durch zwei außerst energie-reiche Jets, die den ausgehenden Quarks aus dem harten Prozess entstammen, diesogenannten Tagging Jets. Diese haben in der Regel einen geringen Winkel zu deneinlaufenden Protonstrahlen und spannen einen Bereich auf, der als Rapiditatsluckebezeichnet wird. In diesem Bereich ist aufgrund des fehlenden Farbflusses nur einegeringe hadronische Aktivitat zu verzeichnen. Fur eine korrekte Ereignisklassifizie-rung wurden zusatzliche Jets, die durch den Parton Shower, Hadronisierung undUnderlying Event entstehen, untersucht. Wahrend das Matrixelement einer hartenWechselwirkung durch Storungstheorie berechnet werden kann, muss die Erzeugungdieser Jets zum Teil auf phanomenologische Modelle, die durchaus verschiedeneVorhersagen liefern konnen, zuruckgreifen. Die beiden Monte-Carlo GeneratorenHerwig++ und Pythia unterscheiden sich unter anderem gerade in diesen Model-len.

ii

Ein Datensatz wurde komplett mit den Monte-Carlo-Generator Pythia erzeugtund dient als Referenz. Die Endzustande von vier weiteren Datensatzen, die auf denMatrix-Element-Generator Vbfnlo basieren, wurden mit Hilfe der GeneratorenHerwig++ und Pythia simuliert. Jeweils zwei der Datensatze wurden mit undohne mehrfacher Partonstreuung (Multiple Parton Interaction) erzeugt.

Der Vergleich der kinematischen Eigenschaften der Teilchen aus dem harten Pro-zess ergab eine gute Ubereinstimmung zwischen den Matrix-Element-Berechnungenvon Vbfnlo und Pythia. Der hadronische Endzustand andererseits zeigt enormeAbweichungen zwischen Herwig++ und Pythia betreffend der kinematisches Ei-genschaften zusatzlicher Jets. Abbildung 0.1 zeigt die z∗ Verteilung,

z∗ =y∗

|y1 − y2|mit y∗ = y3 −

12(y1 + y2) ,

welche ein Maß fur die Lage des dritthartesten Jets bezuglich der fuhrenden Jets,geordnet nach dem Transversalimpuls ist.

Wahrend die Maxima der beiden Herwig++ Datensatze außerhalb von ±0.5liegen, was einer Richtung außerhalb der Rapiditatslucke entspricht, findet manden dritten Jet der Verteilungen bei Pythia eher im Zentralbereich.

z*-1.5 -1 -0.5 0 0.5 1 1.5

arb.

uni

ts

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.0453rd Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Abbildung 0.1: z∗

Verteilung des dritt-hartesten Jets oh-ne einen Schnitt aufden Transversalim-pulses.

Weiterhin kann beobachtet werden, dass Herwig++ bevorzugt Jets mit einemniedrigeren Transversalimpuls erzeugt als Pythia dies tut. Diese Resultate sindentscheidend fur die Anwendung eines kinematisches Schnittes (zentrales Jet-Veto- Central Jet Veto), welcher Ereignisse verwirft, die einen zentralen Jet mit einemhohen Transversalimpuls beinhalten. Der dadurch unterdruckte Untergrund fuhrtzu einer Erhohung des Anteils an gewunschten Signalereignissen. Die aus den Ver-teilungen des Transversalimpulses eines zentralen Jets folgende Vetoeffizienz gibtden Anteil der Signalereignisse an, die bei einem Jet-Veto fur einen gegebenen Mini-malwert des Transversalimpulses akzeptiert werden. Diese Effizienz ist in Abbildung0.2 dargestellt.

iii

T,minVBF events passing central jet veto, p

0 10 20 30 40 50 60 70 80 90 100

cut e

ffici

ency

0

0.2

0.4

0.6

0.8

1

Central Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Abbildung 0.2:Anteil der Signa-lereignisse, die beieiner Begrenzung(Central Jet Veto)fur einen gegebe-nen pT,min Wertakzeptiert werden.

Je nach dem, welche Vorhersage besser ist, lasst sich ein angemessenes Jet-Veto auf den Transversalimpuls des zentralen Jets mit einem pT,min Wert zwischen10 GeV und 25 GeV einfuhren. Um nun in der Lage zu sein, das Higgs-Boson imuntersuchten Kanal zu finden, ist es dringend notig, die Unterschiede zwischen denbeiden Monte-Carlo-Generatoren weiter zu untersuchen und zu verstehen. Weiter-hin ist eine Uberprufung durch erste LHC-Daten unabdingbar. Beispielsweise isthierfur der Kanal Z → µµ geeignet, um theoretische Uberlegungen mit der Realitatzu vergleichen.

iv

ppppppppppppp Universitat Karlsruhe (TH)

Development of aMeta Monitoring System for Grid Sites

andEffects of the Simulation of Hadronic

Jets on the Reconstruction Efficiency inthe Vector Boson Fusion Channel H → ττ

Viktor Mauch

Diplomarbeit

an der Fakultat fur Physikder Universitat Karlsruhe

Referent: Prof. Dr. G. Quast


Korreferent: Priv. Doz. Dr. W. Wagner


17. November 2008

Contents

1. Standard Model of Particle Physics 31.1. Electromagnetic Interaction . . . . . . . . . . . . . . . . . . . . . . . 51.2. Weak Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.3. Electroweak Unification . . . . . . . . . . . . . . . . . . . . . . . . . 61.4. The Higgs Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . 71.5. Higgs Phenomenology . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.5.1. Production of the Higgs boson . . . . . . . . . . . . . . . . . 91.5.2. Higgs Boson Search . . . . . . . . . . . . . . . . . . . . . . . 11

1.6. Results From Recent Analyses . . . . . . . . . . . . . . . . . . . . . 13

2. The Compact Muon Solenoid at the Large Hadron Collider 152.1. The Large Hadron Collider . . . . . . . . . . . . . . . . . . . . . . . 152.2. Compact Muon Solenoid . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.2.1. The Tracking System . . . . . . . . . . . . . . . . . . . . . . 172.2.2. The Electromagnetic Calorimeter . . . . . . . . . . . . . . . . 182.2.3. The Hadronic Calorimeter . . . . . . . . . . . . . . . . . . . . 192.2.4. The Muon Chambers . . . . . . . . . . . . . . . . . . . . . . . 192.2.5. Trigger and Data Acquisition System . . . . . . . . . . . . . 21

3. Software Tools 233.1. ROOT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233.2. Monte-Carlo Event Generation . . . . . . . . . . . . . . . . . . . . . 23

3.2.1. VBFNLO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233.2.2. Pythia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243.2.3. Herwig++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253.2.4. HepMC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

3.3. CMSSW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263.3.1. Event Data Model . . . . . . . . . . . . . . . . . . . . . . . . 263.3.2. Modular Architecture . . . . . . . . . . . . . . . . . . . . . . 273.3.3. Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283.3.4. Jet Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 28

4. The Worldwide LHC Computing Grid 314.1. Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314.2. Workflow of the WLCG . . . . . . . . . . . . . . . . . . . . . . . . . 324.3. Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

i

Contents

4.3.1. Available Monitoring Sources . . . . . . . . . . . . . . . . . . 344.3.2. Problems of the Current Monitoring Infrastructure . . . . . . 35

4.4. The HappyFace Project . . . . . . . . . . . . . . . . . . . . . . . . . 354.4.1. Functionality of the HappyFace Framework . . . . . . . . . . 364.4.2. Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384.4.3. Test Implementation . . . . . . . . . . . . . . . . . . . . . . . 384.4.4. Data Extraction and Access . . . . . . . . . . . . . . . . . . . 444.4.5. History Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . 464.4.6. Conclusion & Outlook . . . . . . . . . . . . . . . . . . . . . . 46

5. Analysis 495.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

5.1.1. Event topology of H → τ+τ− . . . . . . . . . . . . . . . . . . 495.1.2. Data Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

5.2. Parton Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515.3. Particle Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

5.3.1. Tagging Jets . . . . . . . . . . . . . . . . . . . . . . . . . . . 565.3.2. Third Jet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 595.3.3. Central Jet . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

6. Conclusion & Outlook 67

A. The Les Houches Accord 69

B. The HappyFace Project - Source Code 71B.1. Main Category Module “FaceProduction” . . . . . . . . . . . . . . . 71B.2. Data Module “FaceXMLParser” . . . . . . . . . . . . . . . . . . . . 73

C. Monte Carlo Datasets 75C.1. Pure Pythia Reference Sample . . . . . . . . . . . . . . . . . . . . . 75

C.1.1. Pythia Underlying Event Tune (D6T) . . . . . . . . . . . . . 75C.2. VBFNLO Based Samples . . . . . . . . . . . . . . . . . . . . . . . . 76

C.2.1. VBFNLO General Config File . . . . . . . . . . . . . . . . . . 77C.2.2. VBFNLO Cuts Config File . . . . . . . . . . . . . . . . . . . 79

D. Additional Plots 81D.1. Parton Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

D.1.1. Higgs Boson . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81D.1.2. Taus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82D.1.3. Outgoing Quarks . . . . . . . . . . . . . . . . . . . . . . . . . 83

D.2. Particle Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83D.2.1. Tagging Jets . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

D.3. Comparison with Official Data . . . . . . . . . . . . . . . . . . . . . 85D.4. Initial and Final State Radiation of Pyhtia 6 . . . . . . . . . . . . . 86D.5. Inconsistency of Pythia 6 . . . . . . . . . . . . . . . . . . . . . . . . 87

ii

Contents

List of Figures 89

List of Tables 93

Bibliography 95

iii

Contents

iv

Introduction

Within the human nature, curiosity is an outstanding peculiarity, giving mankindthe ambition to explore its environment. Today research in physics examines ouruniverse and its principles from astronomic scales to the smallest constituents ofmatter and their interactions. Due to the technological improvement since the19th century, new complex experiments have extended our knowledge of particlephysics dramatically. Besides the gravitational force which is responsible for theformation of structure in space, there are three further fundamental forces. Theelectromagnetic force acts between charged particles, the strong and weak forcebecome dominant on sub-atomic scales. These forces and the affected particles aredescribed in the Standard Model of particle physics. However unification of gravitywith the Standard Model is so far not succeeded.

In 2009, a new particle accelerator, the Large Hadron Collider (LHC) starts itsoperation at CERN near Geneva, Switzerland. Some of the main goals of thescientists are the verification of the current physics laws in a new energy range andthe discovery of the Higgs boson, which is a consequence of the current model toexplain how particles get their mass. Therefore, two anti-parallel proton beamsare colliding at a centre-of-mass energy of 14 TeV, that is about seven times morethan the up to this date most powerful accelerator Tevatron. One of the twomulti-purpose detectors is the Compact Muon Solenoid (CMS) which is especiallydesigned to find a “light” Higgs boson.

Before the data taking will start, simulations have to be done to estimate thedetector response. Different Monte Carlo techniques are used by the particle physicscommunity to compare different models at specified steps of the collision simulation.

Due to the immense data rate of the four main detectors of the LHC, a new com-puting concept was introduced by the LHC collaborations. The Worldwide LHCComputing Grid (WLCG) is a network of numerous computing centres, which pro-vide computing resources for the scientists all over the world. These computingcentres have to keep obligations concerning the operational availability. To reducethe downtime, monitoring applications which ease the detection of failures, arenecessary. However, the current monitoring infrastructure has conceptional short-comings providing a regular check of a specific computing centre and its services.

In the first chapter, a brief introduction to the Standard Model of particle physicsis given, with emphasis on the Higgs mechanism. The second chapter copes with thedescription of the CMS detector and its components. Chapter 3 presents the soft-ware packages needed for this thesis and describes different Monte Carlo generatorsused for the physics analysis. Chapter 4 focuses on the WLCG and the meta moni-toring application “The HappyFace Project”, which was developed within the scope

1

Contents

of this thesis. Finally, chapter 5 explain the comparison of specific quantities onparton and generator level of the vector boson fusion process pp → Hjj → τ+τ−jj.Therefore different Monte Carlo generation chains were used, from matrix elementcalculation to parton shower and hadronisation.

2

1. Standard Model of Particle Physics

The origins of the atomic theory can be traced back to ancient times. Greekphilosophers established a model which assumes that the world consists of indivis-ible particles called “atomos”. Centuries later, Ernest Rutherford introducedan improved model which describes the substructure of atoms. In his famous goldfoil experiment, he discovered that an atom consists of a charged core and orbitingelectrons. From there on, with increasing energies of the collision experiments, neweffects were discovered and new theories emerged which enhanced our knowledgeabout the principles of matter.

Today, modern physics describes all observed processes in nature by four dif-ferent fundamental forces: gravitation as an interaction between massive objects,electro-magnetic interaction between electrically charged objects, strong interactionbetween coloured quarks and gluons in sub-atomic scales and the weak interactionwhich is amongst other things responsible for the radioactive beta decay (see Tab.1.1).

particle interaction mass JP q T3

Photon (γ) electr.magn. – 1− 0 0Z0 weak 91.18 GeV 1 0 0W± weak 80.40 GeV 1 ±e ±1

8 Gluons (g) strong – 1− 0 ±1

Table 1.1: The gauge bosons in the Standard Model and various parameters:quantum numbers JP , electric charge q and the third component of the weakisospin T3 [1].

The last three forces are combined to the Standard Model of particle physics.In this model, forces are mediated by vector-bosons with spin ~. Beside these,mediators there are two groups of fundamental particles: quarks and leptons (seeTab. 1.2). Due to a spin of ~/2, these particles are subsumed under the namefermions. Each of them can be assigned to one of the three families, also calledgenerations. Furthermore, each of the twelve has an assigned anti-particle with thesame mass but opposite quantum numbers.

Because of rare transitions of quarks from one doublet to another, the masseigenstates are not identical to the eigenstates which diagonalise the weak interac-tion. The relation between both representations is provided by the following CKM

3


FermionsGeneration electr.

spin weak isospin colour1 2 3 charge

Leptonsνe νµ ντ 0 ~/2

+1/2–

e µ τ −e −1/2

Quarksu c t +2/3e ~/2

+1/2r, g, b

d′ s′ b′ −1/3e −1/2

Table 1.2: The fundamental fermions are grouped pair wise in three generationsforming isospin doublets. The dashes for the down-type quarks indicate thatthe mass eigenstates of quarks (given here) are not identical with the eigenstatesof the weak interaction.

matrix 1. |d′〉|s′〉|b′〉

=

Vud Vus Vub

Vcd Vcs Vcb

Vtd Vts Vtb

|d〉|s〉|b〉

In experiments, only composite particles of two and three quarks, called mesons

and baryons respectively, are observed. The discovery of the ∆++ particle, made upfrom three up-quarks, required a new quantum number to be introduced for quarksto preserve Pauli’s exclusion principle for fermions. A new degree of freedom calledcolour was added with the three possible values red, green and blue. Quarks carrya colour and anti-quarks an anti-colour. A homogeneous mixing of these colourswould result white. Quantum chromo dynamics only allows colour-neutral stablehadrons, which can be composed of either the three colours, the three anti-coloursor, for mesons, a colour and an anti-colour.

The mediating particles of the hard interaction are the gluons which carry colour-charge themselves. They form an octet of states with colour and anti-colour withone possible representation being:

rb, rg, bg, br, gr, gb,1√2(rr − bb),

1√6(rr + bb− 2gg)

The used colours are completely random choices; the gluons could be rotated incolour space. There is also one colour singlet which is colour-neutral and can beexpressed as:

1√3(rr + bb + gg)

This gluon does not interact with coloured objects and is therefore non-observable.The fact that gluons can self-couple leads to a completely different behaviour ofcoloured objects when being separated in contrast to electric charges. If quarks

1Cabibbo-Kobayashi-Maskawa matrix

4

1.1. Electromagnetic Interaction

or gluons move apart from each other a gluon band is formed between them withan increasing energy proportional to the distance. At a certain threshold, thefragmentation process starts to create new colourless particles out of the vacuum.

1.1. Electromagnetic Interaction

Classical physics allows a short formulation of electromagnetism using a lorentz-covariant form 2:

∂µFµν = jν

with the electromagnetic field tensor

Fµν = ∂µAν − ∂νAµ ,

and the four-current and electromagnetic four-potential

jµ =(

ρ~j

)Aµ =

(φ~A

).

The charge and the current density are denoted as ρ and ~j. The connection of theelectrostatic scalar potential ρ and the magnetic vector potential ~A is given by theexpressions of the magnetic and electric fields:

~B = ~∇× ~A ~E = −~∇φ− ∂ ~A

∂t

A transformation of the electromagnetic four-potential with an arbitrary, differen-tiable scalar field Λ(x), does not change the fields ~E and ~B:

Aµ → A′µ = Aµ − ∂µΛ(x)

1.2. Weak Interaction

The weak interaction is the only fundamental interaction that can transform quarksand leptons. Transitions of leptons always occur with a corresponding neutrino.The lepton number is preserved family-wise in the weak interaction. The mediatingparticles are charged gauge bosons. These facts lead to a description in doubletsand the introduction of a weak isospin. Ladder operators (νL and lL) carry out thetransitions:

2From here on, the convention c = ~ = 1 is used.

5


νL = ΨL

(10

), lL = ΨL

(01

)with νL = σ+lL , σ± =

12(σx ± σy)

where the left-handed Dirac spinor is denoted by ΨL and the Pauli matrices byσ±. Due to the existence of three generators σi, three gauge fields W i have to beintroduced. However, it is not possible to assign the gauge fields directly to W±

and Z0 because the coupling of the Z0 also depends on the electric charge (see Tab.1.3)

decay channel branching ratio

Z0 → l+l− (10.10± 0.01)%Z0 → νν (20.00± 0.06%

Table 1.3: The branching ratios of the Z0 boson indicate a dependency onthe electric charge. If the coupling depended on the weak charge only, bothnumbers would be equal (numbers taken from [1]).

Furthermore, experiments have shown that nature distinguishes between left- andright-handed leptons. Only left-handed leptons are able to couple to the chargedweak current mediated by weak vector-bosons, as can be seen Fig. 1.1.

The spin ~s and the momentum ~p of a particle define its helicity:

h =~s · ~p|~s||~p|

This quantity is only lorentz invariant for massless particles and equivalent tochirality in this case. Due to experimental studies, an arrangement was madein doublets for the left-handed leptons and singlets for the right-handed leptons.Neutrinos, which are assumed to be massless, are left-handed particles (see Tab.1.4).

eL

νe,L

W−

eR

νe,R

W−

Figure 1.1: Weak interaction mediates transitions of leptons. As weak cur-rents only couple to left-handed fermions (and right-handed anti-fermions) thetransition depicted in the right-hand plot cannot be observed [2].

1.3. Electroweak Unification

To achieve an electroweak unification one has to introduce another field B0. Thisfield should be a scalar singlet of the weak isospin with a hypercharge Y as the

6

1.4. The Higgs Mechanism

GenerationT T31 2 3(

νe

e−

)L

(νµ

µ−

)L

(ντ

τ−

)L

1+1

2−1

2

(e−)R (µ−)R (τ−)R 0 0

Table 1.4: Due to lepton universality, leptons and neutrinos can be arrangedin multiplets. As neutrinos are massless, they can only appear as left-handedparticles. The left-handed quarks can be arranged in three doublets accordingto their generation and six singlets for the right-handed quarks. The chargedgauge bosons W± have a weak isospin of T = ±1, hence the third component(T3) of the weak isospin is conserved in transitions.

coupling charge. The Gell-Mann-Nishijima relation provides the connection to theelectric charge and the weak isospin:

Q = I3 +Y

2

The fields of the gauge bosons W±, Z0 and Aµ are linear combinations of the fourfields W i and B0:

W± =1√2(W 1 ∓ iW 2)

Z0 = − sin (θW)B0 + cos (θW)W 3 Aµ = cos (θW)B0 + sin (θW)W 3

The fact that photons couple to the electric charge of right- and left-handed fermionsbut not to neutral neutrinos leads to the Weinberg angle θW with sin2 (θW) ≈0.232 [1]. The precondition for invariance under local gauge transformation com-bined with the familiar spin formalism leads to unification of the electromagneticand weak interaction to a SU(2)L ⊗U(1)Y group. In contrast to the theory whichpredicts massless bosons, experiments observed massive bosons.

1.4. The Higgs Mechanism

To explain the masses of the the W± and Z0 bosons the concept of spontaneoussymmetry breaking has been proposed by P. Higgs [3]. One introduces an additionalfield, the so-called Higgs field which interacts with all other fields and itself. It is ascalar SU(2) doublet

7


Φ =(

φ+

φ0

)with the potential V (Φ) = µ2|Φ†Φ|+ λ|Φ†Φ|2

If µ2 < 0 the field has a non-disappearing vacuum expectation value:

v =

√−µ2

λ(> 0)

The symmetry is broken spontaneously. The expectation value of the ground state

0�2 > 0 >�

V(�)

+v0�2 < 0 >�

V(�)

Figure 1.2: Illustration of the spontaneous symmetry breaking: for µ2 < 0 theφ = 0 is an instable equilibrium, a real system will randomly choose φ = ±vas ground state.

Φ0 is taken as

|〈Φ0〉| =√−µ2

2λ=

v√2

The parameterisation of the Higgs field with a small deviation at the ground statecombined with the choice of the unitary gauge leads to the expression of Φ:

Φ =1√2

(0

v + H

)where H is an elementary neutral scalar field, the Higgs boson. The kinematic partof the Lagrangian density of the Higgs field has now the following expression

LHiggs = (DµΦ)†(DµΦ)

whereiDµ = i∂µ − g2

~IW~Wµ − g1Y Bµ

8

1.5. Higgs Phenomenology

is the covariant derivative with respect to the gauge fields ~W , B for the weakisospin ~I and the hypercharge Y . The covariant derivative describes gauge invariantcouplings of the Higgs boson to the gauge fields producing mass terms for gaugebosons and fermions. The acquired mass is proportional to the coupling of thegauge boson [4]. In order to verify the Higgs mechanism and to determine itsproperties, it is necessary to actually discover the Higgs boson and to measure itscouplings.


1.5.1. Production of the Higgs boson

The crucial quantities of the cross-sections for the different production modes, seeFig. 1.3, are the kind of collider experiment and the centre-of-mass energy. Thecollision of particles with a sub-structure like protons leads to a hard interactionbetween the constituents which contribute a fraction of the total longitudinal mo-mentum.

Figure 1.3: Different production modes at leading order for the Higgs boson:gluon fusion with a top quark loop (a), weak boson fusion (b), Higgs-strahlung(c) and associated production (d)

9


The parton density function (PDF) describes the probability fi(x,Q2) to find aparton i of the proton with a certain fraction x of the total proton momentum.The PDF depends on the energy transfer Q of the collision. On low energy scales(< 1 GeV) a proton behaves like a point like particle. With increasing energythe three valence quarks of the proton become “visible” for a hard interaction. Afurther increase of the energy leads to virtual quark-anti-quark pairs and gluons inscattering processes (see also Fig. 1.4).

Figure 1.4: Parton density function for quarks and gluons for Q2 =(140 GeV/c)2 = 19600GeV2/c2 using CTEQ5L[5]

The dominant production process for the Higgs boson is the gluon-fusion, seeFig. 1.3a. The vector boson fusion channel has a 10 times smaller cross section.However, the clear signature with two forward directed jets and a reduced hadronicactivity (due to the lack of colour flow) in the central region of the detector allows

10


a quite good classification of the desired signal events. This channel is used in thisthesis and will be explained later in detail. Other possibilities to produce a Higgsboson are provided through the radiation by an off-shell Drell-Yan resonance orthrough a top quark. Both channels have a much lower cross section. They can beused for a Higgs boson search with the requirement of a high momentum leptonoriginating from the associated particles in the case of a Higgs boson decay intotwo photons.

1.5.2. Higgs Boson Search

BR(H)

bb_

τ+τ−

cc_

gg

WW

ZZ

tt-

γγ Zγ

MH [GeV]50 100 200 500 1000

10-3

10-2

10-1

1

Figure 1.5: Branching ratios of the main decay channels of the Higgs bosondepending on its mass (taken from [6])

The decay modes of the Higgs boson depend on its mass. Fig. 1.5 shows thedominance of the different branching ratios of the decay modes in relation to themass range. A Higgs boson with a mass smaller than two vector bosons, preferablydecays into two bottom quarks, a decay channel which is hard to detect due to thehigh QCD bottom quark production cross-section which accounts as an irreduciblebackground.

The decay of H → τ+τ− has a branching ratio which is ten times smaller thanthe H → bb decay. In combination with a restriction of the Higgs boson producedin vector boson fusion, this decay allows a powerful reduction of events comingfrom background.

The branching ratio of the decay into two gluons is comparable to the H → τ+τ−

11


Γ(H) [GeV]

MH [GeV]50 100 200 500 1000

10-3

10-2

10-1

1

10

10 2

Figure 1.6: Decay width Γ of the Higgs boson depending on its mass (takenfrom [6])

decay. However, the QCD background is even higher than for the bb decay.The decay channel to two photons has a branching ratio of some �because

the process can only happen at next-to-leading order. Nonetheless, there is still achance to detect the Higgs boson in this channel, as photons can be detected veryaccurately. Therefore, the CMS collaboration decided to use a very precise electro-magnetic calorimeter and a silicon tracker with a very high spatial resolution.

In a mass range above 135 GeV, the branching ratios of the weak vector bosondecays become dominant. Above a mass of 200 GeV the WW decay is twice asprbable as the ZZ decay since the W bosons have two possible final stats concerningtheir charges. The fully-leptonic decay of both Z bosons with a very clear signaland also the semi-leptonic channel are suitable for a Higgs boson discovery [7, 8].The WW decay on the other hand provides no narrow mass peak for reconstruction.Therefore, analyses deal with the investigation of the background contributions tothis signal channel [9, 10].

Due to the increasing decay width of the Higgs boson (see Fig. 1.6), it is nearlyimpossible to discover a decaying Higgs boson into a top pair on a mass range above400 GeV.

All mentioned channels will be investigated to discover the higgs at a certainmass or to establish new exclusion limits

prove the discovery of the Higgs boson with a certain mass or to establish newexclusion limits.

12

1.6. Results From Recent Analyses

1.6. Results From Recent Analyses

The two experiments CDF and DØ of the up to this date most powerful acceleratorTevatron continued their research in pp collision at a centre-of-mass energy of

√s =

1.96 TeV. The results concerning the limits on the production cross section canbe found in Fig. 1.7. The exact measurement of electroweak parameters giveinformation about the Higgs boson mass. The combination of the results of LEP,Tevatron and SLC, provided by the electroweak working group at LEP [11], givesan upper limit of about 190 GeV at a confidence level of 95%.

Figure 1.7: Combined results from CDF and DØ analyses with an integratedluminosity of 3 fb−1: Limits on the production cross section of a Higgs bosonas a function of the Higgs boson test mass.[12]

13


14

2. The Compact Muon Solenoid at theLarge Hadron Collider

The Large Hadron Collider (LHC) experiment located at CERN [13] near Geneva,Switzerland is the most ambitious high erergy physics project so far. It will beable to collide protons at a centre-of-mass energy of up to 14TeV and has a designluminosity of 1034 cm−2s−1. The accelerator ring is built in an underground tun-nel, passing the Swiss-French border, and accommodates the four main detectorexperiments ALICE, ATLAS, CMS and LHCb, which are situated at defined inter-section points of the two opposing particle beams. ATLAS [14] and the CompactMuon Solenoid (CMS) are two multi-purpose detectors. Their major tasks are thesearch for the Higgs boson and physics beyond the Standard Model. The LHCb[15] detector is specialised on b-quark physics especially CP violation. ALICE [16]will study lead-lead collisions at a centre-of-mass energy of 2.76 TeV per nucleon.Its goal is to produce and explore a quark-gluon plasma which could have existedunder conditions similar to a very early period of the universe. A further experi-ment is TOTEM [17], placed near the CMS experiment. It is designed to measurethe cross-section of total proton-proton collisions.

2.1. The Large Hadron Collider

The LHC is a 26.7km long ring collider built in the same tunnel that formerlyhosted the Large Electron Positron Collider (LEP) experiment.

To keep the protons on their track, about 1232 dipole magnets provide a magneticfield up to 8.33T. The limitation of the centre-of-mass energy is a result of the di-rect proportional dependency between the maximum dipole field and the energy ofthe particles. The maintenance of such a strong magnetic field can only be realisedthrough superconductivity. Therefore the dipoles use niobium-titanium (NbTi) ca-bles, which lose their electric resistance below a temperature of 10 K (−263.2°C).In fact, the LHC will operate at 1.9K (−271.3°C) to achieve a current of 11700 A,which is necessary to create a high magnetic field of 8.33 T which corresponds to aproton beam energy of 7 TeV. The whole cooling process will take a few weeks. Inthe last step superfluid helium is used. With its high thermal conductivity, super-fluid helium is an excellent choice as coolant for large superconductivity systemsand is therefore used for the cooling to 1.9 K.

To achieve a final particle energy of 7TeV, the protons are running through thepre-acceleration chain shown in the figure 2.1. Before the protons are transferredto the LHC ring, the Proton Synchrotron (PS) accelerates them to an energy of

15

2. The Compact Muon Solenoid at the Large Hadron Collider

25 GeV, followed by the Super Proton Synchrotron (SPS), which increases theirenergy to a value of 450 GeV. Then the final acceleration takes 20 minutes in thebeam pipe of the LHC. The complete particle beam is divided into 2808 bunches,each of them containing about 1.15× 1011 protons. Each bunch is separated fromthe next one by a time lag of 25 ns, which corresponds to a minimum distance of 7 m.At a relativistic speed of 0.999999 c, the protons in the LHC ring will make 11245revolutions every second, resulting in around 600 million proton-proton collisionsper second at the intersection points.

CERNfaqLHCthe guide

LINAC 2

Gran Sasso

North Area

LINAC 3Ions

East Area

TI2TI8

TT41TT40

CTF3

TT2

TT10

TT60

e–

ALICE

ATLAS

LHCb

CMS

CNGS

neutrinos

neutrons

pp

SPS

ISOLDEBOOSTERAD

LEIR

n-ToF

LHC

PS

6794_07_LHC_cover_07_K2_wd.indd 1 14.01.2008 9:23:05 Uhr

Figure 2.1: Schematic view of the CERN accelerator complex. The graphicillustrates the chain from the proton injection up to the final collision energyof 7 TeV in the LHC [18].

2.2. Compact Muon Solenoid

The CMS experiment has a compact design compared to the ATLAS, which persuesthe same physics goals. The calorimeter system of CMS is built inside the hugesolenoid. With a total weight of 12500 metric tons, a length of 21 m and a diameterof 15m, it is considerable heavier than ATLAS with its 7000 metric tons, but takesonly a sixth part of the ATLAS volume. Figure 2.2 illustrates the detector topology.In the following subsections several important parts of the detector are described.

More than 3000 scientists and engineers from 183 institutes in 38 countries (June2008) [19] work for the CMS collaboration in different disciplines like detector

16


construction, computing and physics analysis.

C ompac t Muon S olenoid

Pixel Detector

Silicon Tracker

Very-forwardCalorimeter

Electromagnetic�Calorimeter

HadronCalorimeter

Preshower

Muon�Detectors

Superconducting Solenoid

Figure 2.2: Overview over the CMS detector and its components [20].

2.2.1. The Tracking System

The innermost subdetector of CMS is the tracking system, consisting of pixel andstrip detectors. Due to the location close to the intersection point, the componentshave to endure a very high particle flux. Therefore, special attention is paid to thedurability under hard radiation. The complete subsystem has a length of 5.8 mand a diameter of 2.4 m. It covers a cylinder shaped area up to a pseudo-rapidityrange of 2.4.

Two kinds of tracking technologies are used. The most central part is the pixeltracker consisting of silicon pixel detectors with a size of 100× 150 µm2 ordered inthree concentric layers. Special filter techniques allow a spatial resolution of about10 µm in the r-φ-plane and 20 µm in z-direction. This high resolution is necessaryfor the determination of secondary vertices which are required for the detection ofjets created by bottom quarks. The strip tracker, which is located around the pixeltracker, is structured by ten twisted layers of silicon strip detectors. The resolutionhere depends on the distance to the beam pipe. The inner part reaches a spatialresolution of 23 µm in the r-φ-plane and 230 µm in the z-direction. In the outersections the resolution values increase to 53 µm and 530 µm, respectively.

17


Charged particles can be detected by the measurement of amplified currentsresulting from the ionisation of the tracker material. Because of the magnetic fieldthe tracks of the charged particles are bent on a helix. The extrapolated radius hasa direct proportional dependency to the momentum of the particle.

2.2.2. The Electromagnetic Calorimeter

Electrons, positrons and photons create electro-magnetic showers inside dense ma-terial by bremsstrahlung and electron-positron pair production. The total depositedenergy of the shower is proportional to the energy of the original incoming particle.

To provide an excellent energy estimation, a Electromagnetic Colorimeter (ECAL)should have a short radiation length und small Moliere radii 1. The CMS collab-oration decided to use a scintillation calorimeter made of lead tungstate (PbW04)consisting of 80000 crystals inside a solenoid.

The measurement of the showers is performed by photo-multipliers to provideinformation on the incoming particles. Every crystal covers 1° in the φ-η-plane andis 23cm long. The resulting 25.8 radiation lengths, a Moliere radius of 2.2cm anda light emittance of 80% within 25 ns allow an excellent energy resolution which isamong others important for the search of the Higgs boson decay into two photon(H → γγ).

1By definition, it is the radius of a cylinder containing 90% of the shower’s energy deposition. Itis related to the radiation length X0 by the following approximation: RM = 0.0265X0(Z +1.2)

18


2.2.3. The Hadronic Calorimeter

In contrast to photons and electrons, hadronic particles create a cascade by inelas-tic scattering processes. The resulting showers consist mainly of pions, nucleonsand fragments of nuclei. The Hadronic Calorimeter (HCAL) is composed of brassabsorber material and plastic scintillators. The larger part of the shower energyis deposited in the absorber material. Only a small fraction can be used for theenergy estimation, which is considerable worse in comparison to the ECAL.

Apart from providing information on hadronic jets, the output of the HCAL,combined with the ECAL one, is used to calculate the missing energy which iscarried away by particles like muons and neutrinos. The missing energy of muonshas to be corrected due to their electromagnetic interaction with matter. Also otherweakly interacting particles predicted by theories beyond the Standard Model area possibility.

The HCAL achieves a pseudorapidity coverage of |η| < 3. A further forwardcalorimeter extends the measurement range up to a pseudorapidity of 5.0. Becauseof the high particle flux in this section, the forward calorimeter uses steal absorbermaterial with embedded quartz fibres. In this case, Cerenkov light, emitted by theparticles traversing the fibres, is measured by photo-multipliers.

2.2.4. The Muon Chambers

Besides neutrinos muons pass both calorimeter system nearly without depositingenergy. To detect them, large muon chambers consisting of gaseous detectors arebuilt around the superconducting solenoid. Due to the interleaved iron return yokethere is still a magnetic field of up to 1.8T which bends the trajectory of the muonsalso in the outer area. An exact detection of the momentum is crucial for theso-called golden channel where the Higgs boson decays into four muons (H → 4µ).

Three different systems are used for the muon reconstruction. Aluminium drifttubes (DT) are installed in the central region up |η| = 1.2. The endcaps containcathode strip chambers (CSC) for covering an |η| range up to 2.4. Additionally,resistive plate chambers (RPC) are used in both barrel and endcaps. The RPCsprovide a high time resolution with a fast response which is used for the trigger.The detection efficiency of the muon chambers is better than 98% in the barrelregion. To determine the trajectory of the muons accurately, the results from themuon chambers can be combined with the data from the inner tracking systems tothe global muon system.

19


1m 2m 3m 4m 5m 6m 7m0m

Transverse slicethrough CMS

2T

4T

SuperconductingSolenoid

HadronCalorimeter

ElectromagneticCalorimeter

SiliconTracker

Iron return yoke interspersedwith Muon chambers

Key:ElectronCharged Hadron (e.g. Pion)

Muon

PhotonNeutral Hadron (e.g. Neutron)

Figure 2.3: Slice of the CMS detector with the tracks of an electron, a photon, ahadron (e.g. pion) and a muon. In the silicon tracker, all charged particles leavehits which are used for the extrapolation of the trajectories. In the next layer,the energy of γ and e± is estimated followed by the hadron calorimeter whichmeasured the particle showers generated by hadrons like n or π±. Finally, themuon chamber reconstruct the remaining µ±.

20


2.2.5. Trigger and Data Acquisition System

As a result of the enormous interaction rate of about 31.6 MHz 2 and a limitation ofthe possible storage performance of only about 150 events per second, it is necessaryto select only the most interesting events.

The first trigger, the Level-1 trigger, is implemented in the detector electronics.The decision to pass or veto an event is made by evaluating the calorimeter andmuon data. The results correspond to a data rate of about 100 kHz at high lu-minosity and are stored in the hardware buffers. In the next step, the high leveltrigger (HLT) filters the remaining events. This reduction is done by more complexalgorithms which can be reconfigured during operation. With a mean event size of1.5 MB, the final output is about to 225 MB/s. To store and process such a hugedata rate, it is necessary to provide huge computing resources like the establishedcomputing grid.

22808 bunches in the beam pipe × 11245 turn per second

21


22

3. Software Tools

3.1. ROOT

Root [21] is an object-oriented data analysis framework developed at CERN whichwas originally designed for particle physics data analysis. Today Root is also usedin other scientific disciplines such as astronomy and data mining. The frameworkis written in the programming language C++ and provides a C++ interpreter to theuser. It is optimised to handle large data samples and offers numerous analysisfeatures like creating histograms in various formats, fitting the data with arbitraryfunctions and imposing cuts. The user has the possibility to create C++ macrosto automatise the execution of different work steps. Root supports advancedfunctions for graphical output. Due to the fact that Root is developed under anopen-source licence, everybody is allowed to use this software package for free andcan extend its functionality.

3.2. Monte-Carlo Event Generation

In order to find out how the detector signal for a special physics process is expectedto look like, it is necessary to perform simulations before and during the detector isin operation. The quantum mechanical description of nature and the randomness ofeach possible reaction with its probability according to its cross section or branchingratio can be simulated by Monte Carlo (MC) event generators. These applicationsuse probability functions which are evaluated using pseudo-random numbers. Thecomplete simulation of a collider event is subdivided into numerous steps. Theorder is event generation, detector simulation, digitisation and reconstruction. Thefollowing subsections introduce the three MC event generators which are used forthis thesis.

To achieve an adequate statistical precision, millions of events have to be sim-ulated. The comparison between measurements and simulated collisions allowsestimating irreducible backgrounds and validating physics models. After the CMSexperiment will have started, event simulation is still necessary to understand thedetector.

3.2.1. VBFNLO

The physics part of this diploma thesis compares different MC event generatorswith respect to Vector Bosen Fusion processes. One of these generators is Vbfnlo

23

3. Software Tools

hard interaction

underlying event

hard partons

proton remnants

PFS hadronization HFS

p

p K

µ

parton shower

Figure 3.1: Event generation workflow: First, the hard interaction of two par-tons from the incoming beam particles is calculated from the matrix element.Then the outgoing partons from the hard interaction and the underlying eventare showered. In the last step the resulting Partonic Final State (PFS) ishadronised and the generation of the event ends with the Hadronic Final State(HFS) [22].

[23], a parton level Monte Carlo generator which is developed by D. Zeppenfeld etal. from the Institute for Theoretical Physics of the University of Karlsruhe.

Vbfnlo is written in FORTRAN and provides calculation routines for variousVector Boson Fusion processes at NLO QCD. The calculation can be executedin leading (LO) or next-to-leading order (NLO). There are two configuration filesto set up a reaction. In the file vbfnlo.dat it is possible to choose a special VBFprocess and set up parameters like the LO/NLO switch, the employed factorisationscale and the electroweak scheme. The second file cuts.dat allows to implementlimits for particle quantities like transverse momentum, pseudo-rapidity, invariantmass and other important phase space restrictions.

It is also possible to change the Parton Density Function (PDF) via linking theLHAPDF library [24] to the program. The default configuration uses the CTEQ6PDF [25]. The output consists of a particle listing from the hard process with thekinematic quantities and is saved in an XML [26] like format described by the LesHouches Accord (see Appendix A).

3.2.2. Pythia

Pythia [27] is one of the first and still most frequently used Monte Carlo generatorsin the high-energy physics community. It has been developed by the theory groupof the Lund University since 1978 and is completely written in Fortran 77. A newversion, Pythia 8, written in C++ is currently under development. In the meantimethis software branch has achieved almost the same reliability and functionality asthe Fortran version. At the time of writing of this thesis the transition to thenewer C++ version is in progress. The release used for this thesis is Pythia 6.418,the latest stable version of the Fortran branch.

Pythia provides a large collection of calculation routines for 2 → 2 and 2 →

24

3.2. Monte-Carlo Event Generation

3 processes for the hard interaction at leading order precision. Therefore, thematrix element is evaluated according to the chosen reaction. After the hard pro-cess of two incoming partons, showering algorithms calculate the radiation of glu-ons by coloured objects, QED radiation and other higher order corrections. Thehadronisation of the Partonic Final State (PFS) is performed by the Lund stringfragmentation model. In this phenomenological model a quark-antiquark pair isrepresented by a string which moves apart. In the strong interaction, the energy ofthe colour field increases with the distance between the two partons. If the energyis high enough, the string breaks and a new quark-antiquark pair is produced. Thehadronisation will continue until only colour-neutral hadrons remain.

The behaviour of the remaining partons from the beam particles has to be pro-cessed with the help of an underlying event model. Calculations concerning themultiple parton interaction can also be included. The description of the underly-ing event is not trivial. These phenomenological models use different parametersets, so called “tunes”, which are derived from measurements at existing colliderexperiments like the Tevatron.

Pythia also offers the possibility to use other parton-level generators such asVbfnlo or Alpgen with different calculation routines for the hard process. Oneway to transfer the information from the hard process has to be in compliance withthe Les Houches Accord.

3.2.3. Herwig++

Another MC event generator is Herwig++ (Hadron Emission Reactions With In-terfering Gluons) [28]. It is based on the older Herwig MC generator, which waswritten in Fortran and used successfully during the experiments of LEP, HERAand Tevatron. The transition to the LHC experiment causes the necessity to changelarge parts of the source code. Due to the complexity of this undertaking, the devel-opers decided to rewrite the original program in the object-orientated programminglanguage C++.

In contrast to the Lund string model, which is used by Pythia for the fragmen-tation task, Herwig++ hadronises the Partonic Final State with a cluster model.Coloured partons are grouped to colourless clusters. If such a cluster has enoughenergy, new quark-antiquark pairs are produced before the cluster itself performsa decay into a hadron. If the energy does not suffice for a decay, a transfer of themissing energy will be initiated from a neighbouring cluster.

In order to process the underlying event Herwig++ supports the UA5 parame-terisation and a multiparton interaction (MPI) model.

Herwig++ is based on a software toolkit called ThePEG [29]. It defines a generalstructure in terms of abstract base classes for implementing physics models of eventgeneration in high energy particle collisions. The contained routines describe basicfunctionalities like hard partonic matrix elements, parton showers and the decayof unstable particles. In order to implement a new model, new classes have to be

25

3. Software Tools

created which inherit from the base class collection.

3.2.4. HepMC

To store the event data from diffrent MC event generators, standardised specifi-cations are necessary to provide a common output format. Therefore, the objectoriented event record HepMC [30] was developed. The package has been kept assimple as possible with minimal dependencies. It supports several features likestorage of spin density matrices and mother-daughter relationships. Particles andvertices are kept separate in a graph structure, similar to the physics event. Theevent data can be accessed by the utilisation of iterators supplied with the package.

3.3. CMSSW

After the event generation, the detector signal of the particle collision has to besimulated. The CMS collaboration developed a software package with the possi-bility to control all parts of the event analysis. This framework is called CMSSW[31]. It includes interfaces for multiple MC event generators which provide theHadronic Final State of an generated event. There are several templates for differ-ent processes which can be easily modified for own requirements. The events aresaved in the HepMC [30] format stored in Root-files. In the next step the detectorsimulation process the detector response. Finally, CMSSW provides services fordigitisation and reconstruction of physics objects.

3.3.1. Event Data Model

CMSSW uses the concept of the Event Data Model (EDM), a C++ object containerfor all raw and reconstructed data. In every step of the detector simulation it ispossible to access all available data of an event. All objects in an event are storedin a tree structure in ROOT files, and can be directly displayed by Root via abrowser application.

The design of the EDM allows a reduction of the data to high level physics ob-jects. This procedure, also called “skimming”, has the advantage to use only afraction of the primary storage space and thereby to speed up the analysis due tothe faster data access, see Fig. 3.2. CMSSW provides several data formats whichinclude different sets of information pertaining to a physics event. The RECO dataformat combines all information available on the measured particles as well as onhigh-level physics objects like jets, tracks or missing energy. Often analysis tasksneed only higher level physics objects and the AOD (Analysis Object Data) formatcan be used. It is only a subset of the RECO data format and contains eventquantities which are important for a typical analysis job.

26

3.3. CMSSW

AOD

RECO

● reconstructed hits● particle candidates● digis

● reconstructed muons● reconstructed jets● missing transverse energy

AOD

RECO



AOD

RECO



AOD● reconstructed muons● missing transverse energy

jet eta1 2.12 2.33 1.94 1.9

skimming

analysis



Figure 3.2: The skimming process reduces the original RECO data to high-level physics objects which are needed for the analysis. This procedure reducesstorage space and minimise the execution time. The final output of the analysisconsists of histograms or n-tuples.

3.3.2. Modular Architecture

The modular structure of the CMSSW framework makes is possible to activateor deactivate the desired modules and change their settings in a very simple way.Every module fulfils a special function in the simulation (e.g. source, pile-up, jetalgorithms). The complete setup of the event simulation has to be configured in aspecial file which is read by the CMSSW executable cmsRun. The current version ofCMSSW only supports configuration files written in the script language Python[32].

The user has the possibility to control the settings of the modules via changingthe parameter sets in the configuration file. After parsing the configuration file,the CMSSW framework loads all necessary modules.

There are six types of dynamically loadable processing modules, whose interfaceis specified by the framework:

� In the first part of the configuration file, the Source module has to be con-figured to provide the events. Several interfaces allow using MC event gen-erators to produce the MC events on the fly. Of course it is also possible toload already generated events from Root files. Later, with the experimentin operation, also the data acquisition systems will be an input source.

� Filter modules can be used to pass or reject events with special properties.

27

3. Software Tools

� Producer modules allows the creation and addition of new reconstructedobjects to the event.

� The final analysis is done by Analyzer modules which can be used to createhistograms or ntuples (collections of quantities).

� Looper modules control ’multi-pass’ looping over an input data.

� The OutputModule stores the output to external files defined by the stan-dard CMS Root format.

3.3.3. Simulation

The simulation of the detector response uses an realistic description of the detectorgeometry based on Geant 4 [33], a software package which simulates the interac-tion of particles with matter by means of Monte Carlo methods. The simulatedpassage of the particles in the detector material yields hits, which are digitised. Theresulting detector signal is processed by standard reconstruction algorithms to formhigher-level physics objects. Pile-up background from the same bunch-crossing aswell as from other bunch-crossings is also taken into account. Due to the modularlayout of the CMSSW framework, it is very simple to modify detector componentsand their performance, respectively.

Alternatively, a fast simulation (FastSim) is available which reduce the simula-tion time, by using shower parameterisation for the particles. As a result of thissimplification the trajectories of the particles get smeared. Therefore, FastSimcannot keep up with the precision of the full simulation.

3.3.4. Jet Algorithms

Due to the confinement in QCD, the outgoing colour-charged partons produce colli-mated streams of colour-neutral hadrons. To find a relation between the energeticparton from the hard process and the measured particle flow, it is necessary tointroduce a high-level object, the so-called jet. An ideal jet consists of all par-ticles which originate from the same parton. The analysis of jet observables liketransverse momentum and rapidity allows the estimation of the original partonquantities. Various jet algorithms provide the clustering of the particles with dif-ferent approaches. However, a perfect mapping of all measured particles to thesource parton is impossible.

Available jet algorithms can be subdivided into two classes. Cone type algorithmsform a fixed cone in the η-φ-space under special rules. The created cone collects allparticles inside a jet. Cluster algorithms pursue another strategy. The importantquantity for the clustering procedure is the four-momentum distance between twoparticles. The algorithms group the particles iteratively beginning with the pairwhich has the smallest distance. One example of such an cluster algorithm is thekT -algorithm [34] implemented in CMSSW.

28

3.3. CMSSW

The physics analysis in this diploma thesis is based on a cone type jet algorithmcalled SISCone. The following subsections describe the general problems of thecone type approach and introduce the SISCone algorithm.

Infra-Red and Collinear Safety

A robust cone type jet algorithm has to meet special requirements. Primarily theclustering procedure has to be infra-red safe. This means the jet configurationshould not be changed by low energetic particles, as shown in Fig. 3.3. Suchsoft particles can be produced by soft gluon radiation, hadronisation or pile-up. Asolution of the infra-red unsafe behaviour could be the implementation of thresholdsfor the energy of the particles which are considered as seeds.

two jets found one jet found

Figure 3.3: Infra-red unsafe behaviour: The left picture shows a configurationwith two jets. The picture on the right hand side shows how the addition ofa soft particle leads to a new interpretation of the particle flow and a changedjet configuration respectively [22].

Additionally, the seed finding procedure should also take account of the collinearunsafe behaviour. Fig. 3.4 illustrates the difficulty of finding jet seeds if an effectualenergy for a seed particle is distributed between two split collinear particles. As aresult of one missing seed candidate, the algorithm is not able to form a jet.

Iterative Cone Algorithm

At this point, the Iterative cone algorithm is introduced to give an idea how conetype algorithms work in general. In the first step, the most energetic particle istaken as a seed and all objects inside a cone with the radius

∆R =√

(∆η)2 + (∆φ)2

in the η-φ-space form a so-called proto-jet. Direction and energy of the new createdproto-jet are defined by the ET recombination scheme:

29

3. Software Tools

no jet found jet found

Figure 3.4: Collinear unsafe behaviour: The picture on the left hand sideshows two particles which are below the threshold to act as a seed. In the rightpicture, the jet can be formed around one particle with the same energy [22].

ET =∑

i

EiT η =

1ET

∑i

EiTηi φ =

1ET

∑i

EiTφi

The direction of the proto-jet is taken as a new seed for the next iteration. Theprocedure continues until a defined ending criterion like a minimal change of theproto-jet axis. At the end of the iteration, the stable proto-jet is the result for anew jet. To find the next jet, each object from the previous founded jet has tobe removed. As explained before, the seed based approach of the Iterative conealgorithm has an infra-red and collinear unsafe behaviour.

SISCone Algorithm

To avoid the mentioned difficulties, the Seedless Infrared-Safe Cone (SISCone) jetalgorithm was developed. This algorithm works with pairs of particles instead ofsingular particle seeds. Between each pair, with a distance smaller than the givenjet size ∆R, a circle is formed. Both particles have to lie on the circumference.In the next step the corresponding proto-jet is checked for stability. After theidentification of all stables proto-jets in an event, it has to be ensured that thereare no overlaps. Therefore splitting and merging routines go through all createdproto-jets, starting with the hardest one. If there is an overlap with another proto-jet, the fraction of the transverse energy decides the further processing. If this isbelow a defined threshold (splitting parameter Esplit), the objects are reassigned tothe nearest proto-jet in the η-φ-space. Otherwise, the two proto-jets are merged.The remaining proto-jets are the final jets in the event.

30

4. The Worldwide LHC Computing Grid

Particle Collider experiments in modern high energy physics have to deal withhuge data rates. The projected data output of the CMS detector [35], after thereduction by the trigger system, is still in the order of hundreds of Megabytes persecond which corresponds to several Petabytes per year. Furthermore, it is essentialfor scientists all over the world to generate and analyse corresponding Monte Carlosamples to compare expected results with real data from the detector.

The requirements concerning the computing power and storage space led to thedecision by the LHC community to build a network of computing centres whichis called Worldwide LHC Computing Grid (WLCG) [36]. Therefore, storage ele-ments and processing power from different computing clusters have to be organisedto provide a working environment for an international collaboration. The distri-bution of certain parts of the WLCG reflects the contribution of the participatinginstitutions. Every integrated computing centre provides standardised interfacesand software environments for the WLCG so that the work load can be distributedequally on all available sites.

4.1. Structure of the WLCG

The WLCG has a hierarchical structure composed of four layers. The data acquisi-tion system of each LHC experiment has direct access to the Tier-0 at CERN, thecentral root tier of the WLCG. It stores the raw signal data on tape and simultane-ously performs a first reconstruction. In the next step, raw and reconstructed datais copied to Tier-1 sites via fast broadband connections with a data rate of severalhundreds of Megabytes per second, resulting in a distributed backup of the origi-nal data samples. Furthermore, Tier-1 centres are responsible for reconstruction,calibration, skimming, reprocessing and other I/O intensive tasks.

The next subordinate level consists of multiple Tier-2 centres which mainly con-tribute computing power for miscellaneous tasks such as Monte Carlo simulationsand user analyses. Tier-2 centres provide limited disc space and have typically notape archiving. Therefore, they depend on connections to Tier-1 centres for accessto large data samples and the possibility to store the produced data.

The last element in the hierarchy are Tier-3 centres which normally have a lowercomputational power than the upper grid layers. Most of them are operated byinstitutes or smaller research groups and can be used for Monte Carlo productionor interactive analyses.

Corresponding to the definition of tasks, one further issue is important for thecategorisation of each computing centre in the hierarchy. Every site has to fulfil a

31


service level agreement which depends on the Tier status in the WLCG. A Tier-1 centre has to provide an average availability between 98% and 99% [37]. Thiscorresponds to a maximum downtime of 4 days. Service interruptions have to besolved within a few hours. Tier-2 centres have lower obligation, their guaranteedavailability is fixed at 95% [37]. To ensure that the sides comply their conditions,monitoring systems are necessary to detect failures as fast as possible.

Uni/LabUni/Lab Uni/Lab

CC-IN2P3France

ASGCTaiwan

CNAFItaly

FNALUnited States

GridKAGermany

RALUnited Kingdom

PICSpain

NDGFNordic European

Countries

Uni/Lab

Uni/Lab

Uni/Lab

Uni/Lab

Uni/Lab

Uni/LabUni/Lab

Uni/Lab

Uni/Lab

Tier 0

Tier 1

Tier 2/3

RWTH Aachen

Uni Hamburg

Uni Karlsruhe

DESY

Uni/Lab

Figure 4.1: Structure of the WLCG with the central Tier-0 at CERN. All Tier-2 sites are able to access data from every Tier-1 site which is not shown in thisdiagram [38].

4.2. Workflow of the WLCG

Users, with the permission to use the WLCG, are able to access all computingresources and data samples via standardised interfaces. The authentication on theWLCG is realised by using a Public Key Infrastructure (PKI). The user has apair of public and private keys conform to the X.509 standard [39]. To get thispair, the user has to register by requesting a digital certificate from one of theCertification Authorities (CA) [40] accredited by the WLCG. After the identityof the user is verified, the public key is signed by the CA and sent back withadditional information concerning the CA and its digital signature. The certificateherby proves the identity and opens access to the WLCG.

User groups are organised in abstract entities named Virtual Organisations (VO)which amongst others represent the different LHC experiments. The Virtual Or-ganisation Membership Service (VOMS) manages information about the roles andprivileges of users within a VO. This information is presented with the proxy cer-tificate which has to be created by the user due to the security policy. A more

32

4.2. Workflow of the WLCG

detailed description can be found in the gLite User Guide [41].The distribution of the jobs sent by the user is performed by the Resource Broker

(RB). It has access to information about the load of each site and decides whichsite is most suited to execute a job. After a jobs has finished, the output is cachedby the Resource Broker until the user retrieves it. Figure 4.2 gives an overview onthe workflow of job submission to the WLCG.

Each site has to provide special services to contribute resources to the WLCG.The Computing Element (CE) is the portal to the site’s batch system and providesthe current status of the job for other services. The received jobs are forwarded viathe local batch system to the Worker Nodes (WN) where they finally get computed.

In analogy to the CE, the Storage Element (SE) performs the mediation betweenthe WLCG and the local mass storage system. The SE manages the bookkeepingof all available data on hard disks and tape storage of a site and provides a currentfile table for other grid services.

Figure 4.2: Overview of the grid services and the jobsubmission: To submit ajob, a verified user has to access the WLCG via the “User Interface” and send a“input sandbox”, a collection of all necessary job files, to the Resource Broker.To decide where the job will be executed, the Resource Broker gets the “SE &CE Info” of all sites and forwards the job to a site which can provide capableresources and fulfil the job requirements. After the job has been completed,the user can retrieve the “output sandbox” consisting of the job results.

33


4.3. Monitoring the Grid

Complex computer systems like a Tier-1 centre within the WLCG have to fulfilspecial obligations. There are strong requirements concerning operational avail-ability, data transfer quality, storage space and a stable software environment. Toensure that downtimes of a site are as short as possible, it is necessary to implementmonitoring applications which display the current status of the system and ease thefailure detection.

One part of this diploma thesis deals with the development of a new monitoringsystem with the aim to use existing monitoring sources and correlate their results.It is designed to be a simple software framework offering an overview over theimportant information to ease the identification of errors. The prototype of thisapplication is currently monitoring the Tier-1 centre GridKa [42] and its CMSservices.

4.3.1. Available Monitoring Sources

An important issue of this work is the convenient access to the available monitoringdata from different monitoring applications. In the following, the most importantWLCG monitoring sources are described.

ARDA Dashboard: The general monitoring system for the WLCG is the ARDADashboard [43] which is hosted at CERN. It collects, stores and displaysrelevant information to users in a well defined way. Therefore, the ARDADashboard accesses multiple sources at the distributed computing systems ofthe LHC virtual organisation. It checks various activities like job processing,data management, site efficiencies and provides different types of informa-tion displays. In the following, two important dashboard applications areexplained.

The SAM (Site Availability Monitor) application runs several structuraltests on the WLCG sites in periodic time intervals. There are checkpoints forthe software availability and functionality which are verified by the output ofbasic analysis and production jobs.

The Job Summary application of the ARDA Dashboard provides detailson finished jobs. The configuration interface allows to setup different sortingalgorithms and time ranges. The output consists of plots and tables withthe corresponding values. Further information like the exit code statistics offailed jobs can also be requested.

PhEDEx CMS Data Transfers: A complex computing structure like the WLCGdepends on fast and reliable data transfers between the different grid sites.Hence a transfer monitoring application is essential to debug emerging failuresand assure the correct operation. The PhEDEx system (“Physics Experi-ment Data Export”) [44], which is responsible for all CMS data transfers, uses

34

4.4. The HappyFace Project

special software agents. They delegate the movement of files between sites,the migration of files to mass storage and the calculation of file checksums ifnecessary.

The system also provides web tools for transfer monitoring with databasequeries concerning the time range as well as source and destination. Thegraphical output displays the transfer quality in a time-dependent plot.

Site Specific Monitoring Systems: Of course, every site has its own local mon-itoring systems which provide more comprehensive information about thecomputing cluster than the central systems at CERN. Particularly, detailedinformation about the infrastructure is often only hosted at the accordingsides. Internally, the Tier-1 centre GridKa uses the host and service mon-itor application Nagios [45]. Furthermore, a script collection called USCHI(Ultra Sophisticated CMS Hardware Information System) [46] runs severalCMS specific infrastructure tests on the VOBox. Other useful informationare the fairshare values of the specific VOs or the disk / tape space usage ofthe SEs.

4.3.2. Problems of the Current Monitoring Infrastructure

A look at the current monitoring systems of the WLCG reveals numerous difficul-ties. First of all, there are too many monitoring applications providing too unstruc-tured information. For non-experts it is very hard to find out which informationis relevant or responsible for a special problem and where to find it. Furthermore,every monitoring application uses its own technology of presenting data values orgraphic output. So it is also difficult to see correlations between different possibleerror sources.

Additionally, the totality of all grid monitoring systems is uncomfortable to use.A site operator has to check a bunch of different services to access all relevantinformation. It is necessary to change the settings in the web interfaces accordingto own requirements and one has to wait for the data download. Several monitoringwebsites, especially complex systems with a database backend, often need morethan a minute to submit the settings and query the database. By this, the timerequired for a regular site check is unnecessarily increased.

4.4. The HappyFace Project - Site Specific Monitoringfrom Multiple Input Sources

To abolish these grievances it is necessary to think about a meta monitoring system,which should have special properties:

� only one website for the final output

35


– display a simple warning system for the current status of the site / theservices (traffic light logic, smileys, ...)

– collect all relevant information and their history if necessary

– load all important external plots to a cache (for faster access) and showthem in the final output

� backend for implementation of customised tests

– design tests, define rules for judging service status and triggering alerts

– correlate data from different sources

� fast, simple and up-to-date

– the complete monitoring information should be renewed about every 15minutes

– the access and loading time should be as short as possible⇒ simple structure, no complex database

– each test result should be accessible with less than three mouse clicks

– interface to the raw information from the data source

4.4.1. Functionality of the HappyFace Framework

The result of these premises is the HappyFace Project [47]. The framework iswritten in the script language Perl [48]. To allow an easy implementation of newtests and an extension of the functionality, it has a strictly modular design. Theoperation mode can be configured in the main script, where it is possible to activateand deactivate certain tests or functions. Each of these tests provides a parameterset with important variables, which can also be modified in the main script. Thefinal output is an HTML file including some javascript functions to simplify thenavigation and improve the usability. For the future, it is planned to create theoutput data in the XML format to interface with other monitoring systems.

The information display of HappyFace is divided into three main categories:infrastructure, transfer, and production. Each main category consists of multipletests. The category’s summarising status indicator is determined by the worsterror code of all its test results. In the following, the current test implementationis described.

� infrastructure:

– USCHI script collectioncheck several structural properties of the Tier-1 centre GridKa:

* mounts:check if cms production software area is mounted and available

36


* inodes:check if inodes-setting of the file system is high enough

* basic grid functionality:check the presence of the user interface commands

* FTS availability:check if all transfer channels are open

* dCache disk only buffer space:check if disk-only area of GridKa dCache is near full threshold

* dcache tape write buffer space:check if GridKa dCache tape-write buffer is filled up with preciousfiles

* basic VOBox functionality:check the presence of basic VOBox commands

* PhEDEx proxy:check the PhEDEx grid proxy validity

� transfer:

– PhEDEx Incoming / Outgoing Transfer Informationcheck the transfer quality and print error messages of failed tranfers

� production:

– SAM Visualisationcheck the results from the SAM application and provide a hyperlink tothe error report

– CMS Dashboardobserve the Job Summary Service and look after failed jobs, print statis-tics of the exitcodes

– CMS Fairshare of GridKaobserve the fraction of running CMS jobs and detect deviations from thenominal fairshare

Special sections in the final output provide different collections of important plotsfrom external sources in a cache for faster access. Hyperlinks to the data of theoriginal websites are also implemented.

The rating system consists of three states which are given in the table 4.1. Eacherror code, returned by the test modules, has a corresponding smiley face imagewhich symbolises the current status. The main category status is set according tothe worst error code of all its test results. A critical status in a specific categoryrequires an intervention of a responsible person.

The HappyFace Project requires only very basic programs and libraries com-monly available under GNU/Linux, thus it can easily run on a desktop workstation.

37


everything is fine warning status critical status no information

0 1 2 -1

Table 4.1: Rating system of the HappyFace Project: Each test module returnsan error code (−1, 0, 1, 2) which corresponds to a status symbolised by a smileyface image. The main category status is set according to the worst error codeof all its test results.

Only a mechanism for an execution in periodic time intervals, such as cronjobs, aswell as Perl have to be available. To download data from other monitoring sources,utilities like GNU Wget [49] or cURL [50] are required as well.

4.4.2. Workflow

The basic workflow of the framework is illustrated in figure 4.3. There are twoexecutable perl scripts called run.pl and plots.pl. As aforementioned the mainscript run.pl allows the configuration of the complete framework setup. It calls the“FaceFactory” module which manages the three main categories and their tests.Each test module calls the “DataFactory” to get the required data from the corre-sponding data modules. In the next step, the test modules analyse the data andsave the results in HTML fragments and ASCII text files.

To allow a different period of time for the renewal of plots, the script plots.plis executed separately. The plot modules read the result values from the savedASCII text files and create plot images. In the last step, the “HTMLFactory”module combines the HTML fragments in a pre-defined template and creates thefinal output in the form of a single, static HTML file called index.html. The exactdata flow and the according code fragments are described in the following sectionby an example.

4.4.3. Test Implementation

The framework design provides an easy way to implement new test modules to thegiven main categories. In this section, an example is described to give an idea howthe data flow is realised in the HappyFace Project. The goal is to construct a testmodule which analyses the result values from the SAM Dashboard [51]. In the firststep, a new configuration hash (a perl data structure associating keys with values)called %sam options has to be added to the main script run.pl :

# ./scripts/run.pl

38


Figure 4.3: Workflow of the HappyFace Project: The main script “run” callsthe “FaceFactory” module which starts the execution of the included test mod-ules. Each test belongs to one of the three main category modules which collectthe results of their tests for the final output. The test modules need data forthe analysis, so they call the “DataFactory” to get the data, analyse the usefulinformation and store the results into ASCII and HTML fragments. The plotmodules process the ASCII result files to create history plot images. In thelast step, the HTML fragments together with the plot images are combined bythe “HTMLFactory” module to create the final status website.

39


...%sam_options = (

"site" => "T1_DE_FZK",);...

The configuration hash is a parameter set which allows modifying the importantsettings of the test. In this example, only the site name is crucial for the testexecution. Of course, additional key-value-pairs can be integrated to provide amore detailed configuration. In the next step, the test has to be assigned to oneof the main categories done by the call of the “FaceFactory” module in the mainscript:

# ./scripts/run.pl...my $prodFace = mod::FaceFactory->new("prod",

%prodOptions =(

..."SAM" => \%sam_options,...

));...

In this case, the test is integrated in the production category and defined withthe name “SAM” and the configuration hash %sam options. The “FaceFactory”module forwards the production hash %prodOptions to the main category module“FaceProduction”. Other possible values for the initialisation of “FaceFactory” areinfra and transfer which correspond to the main category modules “FaceInfras-tructure” and “FaceTransfer”:

# ./scripts/mod/FaceFactory.pm

package mod::FaceFactory;

use mod::prod::FaceProduction;use mod::trans::FaceTransfer;use mod::infra::FaceInfrastructure;

sub new {my $self = shift @_; my $type = shift @_;

my %options = @_;my $face;

# initialise the module according to the main categroy

if ($type eq "prod") {

40


$face = mod::prod::FaceProduction->new(%options);} elsif($type eq "transfer"){

$face = mod::trans::FaceTransfer->new(%options);} elsif ($type eq "infra") {

$face = mod::infra::FaceInfrastructure->new(%options);}

return $face;} 1;

The test modules together with the related main category module have to bestored in the corresponding directories:

� ./scripts/mod/infra

� ./scripts/mod/trans

� ./scripts/mod/prod

To make the test available for the framework, the test module has to be includedvia the use-command in the main categroy module:

# ./scripts/mod/prod/FaceProduction.pm

package mod::prod::FaceProduction;

use mod::prod::FaceSAM;...

sub new {...}

sub collectResults {...}

sub createHTMLFragment {...}

For the initialisation of the test, the new-function forwards the pre-defined con-figuration hashes to the test modules. The collectResults()-function executesall included tests and returns the status for the complete category. In the laststep, the createHTMLFragment()-function of the main category module collectsthe HTML output fragments of the test modules and combines them to one singleHTML fragment. The complete source code of the “FaceProduction” module canbe seen in Appendix B.

Each test module has the same well-defined structure with a fixed new-function,which initialises the test, and two further functions (createHTMLFragment() and

41


result()) for executing the analysis and for creating the output. The initialisa-tion allows to access the configuration hash inside the test module with a simple$self->{’key’} command.

# ./scripts/mod/prod/FaceSAM.pm

package mod::prod::FaceSAM;

sub new {$self = shift @_;my %options = %{shift @_};my $face = {%options};

bless $face, $self;return $face;

}

To get the essential data, the result()-function calls the DataFactory module.At this point, the forwarded site value defined at the beginning is used. The socreated multiple level hash %dataSam stores the data. The knowledge of the datastructure is presupposed to define correct variables. More details about the dataextraction and its access are described in the next section. The following analysiscode corresponds to the test logic and gives an idea how the Perl syntax has to looklike. In this case a simple if-clause checks the second test error value of the thefourth computing element of GridKa. At the end, every test module has to defineand return a status value ($facevalue = -1,0,1,2). Furthermore, the results aresaved into an ASCII file ./results/sam results.txt.

sub result {my $self = shift @_;my $facevalue = -1;

$dataSam = mod::DataFactory->new("SAM", %options = ("site" => $self->{’site’},

));

open(SAM_RESULTS, ">../results/sam_results.txt");

######## insert "analysis code" ########...my $CEs = $dataSam->{’data’}{’item’}{’Services’}{’item’}[0];my $SEs = $dataSam->{’data’}{’item’}{’Services’}{’item’}[1];...my $Computing_Element_4 = $CEs->{’ServiceNames’}{’item’}[3];...if ($Computing_Element_4->{’Tests’}{’item’}[1]{’Status’} == ’error’) {

$facevalue = 1;

42


} else { $facevalue = 0; }...########################################

print SAM_RESULTS "facevalue\t=\t",$facevalue,"\n";print SAM_RESULTS "site\t=\t",$self->{"site"},"\n";

close(SAM_RESULTS);

$self->{’facevalue’} = $facevalue;return $facevalue;

}

The createHTMLFragment-function simply loads the results from the saved ASCIIfile and creates a HTML fragment with the name (./HTMLFragments/SAM HTML).In the case of no available information ($facevalue = -1), the HTML fragmentwould be empty. The content of the fragment has to be self-contained to be pastedbetween the <body> </body> tags of the output template. The integration of theHTML fragment to the final output is done automatically by the framework.

sub createHTMLFragment {$self = shift @_;

# laod the the results and store them in the hash %dataopen(SAM_RESULTS, "../results/sam_results.txt");while(<SAM_RESULTS>) {

chomp;next unless length;my ($var, $value) = split(/\s*=\s*/, $_, 2);$data{$var} = $value;

}close(SAM_RESULTS);

# create HTML fragmend for the final outputopen(SAM_HTML, ">HTMLFragments/SAM_HTML");if ($self->{"facevalue"} != -1) {

####### insert "HTML code" #############...print SAM_HTML ’ <div align="center">Site: ’,$data{"site"},’</div>’,"\n";print SAM_HTML ’ <div align="center">Result: ’,$data{"facevalue"},’</div>’,"\n";...########################################

}close(SAM_HTML);

}

The last part of the main script defines a hash called %html options. In the sameaction, the main category modules execute the tests via the collectResults()-function and return their status (see Appendix B). After that, the createHTMLFragment()-

43


routines are called to create HTML fragments which include the output of all testsof a main category. Finally, the “HTMLFactory” module is started with the re-quired information to compose the fragments to one single HTML output file.

# ./scripts/run.pl...%html_options = (

"production_face" => $prodFace->collectResults(),"transfer_face" => $transferFace->collectResults(),"infrastructure_face" => $infraFace->collectResults(),"cached_plots_standard" => 1,"cached_plots_shift" => 1,

);

$prodFace->createHTMLFragment();$transferFace->createHTMLFragment();$infraFace->createHTMLFragment();

mod::HTMLFactory->createHTMLFile(%html_options);

4.4.4. Data Extraction and Access

An important premise to realise a meta monitoring systems, which depends onother sources, is the ability to access the external monitoring information in a well-defined way. The XML protocol [26] is well suited for such purpose. It defines ahierarchical structured format for ASCII text files. Script languages like Perl [48],Python [32] or Ruby [52] already provide modules to parse XML files with thestandard installation. As a result of the dynamically extendable structure and thestrict rules of the XML format, the user is able to program algorithms with verysimple access routines.

A typical XML code fragment has the following structure:

<jobsummary><summaries>

<item><name>production</name><terminated>180</terminated><app-succeeded>52</app-succeeded>...

</item></summaries>

</jobsummary>

There are several modules implemented in Perl, which are able to parse the XMLcode and export a multiple level hash consisting of the data. The correspondinghash to the above code example would be:

44


$VAR1 = {’summaries’ => {

’item’ => {’production’ => {

’terminated’ => ’180’,’app-succeeded’ => ’52’,...

To access the information, the user has to follow the hash structure and definethe according variables:

$term = $dataHash->{’summaries’}{’item’}{’production’}{’terminated’};$succ = $dataHash->{’summaries’}{’item’}{’production’}{’app-succeeded’};

In the HappyFace framework, every data module has to be available in the di-rectory ./scripts/mod/data and must be included in the “DataFactory” module.The forwarding of parameter hashes is also supported. The source code of the“DataXMLParser” module can be seen in Appendix B. It needs two parameters,a URL for the XML source and a destination file for the downloaded XML code.It returns a multiple level hash consisting of the parsed information.

# ./scripts/mod/DataFactory.pm

package mod::DataFactory;

use mod::data::DataSam;use mod::data::DataXMLParser;...

sub new {my $self = shift @_;my $type = shift @_;

my %options = @_;my $data;

if ($type eq "SAM") {$data = mod::data::DataSam->new(%options);

} elsif ($type eq "XMLParser") {$data = mod::data::DataXMLParser->new(%options);

} elsif ...

return $data;} 1;

45


Of course, there are also monitoring services which do not have an XML interface.However, it is not advisable to parse the HTML code of the website, in such casesas even small changes in the website layout result in failures of the test. Therefore,compromises with the administrators of the monitoring sources should be found.To provide access in another way, e.g. via a database access, simple text files whichare easier to parse or cronjobs with the permission to copy internal log files.

4.4.5. History Plots

Besides the main category sections in the final output, there are also special sectionswhich provide external plots stored in a cache. These collections are generated bythe cache modules which are themselves managed by the “CacheFactory” module.The possible inclusion in the final output is done by the “HTMLFactory” module.

To provide own history plots without a complex database system, the applica-tion RRDtool (Round Robin Database Tool) [53] is used. This application canbe executed via the command line to create a new database, update an existingdatabase or produce the corresponding plot images which can be linked in theHTML templates of the test modules. One advantage of RRDtool in comparisonwith a relational database system is the higher time resolution of recent data. How-ever the number of input variables and the time ranges have to be defined beforethe creation of the database leading to a runtime optimised system with a verysmall fixed database size.

The plot modules, which use the RRDtool, are managed by the second executablefile plots.pl and are stored in the directory ./scripts/mod/plots. To access the data,the plot modules can readout the results from saved ASCII files or call themselvesdata modules to get recent values.

4.4.6. Conclusion & Outlook

The current source code of the HappyFace Project is managed by the revisioncontrol system subversion [54] on the EKP Trac Server [55], which also provides awiki system with an updated description and an installation guide.

The HappyFace Project has been successfully used by less-experienced shiftersduring important stress test phases of the Tier-1 centre GridKa. Meanwhile otherGerman institutes which are part of the WLCG started to implement their ownversion. The RWTH Aachen [56] already uses an implementation for productivemonitoring of its Tier-2 centre. DESY [57] and the University of Gottingen [58]are in development stage, whereas Gottingen is porting the framework in the scriptlanguage Python.

In the future, there is the aim to introduce a more complex decision-makingsystem, which is able to detect failures and trigger alerts automatically. Such testalgorithms have to be developed in close collaboration with the site administra-tors. Furthermore, there are suggestions to create a history system to store thecomplete status of the site into a database. The long-term planning comprehends a

46


standardised XML output for all supported WLCG centres, which use this softwareframework, to see quickly the current availability status of each site and the WLCGrespectively allowing nationwide shifts.

47


48

5. Analysis

5.1. Introduction

As mentioned in chapter 2, one of the main tasks of the CMS experiment is thesearch of the Higgs boson, the last undiscovered Standard Model particle. Due tothe low cross-section and high background rates, the LHC accelerator will have tobe in operation for several years to make a discovery possible. To reach a significantsignal over background ratio, discovery studies must minimise background eventsby applying techniques like kinematic cuts or combinatorial approaches.

As the branching ratio for the Higgs boson depends heavily on its mass, differentscenarios must be taken into account. One promising channel is the vector bosonfusion process with a relative clear signal structure which is suitable to find a Higgsboson in a low mass range (114 GeV . mH . 166 GeV).

Before the CMS detector starts to take data, Monte Carlo studies have to bedone to estimate the Hadronic Final State (HFS) of the collision, containing allmeasurable particles. To verify the theory, the detector response simulation basedon the HFS has to be compared with real data.

This analysis deals with a comparison of the matrix element generators Vbfnloand Pythia in combination with the showering and hadronisation routines of Her-wig++ and Pythia for a specified vector boson fusion process.

5.1.1. Event topology of H → τ+τ−

In the inelastic proton scattering with a center-of-mass energy of 14 GeV at theLHC, two partons of the incoming protons collide directly in the hard interaction,also called the hard process. One possible reaction, taking place through the colli-sion, is the vector boson fusion process pp → Hjj → τ+τ−jj, investigated in thisthesis. The Higgs boson in this channel is created through a fusion of two W± orZ0 vector bosons which are radiated by two incoming partons. The final state ofthe parton level contains the two scattered partons, and the decay products of theHiggs boson, in that case two taus, see Fig. 5.1.

Since only a fraction of the partons’ momentum is transferred, they are stilldirected in the forward region, each of them in opposite hemispheres. Their largeinvariant mass and the distinct separation in the η-φ-plane can be used successfullyto select H → ττ events and to supress the contribution of other channels.

As the outgoing partons carry a colour charge, they create new quarks out of thevacuum. The following hadronisation process creates colour neutral particles whichfinally interact with the detector material and can thus be measured. The decays

49

5. Analysis

Figure 5.1: Feynman graph of a Higgs boson created by vector boson fusiondecaying into two taus.

of the both taus from the hard interaction can be grouped in three categories: inthe fully leptonic mode, both taus decay into a muon or an electron, while in thesemi-leptonic channel one of the taus and in the fully hadronic channel both tausdecay into hadrons and result in jets in the tau direction.

Due to the lack of colour flow, the central region exhibits a reduced hadronic ac-tivity. However, additional jets can be created by numerous other effects, describedby an underlying event model. First of all, coloured or electrically charged par-ticles radiate. The radiation products are collected to the Initial and Final StateRadiation (ISR / FSR), according on whether the radiation happens, before orafter the hard interaction. Furthermore, the remaining partons from the protons,which are not involved in the hard process, can also interact via gluon exchange.This process, called Multiple Parton Interaction (MPI), is very complex and notwell understood. The MC generators used for this task provide different modelsfor MPI, see Pythia manual [59] and Herwig++ manual [60]. The final state ofthe particle level contains besides the two tagging jets, the tau decay products andfurther jets from parton shower and underlying event.

Jets with a high transverse momentum in the central region complicate the cor-rect classification of the event. The implementation of a central jet veto, whichexcludes events with a hard central jet, would improve the fraction of the desiredsignal events.

5.1.2. Data Samples

This study compares five data samples on parton and generator level for the vectorboson fusion process pp → Hjj → τ+τ−jj. The hard interaction is calculated atleading order (LO) with a Higgs boson mass of mH = 120 GeV.

A reference sample (“pure pythia”) was generated by utilising Pythia for bothmatrix element calculation and generation of the Hadronic Final State (see alsoAppendix C.1). It is comparable to the official sample from the “Computing,Software Analysis Challenge 2007” (CSA07) [61] (see also Appendix D.3). Theother four data samples are based on the matrix element generator Vbfnlo for

50

5.2. Parton Level

the parton level (see also Appendix C.2). For two of these samples showering andhadronisation were performed by Pythia. The other two samples used Herwig++for this task. Both generators provide in each case a configuration with and withouta support of MPI. From here on, the data samples without MPI are denoted as“without underlying event (UE)”. A summary of all five samples can be found inthe Table 5.1.

sample name MEG SHG MPI colour number of events

“pure pythia” Pythia Pythia yes red 9.000.000“pythia” VBFNLO Pythia yes blue 8.000.000“herwig++” VBFNLO Herwig++ yes green 8.000.000“pythia without UE” VBFNLO Pythia no violet 8.000.000“herwig++ without UE” VBFNLO Herwig++ no green-blue 8.000.000

Table 5.1: Overview of the used data samples. There are 5 combinations ofdifferent matrix element generators (MEG) and showering and hadronisationgenerators (SHG) and their underlying event (UE) settings concerning theenabled or disabled Multiple Parton Interaction (MPI). The according coloursare used for all upcoming figures.

In order to use the hard process created by Vbfnlo for the generation of theHadronic Final State, the kinematic proporties of the particles from the hard inter-action are saved into files discribed by the Les Houches Accord (see Appendix A).In the next step the LHE Interface [62] and the ThePEG Interface [63] forwardsthe stored data to Pythia and Herwig++.

In contrast to the “pure pythia” sample, the Vbfnlo based samples have re-stricted phase space conditions concerning the pseudo-rapidity, transverse momen-tum, energy and the invariant mass of the particles from the hard process. Theseapplied cuts are softer than the final cuts which are imposed on all data samplesfor the comparison. The initial restriction helps to minimise the number of eventswhich would be rejected by the final cuts. The complete configuration of these softVbfnlo cuts can be found in Appendix C.2.2.

5.2. Parton Level

The first step in the event topology is the hard interaction of the colliding par-tons. The kinematic properties of the outgoing particles from the hard process arecalculated via perturbation theory. In the introduced data samples for this studymatrix element routines of Pythia and Vbfnlo are used. To ensure that bothMC generators perform the same calculation, a comparison of the parton level be-tween the “pure pythia” reference sample and the four Vbfnlo samples, based onthe same hard process events, is done. To compare all five data samples, commonvector boson fusion (VBF) cuts (see also [64]) are imposed on the particles from

51

5. Analysis

the hard interaction. The first requirement on the outgoing quarks is:

pT ≥ 20 GeV

The choice of a maximum pseudorapidity of the quarks is made in order to keepthe sensitivity threshold of the resulting jet rapidity measurement of the detector:

|η| ≤ 4.5

To get a clear vector boson fusion signal, the two tagging jets, originated from theoutgoing quarks, have to exhibit a rapidity gap and be directed in opposite detectorhemispheres. Therefore, the quarks have to fulfil:

|η1 − η2| ≥ 4 η1 · η2 < 0

Additionally, a cut on the invariant mass of the two outgoing quarks is imposed tosuppress background from QCD processes:

Mq1,q2 ≥ 600 GeV

The two taus, which are the leptonic decay products of the Higgs boson, are requiredto lie in the central region of the detector. They also have to be energetic enoughto be measured:

|ητ | ≤ 2.5 pT,τ ≥ 20 GeV

Furthermore, taus and jets should be well resolvable, so the taus have to lie betweenthe two tagging jets and exhibit a minimum separation from the quarks in the η-φ-plane:

η1 ≥ ητ ≥ η2 ∆Rq,τ ≥ 0.6

Events, matching these requirements, are accepted as vector boson fusion events.Due to the preconditions, the Vbfnlo samples exhibit a greater fraction of acceptedVBF events, see Table 5.2

The normalised distribution of the pseudorapidity, shown in Fig. 5.2, exhibita good agreement between the “pure pythia” sample and the four Vbfnlo basedsamples. The corresponding ratio plot, Fig. 5.3 uses the “pure pythia” sampleas reference. Only the outer regions of the pseudorapidity distribution have smalldeviations. The large statistical uncertainties in the central region result from the

52

5.2. Parton Level

η-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02 Quarks

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE Figure 5.2: Nor-malised distributionof the pseudo-rapidity of bothoutgoing quarks onmatrix element levelwith non-visibleerror bars.

η-5 -4 -3 -2 -1 0 1 2 3 4 5

ratio

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04

1.06

1.08

1.1

Quarks

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.3: pseudo-rapidity ratio plotof both outgoingquarks on matrixelement level withthe “pure pythia”-sample acting asreference.

53

5. Analysis

sample name number of events VBF events

“pure pythia” 9.000.000 1.922.947“pythia” 8.000.000 4.610.461“herwig++” 8.000.000 4.638.175“pythia without UE” 8.000.000 4.634.100“herwig++ without UE” 8.000.000 4.643.854

Table 5.2: Overview of the number of VBF events on parton level.

limited number of events with centrally directed partons from the hard processwhich is a direct consequence of the selection criteria discribed above.

The figure of the transverse momentum distribution of the outgoing quarks, Fig5.4, is similar to the situation for the pseudorapidity distribution. The shapes agreevery well for the range between 20 GeV and 200 GeV. The deviations are in theorder of some percent, see Fig 5.5. A small slope is visible. Pythia producesslightly more outgoing partons in the higher pT range than Vbfnlo does.

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

arb.

uni

ts

0

0.005

0.01

0.015

0.02

0.025Quarks

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE Figure 5.4: Nor-malised distributionof transverse mo-mentum of both out-going quarks on ma-trix element levelwith non-visible er-ror bars.

The invariant di-mass distribution of the outgoing quarks as well as the taus andHiggs boson quantities can be found in Appendix D.1. The results have the samegood agreement like the shown η and pT distributions of the outgoing quarks here.On matrix element level, Pythia and Vbfnlo provide similar calculation results.The small deviations can be caused by deviant input parameters like α, αS or theCKM-Matrix values.

54

5.3. Particle Level

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

ratio

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04

1.06

1.08

1.1Quarks

pythia

herwig++

pythia without UE

herwig++ without UE Figure 5.5: Trans-verse momentumratio plot of bothoutgoing quarkson matrix elementlevel with the “purepythia”-sampleacting as reference.

5.3. Particle Level

After the investigation of the relevant quantities on matrix element level, a com-parison of the showering and hadronisation algorithms of Herwig++ and Pythiafollows. For this, one examines the Hadronic Final State on particle level. Theimportant quantities are streams of collimated particles which are clustered intojets using the SISCone algorithm (see 3.3.4) with the common cone size ∆R = 0.5.The VBF cuts, established in the parton level analysis, are imposed on the two jetswith the highest transverse momentum in an event:

pT ≥ 20 GeV |y| ≤ 4.5 |y1 − y2| ≥ 4 y1 · y2 < 0 Mj1,j2 ≥ 600 GeV

The requirements for the taus, which originate from the Higgs boson decay, arealso maintained. Of course, the seperation depends now on the two tagging jetcandidates instead of the outgoing quarks:

pT,τ ≥ 20 GeV |ητ | ≤ 2.5 y1 ≥ ητ ≥ y2 ∆Rj,τ ≥ 0.6

Besides the tagging jets, the third hardest jet and the hardest central jet cre-ated through underlying event and radiation have to be defined. Therefore, it isnecessary to exclude jets resulting from tau decays. An additional requirementconcerning the distance of jets and taus, coming from the hard process, allows adifferentiation of the jets:

� Tagging Jetsare the two hardest jets in pT of an event which passes the cuts.

� Tau Jetsare defined by a small distance in the η-φ-plane to the next tau from the hard

55

5. Analysis

process:∆Rj,τ < 0.2

� Third Jetis the remaining hardest jet in pT .

� Central Jetis the remaining hardest jet in pT which lies in the rapidity gap between thetwo tagging jets.

Whereas the third and the central jet can be the same one. The introduced cutsreduce the total number of events. Table 5.3 shows the number of accepted VBFevents for each data sample (also with a 3rd and a central jet).

sample name number of events VBF events with 3rd jet with central jet

“pure pythia” 9.000.000 118.890 118.888 118.492“pythia” 8.000.000 262.907 262.907 262.478“herwig++” 8.000.000 312.534 312.525 301.163“pythia without UE” 8.000.000 263.134 263.122 254.422“herwig++ without UE” 8.000.000 297.450 297.189 126.983

Table 5.3: Overview of the number of VBF events on particle level.

5.3.1. Tagging Jets

The comparison of the tagging jets does not show a large deviation. The final statesof all five data samples are very similar in their shapes. In this section all upcomingplots are normalised to the total number of accepted VBF events. Fig. 5.6 andFig. 5.7 show the rapidity distributions of the first and second hardest jet. Thecharacteristic properties from the parton level distribution of the outgoing quarksare maintained. The peaks are close to an absolute rapidity value of |y| = 3 whereasthe maxima of the second hardest jet are a little further away from the origin. Alsothe transverse momentum distributions exhibit a good agreement (see Fig. 5.8 andFig. 5.9). All five spectra peak at nearly the same pT value. The correspondingratio plots and the invariant di-mass distribution can be seen in Appendix D.2.1.

In order to test how well the tagging jets comply with the outgoing quarksat matrix element level, it is helpful to look at the distance ∆R to the nearestquark from the hard interaction, shown in Fig. 5.10 and Fig. 5.11. Most of theevents passing the VBF cuts consist of tagging jets which have a ∆R distancesmaller then 0.1. The implemented cuts provide a very good agreement of thetagging jets and the corresponding outgoing quarks. At this point first noticeabledeviations between the Herwig++ and Pythia are visible. The differences betweenthe Pythia samples are discussed in the conclusion of the next section.

56

5.3. Particle Level

rapidity-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

0.0221st Hardest Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.6: Rapiditydistribution of the1st hardest jet.

rapidity-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

0.0222nd Hardest Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.7: Rapiditydistribution of the2nd hardest jet.

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

0.022


pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.8: Trans-verse momentumdistribution of the1st hardest jet.

57

5. Analysis

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

arb.

uni

ts

0

0.005

0.01

0.015

0.02

0.025

0.03

2nd Hardest Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.9: Trans-verse momentumdistribution of the2nd hardest jet.

R to the next Quark∆0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

arb.

uni

ts

0.002

0.004

0.006

0.008

0.01

0.012


pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.10: Distance ∆R of the 1st

tagging jet to the nearest quark atmatrix element level.

R to the next Quark∆0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

arb.

uni

ts

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

2nd Hardest Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.11: Distance ∆R of the 2nd

tagging jet to the nearest quark atmatrix element level.

58

5.3. Particle Level

5.3.2. Third Jet

Beside the jets originating from the hard process, the event contains additional jets.They either originate from radiation off the outgoing partons or from the underlyingevent. The 3rd jet is investigated as representative quantity of additional jets sinceit is the most dominant one. In the following, all plots showing rapidity andtransverse momentum distributions are normalised to the total number of eventsthat previously fulfilled the requirements for a typical vector boson fusion event.

The rapidity distributions of the 3rd hardest jet, shown in Fig. 5.12, exhibitstrong deviations. Both Herwig++ data samples contain a 3rd Jet with a conspic-uous higher rapidity value in comparison to the Pythia samples.

Furthermore, one can see a much larger difference between the Herwig++ sam-ples with and without underlying event in contrast to Pythia. The absence of theunderlying event in the Herwig++ sample leads to a vastly reduced jet activity inthe central region. The same effect in Pythia is much smaller.

rapidity-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

3rd Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.12: Ra-pidity distribution ofthe 3rd hardest jetwithout a pT cut.

The transverse momentum distribution, shown in Fig. 5.13, exhibits further dif-ferences between the samples. The 3rd jets occuring in the Hadronic Final Statesafter showering with Herwig++ have, in general, a lower transverse momentumthan 3rd jets in the samples with the Pythia showering algorithm. The disagree-ment of the “pure pythia” sample (red colour) and the “pythia” sample (blue colour)which is based on Vbfnlo is quite surprising because of the exellent agreement onparton level and the same identical settings for both samples. This inconsistencyreoccurs on other following comparisons and will be discussed later.

Rapidity of the Third Jet Relative to the Tagging Jets

In order to get a more precise picture of the position of the 3rd jet with respect tothe rapidity gap spanned by the tagging jets, two new rapidity based observables

59

5. Analysis

[GeV/c]T

p0 5 10 15 20 25 30 35 40 45 50

arb.

uni

ts

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.083rd Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.13: Trans-verse momentumdistribution of the3rd hardest jet.

are introduced. The variable y∗ is defined as the difference between the rapidity ofthe 3rd jet and the mean rapidity of the two tagging jets:

y∗ = y3 −12(y1 + y2)

So the position of the 3rd jet is centred with respect to the rapidity gap. Forevents with a 3rd jet lying in the centre of the rapidity gap, y∗ is zero. If the 3rd

jet is close to the tagging jets, y∗ is around ±3, which corresponds to the rapiditydistribution peaks of the tagging jets. For a symmetric rapidity gap, the value ofy∗ complies to the effective rapidity position y3 of the 3rd jet.

The observable z∗ is a measure for the direction of the 3rd jet with respect to thetwo tagging jets:

z∗ =y∗

|y1 − y2|

This variable constitutes a normalisation of the observable y∗ on the width ofthe rapidity gap. If the 3rd jet lies inside the rapidity gap, the absolute value of z∗

is smaller than 12 and larger than 1

2 for a 3rd jet outside the gap.

The y∗ distribution is shown in Fig. 5.14. The central region of the Herwig++sample without underlying event is free of 3rd jets. This complies with the expec-tations as the radiation of the partons from the hard interaction goes in a similardirection as the tagging jets. Additional 3rd jets in the central region appear ifthe underlying event is taken into account. The Pythia samples do not show thischaracteristic difference. The distributions hardly depend on the underlying event.In general, the distributions peak in a more central region.

60

5.3. Particle Level

y*-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

3rd Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.14: y∗ dis-tribution of the 3rd

hardest jet without apT cut.

Fig. 5.15 shows the z∗ distribution for all five samples. The peaks are sharperthan in the y∗ distribution and the plot reveals the position of the 3rd jet relativeto the two tagging jets. The characteristic peaks near ±0.5 originate from theproperties of the jet finder. The existence of a jet causes the region around itselfto be free of other jets. Due to a jet finder cone size of ∆R = 0.5 and a minimumrapidity gap of |y1 − y2| ≥ 4 the minimum distance dmin to the next jet can becalculated as:

dmin =∆R

|y1− y2|=

0.54

= 0.125

z*-1.5 -1 -0.5 0 0.5 1 1.5

arb.

uni

ts

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.0453rd Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.15: z∗ dis-tribution of the 3rd

hardest jet wihtout apT cut.

A transverse momentum cut of pT,min > 20 GeV on the third jet, shown in Fig.5.16, reveals the favoured production of low pT jets by the underlying event model of

61

5. Analysis

z*-1.5 -1 -0.5 0 0.5 1 1.5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.0183rd Jet - pt20

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.16: z∗ dis-tribution of the 3rd

hardest jet with a pT

cut of 20 GeV.

Herwig++. The central region is completely free of 3rd jets after applying the cut.The differences between the Vbfnlo based Pythia samples remain unchanged.At this point, the already mentioned inconsistency concerning the pT spectrum ofPythia is visible. Also the total number of events with a hard 3rd jet decreasesmuch stronger in Herwig++ than the Pythia samples.

Conclusion

The investigation of the rapidity and the transverse momentum distributions of the3rd jet leads to interesting results concerning the differences of the five examineddata samples.

The main issue of the comparison is the difference in the rapidity distribution ofthe 3rd jet between Herwig++ and Pythia. Jets in Herwig++ lie mostly outsidethe rapidity gap. On the other hand, jets in Pythia favour a position betweenthe tagging jets. The reason for this enormous deviation has to be understood forfurther studies. One possible reason could be the Initial State Radiation (ISR) ofPythia which was investigated by Christoph Hackstein [65], see also AppendixD.4. The ISR implementation of Pythia prefers to produce central jets, a factwhich is disputable and not exhibited by Herwig++.

Another interesting outcome is the inconsistency of Pythia, which was alsofound out by Christoph Hackstein [65]. The Fortran version of Pythia seems toprovide a different result, if in contrast to a normal run a generated hard processis saved to a Les Houches file and forwarded back via the LHE Interface (see alsoAppendix D.5).

Furthermore, the underlying event model of Herwig++ exhibits a bigger dif-ference than Pythia does. The jets created by the underlying event of Her-wig++ are located in a low pT range. Therefore, a transverse momentum cut ofpT,min = 20 GeV results a central region free of hard jets.

62

5.3. Particle Level

5.3.3. Central Jet

As described above, the vector boson fusion process is characterised by a very clearsignature with two tagging jets spanning a rapidity gap. The reduced hadronicactivity in the central region can be used to suppress other channels with two jetsand two taus in the final state. One possible approach is the rejection of eventswith a jet inside the rapidity gap with a transverse momentum above a certainthreshold. In the following, this important measure will be studied. Again, thedistributions are normalised to the total number of events passing the general cutsfor the vector boson fusion channel.

The rapidity distribution of the central jet is shown in Fig. 5.17. Without acut on the transverse momentum, the three data samples with underlying eventbasically agree in their shapes. Again, the effect of the underlying event is muchlarger in Herwig++ than in Pythia.

rapidity-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

Central Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.17: Ra-pidity distribution ofthe hardest centraljet without a pT cut.

The selection of events where the central jet’s transverse momentum exceeds20 GeV, shown in Fig. 5.18, reveals the differences between Herwig++ and Pythiaand the inconsistency of Pythia.

Fig. 5.19 shows the z∗ distribution for the central jet. Without the underlyingevent model, most of the activity in the Herwig++ sample is in direction to thetagging jets, as jets only appear through radiation off the tagging jets and clusteringeffects. In the case of enabled underlying event, the central jet also tends to lieclose to the tagging jets. Again, the peaks on ±0.38 and the drop of ±0.5 canbe explained by the use of a jet algorithm with a cone size of ∆R = 0.5. Thecontribution of the underlying event model leads to more hadronic activity in thecentral region.

The distributions of the tranverse momentum, see Fig. 5.20, yield similar resultsas the study of the 3rd jet. As before, the showering and underlying event routinesof Herwig++ tend to produce central jets with a lower transverse momentum

63

5. Analysis

rapidity-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01Central Jet - pt20

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.18: Ra-pidity distribution ofthe hardest centraljet with a pT cut of20 GeV.

z*-0.5 -0.4 -0.3 -0.2 -0.1 -0 0.1 0.2 0.3 0.4 0.5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018Central Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.19: z∗

distribution of thehardest central jetwithout a pT cut.

64

5.3. Particle Level

compared to Pythia.

[GeV/c]T

p0 5 10 15 20 25 30 35 40 45 50

arb.

uni

ts

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07Central Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.20: Trans-verse momentumdistribution of thehardest central jet

As a result of the different spectra for Pythia and Herwig++, the efficiency ofa rejection of events based on the transverse momentum of the central jets differclearly (see Fig. 5.21). Due to the inconsistency of Pythia mentioned above, theresults for the Vbfnlo samples showerd with Pythia should be handled with care.

T,minVBF events passing central jet veto, p

0 10 20 30 40 50 60 70 80 90 100

cut e

ffici

ency

0

0.2

0.4

0.6

0.8

1

Central Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure 5.21: Vetoefficiency. Fractionof events which passthe central jet vetofor a given pT,min

value.

65

5. Analysis

The cut on the central jet’s transverse momentum has a much better veto effi-ciency for the Herwig++ samples than for the Pythia reference sample which iscomparable to the samples used for recent analyses of the Higgs Working Group.Depending on the showering and underlying event model that describes the realitybetter, one can impose a reasonable central jet veto with a pT,min value between10 GeV and 25 GeV to reject a large number of events contributing to the back-ground while preserving a large number of desired H → ττ events at the sametime.

66

6. Conclusion & Outlook

With the WLCG, consisting of a network of several computing centres, a newcomputing concept was introduced to handle the huge data rate of the LHC exper-iments. To minimise downtimes of the WLCG sites, the meta monitoring softwareframework “The HappyFace Project” was developed to simplify the detection oferror sources. This application makes it possible to correlate different monitoringsources and provides a quick overview on all important information concerning theoperation status of a site and its services. In the meantime other institutes of theGerman WLCG physics community use this application for the monitoring of theirown systems. On the long-term scale there is the ambition to provide a standard-ised output for all supported WLCG sites to get a global view on the availabilitystatus of each site and the WLCG respectively.

The physics analysis of this diploma thesis compared different Monte Carlo gen-erators. One of the promising channels to find a light Higgs boson in a mass rangebetween 114 GeV and 166 GeV is the vector boson fusion process with a very clearsignal structure. Different generation chains of the process pp → Hjj → τ+τ−jjwith a Higgs mass mH = 120 GeV were investigated.

A vector boson fusion process is characterised by a rapidity gap spanned by thetwo tagging jets, which result from the outgoing quarks close to the beam direction.The reduced hadronic activity in the central region is a consequence of the absenceof color flow in the hard process. For a correct event classification, the quantitiesof additional jets were studied. While the matrix element of a hard interactioncan be calculated via perturbation theory, the generation of jets on particle levelis performed by different phenomenological models, which can provide differentresults.

The first data sample, completely produced by the MC generator Pythia, actsas a reference. Four further data samples based on the matrix element generatorVbfnlo were forwarded to the MC generators Herwig++ and Pythia for gen-erating the Hadronic Final State (with and without supporting Multiple PartonInteraction).

The comparison of the kinematic properties of the particles from the hard pro-cess gives a good agreement between the matrix element calculations of Vbfnloand Pythia. The Hadronic Final State on the other hand exhibits enormous de-viations concerning the observables of additional jets, produced by the showeringand hadronisation routines of Herwig++ and Pythia. The third hardest jet ofthe event, generated by Herwig++, tends to be located outside the rapidity gap,whereas the data samples created by Pythia more often contain a third jet inside

67

6. Conclusion & Outlook

the rapidity gap. Furthermore, Herwig++ produces preferentially jets with a lowertransverse momentum value than Pythia does.

These results are important for the implementation of a central jet veto, whichrejects events with a hard jet in the central region and improves the fraction of thedesired signal events. This thesis has shown that the showering implementation ofHerwig++ leads to a much better veto efficiency than Pythia, which is the mostfrequently used Monte Carlo generator in high energy physics. A successful earlyHiggs discovery in this channel strongly depends on a realistic description of theactivity in the central region and the final choice of the Central Jet Veto. Therefore,additional studies are necessary to investigate the reasons of the differences betweenHerwig++ and Pythia. However, verification with first data from the LHC isabsolutely essential. The channel Z → µµ is suitable to compare theoretical ideaswith the reality.

68

A. The Les Houches Accord

The event files created by the matrix element generator Vbfnlo contain only thehard partonic process. The outcoming particles are quarks, gluons and the decayproducts of the Higgs boson. The next step is employing a showering and hadro-nisation generator (SHG) which generates the final state particles of an event.Therefore, an interface between the two applications has to be provided. Vbfnlouses a special XML file format which is defined by the Les Houches Accord [66].After some introductory comments, Vbfnlo provides a parameter set about thesettings and the considered processes (<init> block) followed by the event data(<event> blocks):

<LesHouchesEvents version="1.0">



<init># compulsory initialization information - HEPRUP data

</init>

<event># compulsory event information - HEPEUP data

</event>

(further <event> blocks, one for each event)

</LesHouchesEvents>

process run information: HEPRUPIDBMUP(2), EBMUP(2), PDFGUP(2), PDFGUP(2), IDWTUP, NPRUP,XSECUP, XERRUP, XMAXUP, LPRUP

The first variables correspond to the particle ID [67] (IDBMUP) of the beamparticles and their energy (EBMUP). In the case of a hadron collision, it is alsonecessary to specify the PDF sets (PDFGUP, PDFSUP). The switch IDWTUP de-fines the weighting settings for the generated events and the behaviour of the

69

A. The Les Houches Accord

SHG.After these general information, an itemisation of the different provided pro-cesses follows. Each of the NPRUP rows consists of the cross section (XSECUP),its uncertainty (XERRUP), the maximal weight (XMAXUP) and the internal iden-tifying number (LPRUP) of the process.

process event information: HEPEUPNUP, IDPRUP, XWGTUP, SCALUP, AQEDUP, AQCDUP,IDUP, ISTUP, MOTHUP(2), ICOLUP(2), PUP(5), VTIMUP, SPINUP

The first part of the <event> block contains basic information like the num-ber of particles NUP, the process ID (IDPRUP), the weight (XWGTUP), the scale(SCALUP) and the values of the coupling constants (AQEDUP, AQCDUP).This is followed by a list of the NUP particles which participate in the hardprocess vertex. Every particle is described by a parameter set containing theparticle ID (IDUP), the status of the particle (ISTUP), the mother particles(MOTHUP) and the colourflow (ICOLUP). Finally, there are some relevant phys-ical quantities like the five-momentum of the particle (PUP) composed of px,py, pz, E and minv, the invariant lifetime (VTIMUP) and the spin information(SPINUP).

The usage of the XML format has several advantages. The structure is extendablein a very simple way. The user can add additional information by creating a new tagpair (<tag> ...</tag>). Comments can also be inserted in a  blockwhich is ignored by the XML parser routines. However, the LHA specifications donot fulfil the XML document standard and a validation by the World Wide WebConsortium (W3C) [68] would fail.

70

B. The HappyFace Project - SourceCode

B.1. Main Category Module “FaceProduction”

# ./scripts/mod/prod/FaceProduction.pm

package mod::prod::FaceProduction;

use mod::prod::FaceSAM;use mod::prod::FaceFairshare;use mod::prod::FaceDashboard;

#---------------------------------------------------------------------------------

sub collectResults {my $self = shift @_;my $facevalue = -1;

my @tests;

$i = 0;foreach $key (keys %{$self}) {

$tests[$i] = $key;$i++;

}

for ($i = 0; $i < scalar(@tests); $i++) {$result_value = $self->{"$tests[$i]"}->result();if ($result_value > $facevalue) { $facevalue = $result_value; }

}

return $facevalue;}

#---------------------------------------------------------------------------------

sub createHTMLFragment {my $self = shift @_;my @tests;

open(PROD_HTML, ">../HTMLFragments/PROD_HTML");

71

B. The HappyFace Project - Source Code

$i = 0;foreach $key (keys %{$self}) {


}

for ($i = 0; $i < scalar(@tests); $i++) {$self->{$tests[$i]}->createHTMLFragment();

open($file_handle = $tests[$i], $file = "../HTMLFragments/".$tests[$i]."_HTML");while (<$file_handle>) {

chomp;print PROD_HTML "$_\n";

}close($file_handle);

}

close(PROD_HTML);

}

#---------------------------------------------------------------------------------

sub new {

my $self = shift @_;my %options = @_;my %face = ();my @tests;

$i = 0;foreach $key (keys %options) {


}

for ($i = 0; $i < scalar(@tests); $i++) {if ( $options{$tests[$i]} ) {

$module_name = "mod::prod::Face".$tests[$i];$face{$tests[$i]} = $module_name->new($options{$tests[$i]});

}}

my $face = {%face};bless $face, $self;return $face;

} 1;

72

B.2. Data Module “FaceXMLParser”

B.2. Data Module “FaceXMLParser”

# ./scripts/mod/data/DataXMLParser.pm

package mod::data::DataXMLParser;

use mod::XML::Simple;

sub new {$self = shift @_;

%options = @_;$url = $options{’url’};$fname = $options{’filename’};

$cmd = "curl -H \’Accept: text/xml\’ \’$url\’ | xmllint --format -> ../data/$fname";

system($cmd);

# open the xml source codeif (!-e $fname || -z $fname || !open(SOURCE_FILE, $fname)){

print "Nonexistent or empty or can not open for read $fname, skipping\n";my $ref = {};bless $ref, $self;return $self;

}

# load the xml source code to the string ’$source_code’$source_code = "";while(<SOURCE_FILE>) {

chop;$source_code = $source_code . $_;

}close(SOURCE_FILE);

$xml = new XML::Simple;

# parsing the XML code$ref = $xml->XMLin($source_code);

$ref = {%{$ref}};bless $ref, $self;

} 1;

73

B. The HappyFace Project - Source Code

74

C. Monte Carlo Datasets

C.1. Pure Pythia Reference Sample

The pure Pythia reference sample uses version 6.418 which is integrated in theCMSSW 2.1.8 framework, used for this production. The parameter set pythiaUESettingswhich steers the underlying event model can be found in Appendix C.1.1. Thecrucial settings defining the hard interaction can be found in the parameter setprocessParameters of the Pythia configuration in the CMSSW config file:

’PMAS(25,1) = 120. !Higgs boson mass’,’MSUB(102) = 0 !ggH’,’MSUB(123) = 1 !ZZ fusion to H’,’MSUB(124) = 1 !WW fusion to H’,’MDME(220, 1) = 1 !Higgs decay in tau- tau+’,

C.1.1. Pythia Underlying Event Tune (D6T)

# UE SettingspythiaUESettings = cms.vstring(’MSTJ(11)=3 ! Choice of the fragmentation function?’,’MSTJ(22)=2 ! Decay those unstable particles+’,’PARJ(71)=10 . ! for which ctau 10 mm+’,’MSTP(2)=1 ! which order running alphaS+’,’MSTP(33)=0 ! no K factors in hard cross sections+’,’MSTP(51)=10042 ! CTEQ6L1 structure function chosen+’,’MSTP(52)=2 ! work with LHAPDF+’,’MSTP(81)=1 ! multiple parton interactions 1 is Pythia default+’,’MSTP(82)=4 ! Defines the multi-parton model+’,’MSTU(21)=1 ! Check on possible errors during program execution+’,’PARP(82)=1.8387 ! pt cutoff for multiparton interactions+’,’PARP(89)=1960. ! sqrts for which PARP82 is set+’,’PARP(83)=0.5 ! Multiple interactions: matter distrbn parameter+’,’PARP(84)=0.4 ! Multiple interactions: matter distri parameter+’,’PARP(90)=0.16 ! Multiple interactions: rescaling power+’,’PARP(67)=2.5 ! amount of initial-state radiation+’,’PARP(85)=1.0 ! gluon prod. mechanism in MI+’,’PARP(86)=1.0 ! gluon prod. mechanism in MI+’,’PARP(62)=1.25 ! +’,’PARP(64)=0.2 ! +’,

75


’MSTP(91)=1 ! +’,’PARP(91)=2.1 ! kt distribution+’,’PARP(93)=15.0 ! +’,’PMAS(5,1)=4.8 ! b quark mass’,’PMAS(6,1)=172.3 ! t quark mass’

),

C.2. VBFNLO Based Samples

The matrix element generator Vbfnlo provides the file vbfnlo.dat for the defi-nition of the process. The complete configuration can be found in Appendix C.2.1.Below, some important settings are itemised:

PROCESS = 103 ! VBF -> Higgs -> Tau+ Tau-ID_MUF = 12 ! ID for factorization scaleEWSCHEME = 3 ! Choose scheme for electroweak parameters (1,2,3)

The option ID MUF = 12 affects a dynamical behaviour of the factorisation scaleby the momentum transfer of the exchanged W± and Z bosons. Several electroweakinterdependent observables influence the calculation. These are the masses MW andMZ of W±, Z boson, the Weinberg angle θW , the electromagnetic coupling constantg, the fine structure constant α and the Fermi constant GF . The relations are:

cos2 θW =M2

W

M2Z

e = g sin θW α =e2

4πGF =

g2

4√

2M2W

The scheme chosen by the option EWSCHEME = 3 corresponds to the Gµ scheme.The values for the boson masses and GF are set to the current experimentally foundvalues and θW , α are calculated:

cos2 θW =M2

W

M2Z

α =√

GF 4√

2MW

76


C.2.1. VBFNLO General Config File

! This is the main input file for vbfnlo

! General parameters of the calculation!-------------------------------------------PROCESS = 103 ! Identifier for process

LO_ITERATIONS = 4 ! number of iterations for LO calculationNLO_ITERATIONS = 4 ! number of iterations for real-emissions calculationLO_POINTS = 21 ! number of points for LO calculation ( = 2^..)NLO_POINTS = 21 ! number of points for real-emissions calculation ( = 2^..)

LO_GRID = "grid2" ! name of gridfile for LO calculationNLO_GRID = "grid3" ! name of gridfile for NLO calculation (real emissions)NLO_SWITCH = false ! switch: nlo/lo calculation

ECM = 14000d0 ! collider center-of-mass energyBEAM1 = 1 ! type of beam 1 (1=proton, -1 = antiproton)BEAM2 = 1 ! type of beam 2 (1=proton, -1 = antiproton)

ID_MUF = 12 ! ID for factorization scaleID_MUR = 12 ! ID for renormalization scaleMUF_USER = 100d0 ! user defined factorization scale, if MUF is set to 0MUR_USER = 100d0 ! user defined renormalization scale, if MUR is set to 0XIF = 1d0 ! scale factor xi for mu_F (not mu^2!!)XIR = 1d0 ! scale factor xi for mu_R

! Physics parameters!------------------------HMASS = 120d0 ! Higgs massTOPMASS = 172.5d0 ! Top massALFA_S = 0.118d0 ! Q.C.D. FINE STRUCTURE CONSTANTEWSCHEME = 3 ! Choose scheme for electroweak parameters (1,2,3)FERMI_CONST = 1.16639d-5 ! Fermi ConstantALFA = 7.7579519d-3 ! Q.E.D. FINE STRUCTURE CONSTANTSIN2W = 0.2312d0 ! Sin^2(theta_w)WMASS = 80.423d0 ! W massZMASS = 91.188d0 ! Z massANOM_CPL = false ! use anomalous couplings

! Parameters for the LHA event output!-----------------------------------------LHA_SWITCH = true ! Les Houches interface only for LO calculationUNWEIGHTING_SWITCH = true ! weighted/unweighted (T/F) events for LHAPRENEVUNW = 1000 ! number of events to calculate pre-maximal weightTAUMASS = true ! Include mass of the tau lepton(s) in the LHA file

77


! PDF set parameters!------------------------PDF_SWITCH = 0 ! which pdfs to use: 1 = lhapdf, 0 = hard-wired cteq (default)! choose pdfset and pdfmember here. Look at the LHAPDF manual for details.LO_PDFSET = "PDFsets/cteq6ll.LHpdf"NLO_PDFSET = "PDFsets/cteq6.LHpdf"LO_PDFMEMBER = 0NLO_PDFMEMBER = 0

! Parameters for histogram creation!---------------------------------------ROOT = false ! create root-file?HBOOK = false ! create paw-file?TOP = false ! create top-drawer file?GNU = true ! create gnu-plot script file?REPLACE = true ! replace output files?ROOTFILE = histograms ! name of root-file ( + ’.root’)PAWFILE = histograms ! name of paw-file ( + ’.paw’)TOPFILE = histograms ! name of top-drawer file ( + ’.top’)GNUFILE = histograms ! name of gnuplot file ( + ’.gp’)

78


C.2.2. VBFNLO Cuts Config File

! input file for the cut parameters

RJJ_MIN = 0.8d0 ! min jet-jet R separationY_P_MAX = 5.0d0 ! max pseudorapidity for partonsNJET_MIN = 2 ! min nb of defined jets

PT_JET_MIN = 10d0Y_JET_MAX = 5d0

RLL_MIN = 0.0d0RLL_MAX = 50.0d0RJL_MIN = 0.0d0RGG_MIN = 0.0d0RGG_MAX = 50.0d0RJG_MIN = 0.8d0RLG_MIN = 0.0d0Y_L_MAX = 2.5d0PT_L_MIN = 20d0Y_G_MAX = 1.5d0PT_G_MIN = 20d0ETAJJ_MIN = 2d0YSIGN = true ! jets #1 and #2 must have opposite sign rapidityLRAPIDGAP = true ! leptons fall inside rapidity gapDELY_JL = 0.0d0 ! min y-dist of leptons from tagging jetsGRAPIDGAP = true ! photons fall inside rapidity gapDELY_JG = 0.0d0 ! min y-dist of photons from tagging jets

MDIJ_MIN = 400.0d0 ! dijet min mass cut on tag jetMDIJ_MAX = 14000.0d0 ! dijet max mass cut on tag jet

JVETO = false ! veto jet cutsDELY_JVETO = 0.0d0 ! min veto-tag y-distYMAX_VETO = 5.0d0 ! max |y| for veto jetPTMIN_VETO = 20.0d0 ! min pT for veto jet

79


80

D. Additional Plots

D.1. Parton Level

D.1.1. Higgs Boson

η-5 -4 -3 -2 -1 0 1 2 3 4 5

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

0.022

Higgs

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.1: Normalised pseudo-rapidity distribution of the Higgs bo-son on matrix element level.

η-5 -4 -3 -2 -1 0 1 2 3 4 5

ratio

0.9

1

1.1

1.2

1.3

1.4 Higgs

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.2: Pseudo-rapidity ratioplot of the Higgs boson on matrix el-ement level.

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016 Higgs

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.3: Normalised tranversemomentum distribution of the Higgsboson on matrix element level.

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

ratio

0.94

0.96

0.98

1

1.02

1.04

1.06

1.08

1.1 Higgs

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.4: Transverse momentumratio plot of the Higgs boson on ma-trix element level

81

D. Additional Plots

D.1.2. Taus

η-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

arb.

uni

ts

0.004

0.006

0.008

0.01

0.012

0.014

0.016

Taus

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.5: Normalised pseudo-rapidity distribution of the taus onmatrix element level.

η-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

ratio

0.9

0.92

0.94

0.96

0.98

1

1.02

Taus

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.6: Pseudo-rapidity ratioplot of the taus on matrix elementlevel.

[GeV/c]T

p0 10 20 30 40 50 60 70 80 90 100

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016 Taus

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.7: Normalised tranversemomentum distribution of the tauson matrix element level.

[GeV/c]T

p0 10 20 30 40 50 60 70 80 90 100

ratio

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04

Taus

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.8: Transverse momentumratio plot of the taus on matrix el-ement level

82

D.2. Particle Level

D.1.3. Outgoing Quarks

]2diquark invariant mass [GeV/c600 800 1000 1200 1400 1600 1800 2000 2200 2400

arb.

uni

ts

0

0.005

0.01

0.015

0.02

0.025

Quarks

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.9: Normalised invariant di-mass distribution of the outgoingquarks on matrix element level.

]2diquark invariant mass [GeV/c600 800 1000 1200 1400 1600 1800 2000 2200 2400

ratio

0.92

0.94

0.96

0.98

1

1.02

1.04

1.06

Quarks

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.10: Invariant di-mass ratioplot of the outgoing quarks on matrixelement level.

D.2. Particle Level

D.2.1. Tagging Jets

]2dijet invariant mass [GeV/c600 800 1000 1200 1400 1600 1800 2000 2200 2400

arb.

uni

ts

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

1st Hardest Jet

pure pythia

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.11: Normalised invariantdi-mass distribution of the taggingjets.

]2dijet invariant mass [GeV/c600 800 1000 1200 1400 1600 1800 2000 2200 2400

ratio

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.51st Hardest Jet

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.12: Invariant di-mass ratioplot of the tagging jets.

83

D. Additional Plots

rapidity-5 -4 -3 -2 -1 0 1 2 3 4 5

ratio

0

0.2

0.4

0.6

0.8

1

1.2

1st Hardest Jet

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.13: Rapidity ratio plot ofthe 1st hardest tagging jet

rapidity-5 -4 -3 -2 -1 0 1 2 3 4 5

ratio

0

0.2

0.4

0.6

0.8

1

1.2

2nd Hardest Jet

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.14: Rapidity ratio plot ofthe 2nd hardest tagging jet

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

ratio

0.6

0.8

1

1.2

1.4

1.6

1.8

1st Hardest Jet

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.15: Transverse momentumratio plot of the 1st hardest taggingjet.

[GeV/c]T

p0 20 40 60 80 100 120 140 160 180 200

ratio

0.8

1

1.2

1.4

1.62nd Hardest Jet

pythia

herwig++

pythia without UE

herwig++ without UE

Figure D.16: Transverse momentumratio plot of the 2nd hardest taggingjet.

84

D.3. Comparison with Official Data

D.3. Comparison with Official Data

Fig. D.17 and Fig. D.18 show the z∗ distribution of the 3rd hardest jet concerningthe transverse momentum. The observable z∗ provides a better picture of therelationship between the 3rd jet and the tagging jets (see also 5.3.2) and can becalculated by:

y∗ = y3 −12(y1 + y2) z∗ =

y∗

|y1 − y2|The official data sample from the CSA ’07 production (black distribution) agrees

with the selfmade “pure pythia” samples very well.

z*-1.5 -1 -0.5 0 0.5 1 1.5

arb.

uni

ts

0

0.005

0.01

0.015

0.02

0.025

0.03 3rd Jet

pure pythia

official pythia

Figure D.17: z∗ dis-tribution of the 3rd

hardest jet.

z*-1.5 -1 -0.5 0 0.5 1 1.5

arb.

uni

ts

0

0.005

0.01

0.015

0.02

0.025

0.03

0.0353rd Jet - pt20

pure pythia

official pythia

Figure D.18: z∗ dis-tribution of the 3rd

hardest jet with a pT

cut of 20 GeV.

85

D. Additional Plots

D.4. Initial and Final State Radiation of Pyhtia 6

Fig. D.19 and Fig. D.20 show the z∗ distributions of the Initial and Final StateRadiation of Pythia for the equal process used in the analysis. While the FinalState Radiation favours the production of jets outside the rapidity gap close to thetagging jets, the jets of the Initial State Radiation are mostly located in the centralregion. This fact is not necessarily expected, since the Initial State Radiation takesplace before the hard interaction and therefore should be directed close to thetagging jets (|z∗| = 0.5).

vbf events, z*−2 −1.5 −1 −0.5 0 0.5 1 1.5 2

/ dz

*σd

0

100

200

300

400

500

600

700

800

z* zstarEntries 24452Mean 0.002872RMS 0.4554

z*

Figure D.19: z∗ dis-tribution of the Ini-tial State Radiationof Pythia 6

vbf events, z*−2 −1.5 −1 −0.5 0 0.5 1 1.5 2

/ dz

*σd

0

200

400

600

800

1000

1200

1400

z* zstarEntries 20049Mean −0.001035RMS 0.6232

z*

Figure D.20: z∗ dis-tribution of the Fi-nal State Radiationof Pythia 6.

86

D.5. Inconsistency of Pythia 6

D.5. Inconsistency of Pythia 6

The inconsistency of Pythia becomes visible, if in contrast to a normal run agenerated hard process on matrix element level (ME) is saved to a Les Houchesfile and forwarded to Pythia via the LHE Interface [62] to generate the HadronicFinal State. This misfeature was discoverd by comparing the following data samplesbased on the same process used for the analysis [65]:

� Vbfnlo (ME) → LHE file → Pythia (showering) (red colour)

� Pure Pythia (ME and showering) (blue colour)

� Pythia (ME) → LHE file → Pythia (showering) (green colour)

Fig. D.21 shows the rapidity distribution of the 3rd jet. At this point thedeviations are small. A cut on the transverse momentum, shown in Fig. D.22,results a larger difference between the “pure pythia” sample and the other twosamples, which use the LHE Interface to load the hard process.

Figure D.21: Ra-pidity distribution ofthe 3rd jet without apT cut.

Figure D.22: Ra-pidity distribution ofthe 3rd jet with a pT

cut of 20 GeV.

87

D. Additional Plots

88

List of Figures

0.1. z∗ Verteilung des dritt-hartesten Jets ohne Schnitt auf den Trans-versalimpulses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

0.2. Vetoeffizienz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

1.1. Transitions mediated by weak interaction . . . . . . . . . . . . . . . 61.2. Illustration of the spontaneous symmetry breaking . . . . . . . . . . 81.3. Different production modes for the Higgs boson . . . . . . . . . . . . 91.4. Parton density function for quarks and gluons for Q2 = 19600GeV2/c2

using CTEQ5L . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.5. Branching ratios of the main decay channels of the Higgs boson

depending on its mass . . . . . . . . . . . . . . . . . . . . . . . . . . 111.6. Decay width Γ of the Higgs boson depending on its mass . . . . . . . 121.7. Combined results from CDF and DØ analyses with an integrated

luminosity of 2.4 fb−1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.1. Schematic view of the CERN accelerator complex . . . . . . . . . . . 162.2. Overview over the CMS detector and its components . . . . . . . . . 172.3. Slice of the CMS detector . . . . . . . . . . . . . . . . . . . . . . . . 20

3.1. General Workflow of a Monte-Carlo event generator . . . . . . . . . 243.2. Workflow of the CMSSW analysis . . . . . . . . . . . . . . . . . . . . 273.3. Infra-red unsafe behaviour . . . . . . . . . . . . . . . . . . . . . . . . 293.4. Collinear unsafe behaviour . . . . . . . . . . . . . . . . . . . . . . . . 30

4.1. Tiered Structure of the WLCG . . . . . . . . . . . . . . . . . . . . . 324.2. Overview of the grid services and the jobsubmission . . . . . . . . . 334.3. Workflow of the HappyFace Project . . . . . . . . . . . . . . . . . . 39

5.1. Feynman graph of a Higgs boson created through vector boson fusiondecaying into to taus . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

5.2. Normalised distribution of the pseudo-rapidity of both outgoing quarkson matrix element level. . . . . . . . . . . . . . . . . . . . . . . . . . 53

5.3. pseudorapidity ratio plot of both outgoing quarks on matrix elementlevel with the “pure pythia”-sample acting as reference . . . . . . . . 53

5.4. Normalised distribution of transverse momentum of both outgoingquarks on matrix element level. . . . . . . . . . . . . . . . . . . . . . 54

5.5. Transverse momentum ratio plot of both outgoing quarks on matrixelement level with the “pure pythia”-sample acting as reference . . . 55

89

List of Figures

5.6. Rapidity distribution of the 1st hardest jet . . . . . . . . . . . . . . . 575.7. Rapidity distribution of the 2nd hardest jet . . . . . . . . . . . . . . 575.8. Transverse momentum distribution of the 1st hardest jet . . . . . . . 575.9. Transverse momentum distribution of the 2nd hardest jet . . . . . . 585.10. Distance ∆R of the 1st tagging jet to the nearest quark . . . . . . . 585.11. Distance ∆R of the 2nd tagging jet to the nearest quark . . . . . . . 585.12. Rapidity distribution of the 3rd hardest jet without a pT cut . . . . . 595.13. Transverse momentum distribution of the 3rd hardest jet . . . . . . . 605.14. y∗ distribution of the 3rd hardest jet without a pT cut . . . . . . . . 615.15. z∗ distribution of the 3rd hardest jet without a pT cut . . . . . . . . 615.16. z∗ distribution of the 3rd hardest jet with a pT cut of 20 GeV . . . . 625.17. Rapidity distribution of the hardest central jet without a pT cut . . 635.18. Rapidity distribution of the hardest central jet with a pT cut of 20 GeV 645.19. z∗ distribution of the hardest central jet without a pT cut . . . . . . 645.20. Transverse momentum distribution of the hardest central jet . . . . 655.21. Veto efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

D.1. Normalised pseudo-rapidity distribution of the Higgs boson on ma-trix element level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

D.2. Pseudo-rapidity ratio plot of the Higgs boson on matrix element level 81D.3. Normalised transverse momentum distribution of the Higgs boson

on matrix element level. . . . . . . . . . . . . . . . . . . . . . . . . . 81D.4. Transverse momentum ratio plot of the Higgs boson on matrix ele-

ment level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81D.5. Normalised pseudo-rapidity distribution of the taus on matrix ele-

ment level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82D.6. Pseudo-rapidity ratio plot of the taus on matrix element level . . . . 82D.7. Normalised transverse momentum distribution of the taus on matrix

element level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82D.8. Transverse momentum ratio plot of the taus on matrix element level 82D.9. Normalised invariant di-mass distribution of the outgoing quarks on

matrix element level. . . . . . . . . . . . . . . . . . . . . . . . . . . . 83D.10.Invariant di-mass ratio plot of the outgoing quarks on matrix element

level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83D.11.Normalised invariant di-mass distribution of the tagging jets . . . . . 83D.12.Invariant di-mass ratio plot of the tagging jets . . . . . . . . . . . . . 83D.13.Rapidity ratio plot of the 1st hardest tagging jet . . . . . . . . . . . 84D.14.Rapidity ratio plot of the 2nd hardest tagging jet . . . . . . . . . . . 84D.15.Transverse momentum ratio plot of the 1st hardest tagging jet . . . . 84D.16.Transverse momentum ratio plot of the 2nd hardest tagging jet . . . 84D.17.z∗ distribution of the 3rd hardest jet . . . . . . . . . . . . . . . . . . 85D.18.z∗ distribution of the 3rd hardest jet with a pT cut of 20 GeV . . . . 85D.19.z∗ distribution of the Initial State Radiation of Pythia 6 . . . . . . . 86D.20.z∗ distribution of the Final State Radiation of Pythia 6 . . . . . . . 86

90

List of Figures

D.21.Rapidity distribution of the 3rd jet without a pT cut . . . . . . . . . 87D.22.Rapidity distribution of the 3rd jet with a pT cut of 20 GeV . . . . . 87

91

List of Figures

92

List of Tables

1.1. Gauge bosons in the Standard Model . . . . . . . . . . . . . . . . . . 31.2. Fundamental particles in the Standard Model . . . . . . . . . . . . . 41.3. Branching ratios for leptonic decays of the Z0 boson . . . . . . . . . 61.4. Arrangement of leptons in multiplets . . . . . . . . . . . . . . . . . . 7

4.1. Rating system of the HappyFace Project . . . . . . . . . . . . . . . . 38

5.1. Overview of the used data samples . . . . . . . . . . . . . . . . . . . 515.2. Number of VBF events on parton level . . . . . . . . . . . . . . . . . 545.3. Number of VBF events on particle level . . . . . . . . . . . . . . . . 56

93

List of Tables

94

Bibliography

[1] W. M. Yao et al. Review of particle physics. J. Phys., G33:1–1232, 2006.

[2] Manuel Zeise. Modelling of Background from Z Boson Search at the LHC inthe Channel H → ττ , IEKP-KA/2008-10.

[3] Peter Ware Higgs. Broken Symmetries and the Masses of Gauge Bosons. Phys-ical Review Letters, 13:508-509, 1964.

[4] Christoph Hackstein. Simulation of Final States in Vector Boson Fusion,November 2007.

[5] Online parton distribution calculator with graphical display,http://durpdg.dur.ac.uk/hepdata/pdf3.html.

[6] A. Djouadi, J. Kalinowski, and M. Spira. HDECAY: a program for Higgs bosondecays in the Standard Model and its supersymmetric extension. ComputerPhysics Communications, 108(1):56–74, 1998.

[7] S. Baffioni, C. Charlot, F. Ferri, N. Godinovic, P. Meridiani, I. Puljak,R. Salerno, and Y. Sirois. Discovery Potential for the SM Higgs Boson inthe H→ ZZ(∗) → e+e−e+e− Decay Channel. CERN-CMS-Note-2006-115, J.Phys, 634:N23–N46, 2007.

[8] Ulrich Felzmann, Gunter Quast and Christian Weiser. Observability of a HeavyHiggs Boson in the Channel qqH and H→ ZZ → llqq. CERN-CMS-AN-2007-020.

[9] H. Pi, P. Avery, J. Rohlf, C.G. Tully, and S. Kunori. Search for StandardModel Higgs Boson via Vector Boson Fusion in the H → W+W− to l±νjjchannel with 120 < mH < 250GeV/c2.

[10] G. Davatz, M. Dittmar, and AS Giolo-Nicollerat. Standard model Higgs dis-covery potential of CMS in the H → WW → lνlν channel. J. Phys. G, 33,2007.

[11] LEPEWWG, http://lepewwg.web.cern.ch/LEPEWWG/.

[12] TEVNPH Working Group. Combined CDF and Dzero Upper Limits on Stan-dard Model Higgs-Boson Production.

[13] Oragnisation Europeene pour la Recherche Nucleaire (CERN),http://www.cern.ch/.

95

Bibliography

[14] ATLAS, http://atlas.web.cern.ch/Atlas/index.html.

[15] LHCb, http://lhcb.web.cern.ch/lhcb/.

[16] ALICE, http://aliceinfo.cern.ch/.

[17] TOTEM, http://totem.web.cern.ch/Totem/.

[18] CERN Communication Group. CERN FAQ LHC the guide, 2008. CERN-Brochure-2008-001-Eng.

[19] CMS Collaboration, http://cmsinfo.cern.ch/outreach.

[20] The CMS Collaboration. CMS physics : Technical Design Report, 2006.CERN-LHCC-2006-001.

[21] ROOT, http://root.cern.ch/.

[22] Michael Heinrich. The Influence of Hadronisation and Underlying Event onthe Inclusive Jet Cross-Section at the LHC. IEKP-KA/2008-11, 2007.

[23] VBFNLO, http://www-itp.particle.uni-karlsruhe.de/∼vbfnloweb/.

[24] MR Whalley and D. Bourilkov. RC Group,“The Les Houches accord PDFs(LHAPDF) and LHAGLUE,”. Arxiv preprint hep-ph/0508110.

[25] S. Kretzer, HL Lai, F.I. Olness, and WK Tung. CTEQ6 parton distributionswith heavy quark mass effects. Physical Review D, 69(11):114005, 2004.

[26] XML (Extensible Markup Language), http://www.w3.org/XML/.

[27] T. Sjostrand, S. Mrenna, and P. Skands. PYTHIA 6.4 physics and man-ual,(2006). Arxiv preprint hep-ph/0603175.http://home.thep.lu.se/∼torbjorn/Pythia.html.

[28] Herwig++, http://projects.hepforge.org/herwig/.

[29] ThePEG, http://home.thep.lu.se/ThePEG/.

[30] HepMC, https://savannah.cern.ch/projects/hepmc/.

[31] CMS Software Project,http://cmsdoc.cern.ch/cms/cpt/Software/html/General/.

[32] Python, http://www.python.org/.

[33] Geant 4, http://geant4.web.cern.ch/geant4/.

[34] J. M. Butterworth, J. P. Couchman, B. E. Cox, and B. M. Waugh. Ktjet: Ac++ implementation of the kt clustering algorithm. 2002.

96

Bibliography

[35] Compact Muon Solenoid (CMS), http://cms.cern.ch/.

[36] Worldwide LHC Computing Grid, http://lcg.web.cern.ch/lcg/.

[37] Memorandum of Understanding for Collaboration in the Deployment and Ex-ploitation of the Worldwide LHC Computing Grid,http://lcg.web.cern.ch/lcg/C-RRB/MoU/WLCGMoU.pdf.

[38] Dr. rer. nat. Volker Buge. Virtualisation of Grid Resources and Prospects ofthe Measurement of Z Boson Production in Association with Jets at the LHC.2008.

[39] R. Housley, W. Polk, W. Ford, and D. Solo. Internet X. 509 Public KeyInfrastructure Certificate and Certificate Revocation List (CRL) Profile, 2002.

[40] Certification Authorities (CA) recognised by LCG,http://lcg.web.cern.ch/LCG/users/registration/certificate.html.

[41] gLite User Guide, http://glite.web.cern.ch/glite/documentation/.

[42] GridKa, http://grid.fzk.de/.

[43] Arda Dashboard, http://dashboard.cern.ch/.

[44] PhEDEx CMS Data Transfers,http://cmsdoc.cern.ch/cms/aprom/phedex/.

[45] Nagios, http://www.nagios.org/.

[46] USCHI, https://ekptrac.physik.uni-karlsruhe.de/USCHI.

[47] HappyFace Project,https://ekptrac.physik.uni-karlsruhe.de/HappyFace.

[48] Perl, http://www.perl.org/.

[49] GNU Wget, http://www.gnu.org/software/wget/.

[50] cURL, http://curl.haxx.se/.

[51] SAM Dashboard,http://lxarda16.cern.ch/dashboard/request.py/latestresultsview.

[52] Ruby, http://www.ruby-lang.org/.

[53] RRDtool, http://oss.oetiker.ch/rrdtool/.

[54] subversion, http://subversion.tigris.org/.

[55] EKP Trac Server, https://ekptrac.physik.uni-karlsruhe.de/.

97

Bibliography

[56] RWTH Aachen, http://www.rwth-aachen.de/.

[57] DESY, http://www.desy.de/.

[58] University of Goettingen, http://www.uni-goettingen.de/.

[59] T. Sjostrand, S. Mrenna, and P. Skands. PYTHIA 6.4 physics and manual.JHEP, 5:026, 2006.

[60] M. Bahr, S. Gieseke, MA Gigg, D. Grellscheid, K. Hamilton, O. Latunde-Dada, S. Platzer, P. Richardson, MH Seymour, A. Sherstnev, et al. Herwig++Physics and Manual. arXiv, 803, 2008.

[61] Computing, Software, Analysis Challenge 2007,https://twiki.cern.ch/twiki/bin/view/CMS/CSA07.

[62] Christophe Saout. LHE Interface,https://twiki.cern.ch/twiki/bin/view/CMS/SWGuideLHEInterface.

[63] Fred Stober, Christoph Hackstein and Oliver Oberst. ThePEG Interface,https://twiki.cern.ch/twiki/bin/view/CMS/ThePEGInterface.

[64] T. Figy, D. Zeppenfeld, and C. Oleari. Next-to-leading order jet distribu-tions for Higgs boson production via weak-boson fusion. Physical Review D,68(7):73005, 2003.

[65] Christoph Hackstein, Gunter Quast and Manuel Zeise. Comparison of Pythia,vbfnlo and Herwig++ for the vector boson fusion channel, Higgs WG meeting- November 4, 2008,http://indico.cern.ch/getFile.py/access?contribId=0&resId=0&materialId=slides&confId=44199.

[66] J. Alwall, A. Ballestrero, P. Bartalini, S. Belov, E. Boos, A. Buckley, JM But-terworth, L. Dudko, S. Frixione, L. Garren, et al. A standard format for LesHouches Event Files. Computer Physics Communications, 176(4):300–304,2007.

[67] Monte Carlo Particle Numbering Scheme,http://pdg.lbl.gov/2008/reviews/montecarlorpp.pdf.

[68] World Wide Web Consortium, http://www.w3.org/.

98

Danksagung

Mein besonderer Dank gilt Herrn Prof. Dr. Gunter Quast fur die Uberlassungdes Themas sowie seine stets großzugige Unterstutzung und wertvolle Betreuung.Ebenso danke ich Priv. Doz. Dr. Wolfgang Wagner fur die Ubernahme des Kor-referats.

Mein allerherzlichster Dank gebuhrt Manuel Zeise. Seine großartige Betreuung,Motivation und eine schier unendliche Geduld mir gegenuber wahrend des gesamtenletzten Jahres machten das Anfertigen dieser Diplomarbeit erst moglich.

Den Kollegen Christoph Hackstein und Artem Trunov danke ich fur die wertvolleUnterstutzung und die enge Zusammenarbeit bei den jeweiligen Themengebietendieser Arbeit.

Ich bedanke mich weiterhin bei Dr. Volker Buge und in ganz besonderem Maßebei Michael Heinrich. Ihre Anregungen und Korrekturen waren von unschatzbaremWert. Habt vielen Dank.

Mein Dank auch an alle anderen Kollegen aus dem Buro, am FZK und am CERN:Dr. Ulrich Felzmann, Dr. Christopher Jung, Benjamin Klein, Julian Merkert, An-dreas Oehler, Oliver Oberst, Danilo Piparo, Dr. Klaus Rabbertz, Christophe Saout,Dr. Armin Scheurer, Dr. Gregory Schott und Fred Stober fur das Korrekturlesendieser Arbeit, die freundschaftliche Zusammenarbeit und die sehr angenehme At-mosphare in der Arbeitsgruppe.

Meinen Eltern danke ich fur ihre Unterstutzung und ihr Vertrauen.Simon Wendel und meinen Freunden danke ich fur die moralische Unterstutzungwahrend meines gesamten Studiums.

99

D. Danksagung

100

Hiermit versichere ich, die vorliegende Arbeit selbststandig verfasstund nur die angegebenen Hilfsmittel verwendet zu haben.

Viktor Mauch

Karlsruhe, den 17. November 2008

Universitat Karlsruhe (TH)thesis/data/iekp-ka2008...se angeben. Der LHC erweitert den...

Documents

Transcript of Universitat Karlsruhe (TH)thesis/data/iekp-ka2008...se angeben. Der LHC erweitert den...