Busqueda del bos on de Higgs en el canal H WW 2l2 en el .... Francisco Javier Cuevas Maestro,...

Universidad de Oviedo

Busqueda del boson de Higgs en el canalH→WW→2l2ν en el experimento CMS

Memoria de tesis presentada por

Lara Lloret Iglesias

para optar al grado de Doctor

Dirigida porDr. Francisco Javier Cuevas Maestro

Oviedo, Junio de 2013

Universidad de Oviedo

Search for the standard model Higgs bosonin the H→WW→2l2ν channel with the CMS

experiment

Memoria de tesis presentada por

Lara Lloret Iglesias

para optar al grado de Doctor

Dirigida porDr. Francisco Javier Cuevas Maestro


Dr. Francisco Javier Cuevas Maestro, Profesor Titular de la Universidad deOviedo

Certifica:Que la presente memoria: Busqueda del boson de Higgs en el canal H→WW→2l2ν

en el experimento CMS, ha sido realizada bajo mi direccion en el Departamento deFısica Facultad de Ciencias de la Universidad de Oviedo por Lara Lloret Iglesias, paraoptar al grado de Doctor en Ciencias Fısicas.

Y para que ası conste, en cumplimiento de la legislacion vigente, firmo el presentecertificado:


A mi familia

Contents

1 Resumen 1

2 Introduction 7

3 Standard Model Higgs Boson 93.1 The Standard Model of Elementary Particles . . . . . . . . . . . . . . . . . 93.2 The Higgs mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103.3 Higgs searches at LEP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113.4 Higgs searches at the Tevatron . . . . . . . . . . . . . . . . . . . . . . . . . 12

4 LHC accelerator, CMS detector and Physics Objects 154.1 LHC detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.1.1 A Large Ion Collider Experiment (ALICE) . . . . . . . . . . . . . . 164.1.2 A Toroidal LHC Apparatus (ATLAS) . . . . . . . . . . . . . . . . . 164.1.3 The Large Hadron Collider beauty experiment (LHCb) . . . . . . . 16

4.2 Compact Muon Solenoid (CMS) detector . . . . . . . . . . . . . . . . . . . 164.2.1 Tracker system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.2.1.1 Pixel Tracker . . . . . . . . . . . . . . . . . . . . . . . . . 174.2.1.2 Silicon Tracker . . . . . . . . . . . . . . . . . . . . . . . . 18

4.2.2 Calorimeters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184.2.2.1 Electromagnetic Calorimeter . . . . . . . . . . . . . . . . 184.2.2.2 Hadronic Calorimeter . . . . . . . . . . . . . . . . . . . . 18

4.2.3 Muon System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184.2.3.1 Drift Tube Chambers . . . . . . . . . . . . . . . . . . . . 194.2.3.2 Cathode Strip Chambers (CSCs) . . . . . . . . . . . . . . 204.2.3.3 RPCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.3 Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204.3.1 Level 1 Trigger (L1) . . . . . . . . . . . . . . . . . . . . . . . . . . 214.3.2 High Level Trigger (HLT) . . . . . . . . . . . . . . . . . . . . . . . 22

4.4 CMS computing model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224.4.1 Hierarchical architecture . . . . . . . . . . . . . . . . . . . . . . . . 224.4.2 CMSSW software . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234.4.3 T3-Oviedo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4.5 Physics Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264.5.1 Vertex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274.5.2 Muons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

ix

CONTENTS

4.5.2.1 Muon Reconstruction . . . . . . . . . . . . . . . . . . . . 284.5.2.2 Muon Isolation . . . . . . . . . . . . . . . . . . . . . . . . 30

4.5.3 Electrons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324.5.3.1 Electron Reconstruction . . . . . . . . . . . . . . . . . . . 324.5.3.2 Electron Isolation . . . . . . . . . . . . . . . . . . . . . . . 34

4.5.4 Lepton and Trigger efficiencies . . . . . . . . . . . . . . . . . . . . . 364.5.4.1 Lepton efficiencies . . . . . . . . . . . . . . . . . . . . . . 374.5.4.2 Trigger Efficiencies . . . . . . . . . . . . . . . . . . . . . . 38

4.5.5 Jets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404.5.5.1 Reconstruction algorithms . . . . . . . . . . . . . . . . . . 404.5.5.2 Clustering Algorithms . . . . . . . . . . . . . . . . . . . . 414.5.5.3 Energy Corrections. . . . . . . . . . . . . . . . . . . . . . 424.5.5.4 Bottom quark jets tagging. . . . . . . . . . . . . . . . . . 43

4.5.6 Missing Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 434.5.6.1 MVADY : A multivariate technique to reject Drell-Yan Back-

ground . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

5 SM Higgs in the WW ∗ decay channel 475.1 Higgs Phenomenology at the LHC . . . . . . . . . . . . . . . . . . . . . . . 475.2 Higgs Searches in CMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485.3 The H → WW ∗ process . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495.4 Signature of signal and background . . . . . . . . . . . . . . . . . . . . . . 495.5 LHC center of mass energy and integrated luminosity scenarios . . . . . . . 515.6 Datasets and triggers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

5.6.1 Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545.6.1.1 2011 period datasets . . . . . . . . . . . . . . . . . . . . . 545.6.1.2 2012 period datasets . . . . . . . . . . . . . . . . . . . . . 54

5.6.2 Monte Carlo Samples used in the analysis . . . . . . . . . . . . . . 545.6.3 Triggers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

5.7 Multiple interactions reweight . . . . . . . . . . . . . . . . . . . . . . . . . 56

6 Event selection and background estimation using data driven methods 596.1 Common WW selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596.2 mH dependent analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

6.2.1 Cut based analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 636.2.1.1 7 TeV analysis . . . . . . . . . . . . . . . . . . . . . . . . 636.2.1.2 8 TeV analysis . . . . . . . . . . . . . . . . . . . . . . . . 63

6.2.2 MVA analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 636.2.3 Single variable shape analysis . . . . . . . . . . . . . . . . . . . . . 66

6.2.3.1 Comparison between the different shape approaches with2011 data . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

6.3 Background estimation using data driven methods . . . . . . . . . . . . . . 696.3.1 Drell-Yan background . . . . . . . . . . . . . . . . . . . . . . . . . 696.3.2 Drell-Yan to ττ background . . . . . . . . . . . . . . . . . . . . . . 71

6.4 Top backgrounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 716.4.1 WW background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

x

CONTENTS

6.4.2 W+jets background . . . . . . . . . . . . . . . . . . . . . . . . . . . 786.4.3 ZZ, WZ and W + γ backgrounds . . . . . . . . . . . . . . . . . . . 84

7 Systematic Uncertainties 877.1 Experimental uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

7.1.1 Lepton identification efficiencies . . . . . . . . . . . . . . . . . . . . 887.1.2 Missing transverse momentum resolution . . . . . . . . . . . . . . . 887.1.3 Lepton momentum scale . . . . . . . . . . . . . . . . . . . . . . . . 887.1.4 Jet energy scale uncertainty . . . . . . . . . . . . . . . . . . . . . . 897.1.5 Electron energy resolution . . . . . . . . . . . . . . . . . . . . . . . 907.1.6 Luminosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 917.1.7 Pile-Up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 917.1.8 Uncertainties on background estimates . . . . . . . . . . . . . . . . 91

7.2 Theoretical uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . 927.3 Statistical uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

8 Results 958.1 WW production cross section . . . . . . . . . . . . . . . . . . . . . . . . . 95

8.1.1 Previous results at the LHC . . . . . . . . . . . . . . . . . . . . . . 968.1.2 WW cross section measurement at 8 TeV . . . . . . . . . . . . . . . 978.1.3 WW cross section measurement at 8 TeV in each leptonic channel . 101

8.2 H → WW results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1048.2.1 Cut based analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 1048.2.2 Single variable analysis . . . . . . . . . . . . . . . . . . . . . . . . . 111

8.3 Higgs combination: Observation of a new particle . . . . . . . . . . . . . . 119

9 Conclusions 129

10 Conclusiones 135

Bibliography 141

A Further studies using the 1D shape analysis 149A.1 Results with mT -shape analysis . . . . . . . . . . . . . . . . . . . . . . . . 149A.2 Results with 2MR-shape analysis . . . . . . . . . . . . . . . . . . . . . . . 154A.3 Results with m``-shape analysis . . . . . . . . . . . . . . . . . . . . . . . . 158

B Two Dimensional Shape Analysis 161

C WW production cross section update 171C.1 Background estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171C.2 WW cross-section measurement with the full 2012 dataset . . . . . . . . . 172

D HWW : additional material 175D.1 Shape based analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

D.1.1 7 TeV analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175D.1.2 8 TeV analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

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CONTENTS

D.2 Cut based analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178D.2.1 7 TeV analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178D.2.2 8 TeV analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

xii

1

Resumen

En esta tesis se presenta la busqueda del boson de Higgs en el canal H → WW → 2l2 que hallevado a su observacion. Los datos utilizados corresponden a toda la luminosidad recogidadurante 2011 y 2012 por el detector CMS en el acelerador LHC. El analisis que se presentaes el resultado de anos de optimizacion y estudios exhaustivos siempre adaptandose a lascambiantes condiciones y a los diferentes escenarios de CMS. Para confirmar la existenciade nueva fısica es necesario observar un exceso de al menos 5 σ. En Julio de 2012 se anunciola observacion de una nueva particula, potencialmente el boson de Higgs, con una masa dealrededor de 125 GeV/c2 con una significancia de 5 σ. Este resultado de extrema relevanciase ha logrado combinando los resultados de esta tesis con otros cuatro canales en CMS: γγ,ZZ, ττ y bb. La significancia local en el canal H → WW en el momento de la observacionpara un boson con una masa de 125 GeV/c2 era de 1.6 σ. La observacion de esta nuevapartıcula tuvo lugar a mediados del ano 2012 usando toda la luminosidad correspondienteal ano 2011 (5.1 fb−1) y 5.3 fb−1 del ano 2012. Esto corresponde a menos de la mitad dela luminosidad total recogida por CMS al final de 2012.

El resultado presentado en esta tesis corresponde a la busqueda del Higgs del modeloestandar en el canal H → WW utilizando toda la luminosidad tanto a 7 TeV como a 8TeV (unos 25 fb−1). La estrategia del analisis ha cambiado entre 2011 y 2012. Durante lamayor parte del ano 2011 el principal objetivo era reducir al maximo la ventana de masadel boson de Higgs, excluyendo el mayor rango de masa posible. Tras los primeros indiciosde nueva fısica a finales de 2011 la estrategia de analisis se modifico de cara a optimizar lasensibilidad del canal para la zona de baja masa.

El canal H → WW presenta un estado final con dos leptones aislados de alto momentotransverso (pT ) y un valor elevado de energıa transversa faltante (Emiss

T ) debido a que losneutrinos escapan a la deteccion. Los sucesos estan clasificados en tres categorıas diferentesdependiendo del numero de jets con alto pT en el estado final. Para cada categorıa lossucesos se dividen segun presenten leptones con el mismo sabor ( µµ y ee) o leptones condiferente sabor (eµ y µe). El fondo de top es reducido principalmente aplicando dos tiposdiferentes de veto al quark b: uno basado en la larga vida media de dichos quarks y otrobasado en la presencia de muones provenientes de la desintegracion del quark b (softmuons).El fondo de Drell-Yan se reduce drasticamente eliminando la ventana de masa invariantecorrespondiente a la masa del boson Z y aplicando un corte duro en la Emiss

T para los sucesoscon leptones del mismo sabor. El fondo de WW es irreducible pero puede ser controladocon una serie de cortes optimizados en funcion del valor de mH . La principal variable

1

1. RESUMEN

discriminante para reducir este fondo es el angulo entre los dos leptones seleccionados en elplano transverso. Este observable fısico tiende a ser pequeno en el caso de la senal debido acorrelaciones de spin. Los principales fondos de este analisis (W+jets, top, DY and WW)se estiman con metodos basados directamente en los datos.

La figura 1.1 muestra la significancia esperada y observada en funcion de la masa delHiggs para los analisis de 7 TeV y 8 TeV juntos.

Figure 1.1: Significancia esperada y observada para cada hipotesis de masa para el analisisa 7 TeV y 8 TeV. La lnea de puntos corresponde a la significancia esperada para la busquedade un boson de Higgs con masa mH , en presencia de un boson de dicha masa. La lınea soliday las bandas de color muestran la significancia a una masa mH en caso de que el boson deHiggs tuviera una masa de 125 GeV/c2. Los puntos muestran la significancia observada parael exceso en la busqueda del boson de Higgs con una mH .

El resultado final para el analisis a 7 TeV y 8 TeV presentado en esta tesis se haobtenido con dos selecciones diferentes: un analisis basado en cortes y otro basado en laforma (shape) de la distribucion de un discriminante unidimensional con significado fısico.La Tabla 1.2 presenta un resumen de los rangos de exclusion esperados y observados asıcomo de la significancia para la busqueda del boson de Higgs utilizando el analisis basadoen cortes.

Los resultados para el analisis usando la distribucion unidimensional de un observablefısico se obtuvieron en 2011 utilizando la forma de la masa invariante de los dos leptones(mll) al nivel conocido como N-1. Este nivel de seleccion corresponde al nivel final del

2

Figure 1.2: Lımites esperados y observados y significancia para todos los sabores leptonicosen los canales de 0 jets y 1 jet utilizando 19.5 fb−1 de datos a 8 TeV para el analisis basadoen cortes.

analisis eliminando el corte en la variable estudiada para intentar mantener todo el poderdiscriminante sin distorsionar la forma de la variable para la extraccion de la senal. Elrango de exclusion que se obtiene excluye el rango de masas [140–230] al 95% C.L. con laaproximacion bayesiana. Con el metodo CLs, el rango de exclusion es [133–230] al 95%.En ausencia de senal, el rango de exclusion esperado es [126–230] al 95% C.L (CLs).

Para el analisis usando los datos de 2012, el resultado final para el analisis unidimen-sional se obtiene utilizando la forma de la distribucion de tres discriminantes diferentes:la masa transversa (mT) , una variable de razor (2MR) y la masa invariante (mll). Lasdistribuciones se estudian a un nivel de seleccion intermedio en el que todavıa no se haaplicado ningun corte dependiente de la masa del Higgs. Se ha estudiado igualmente unaaproximacion adicional utilizando la distribucion de la masa invariante tras haber aplicadotodos los cortes del analisis pero eliminando el corte en la variable mll. La Tabla 2 resumela significancia esperada y observada utilizando la forma de distintas variables unidimen-sionales para sucesos con leptones de distinto sabor y combinando los resultados con losdel analisis basado en cortes para los sucesos con leptones del mismo sabor.

Una vez que los resultados del canal HWW se han combinado con los obtenidos por los

3

1. RESUMEN

canales ZZ, ττ , γγ y bb, se observa un exceso de sucesos con respecto al fondo esperadopara una masa en torno a 125 GeV/c2, indicando la presencia de una nueva partıcula.La consistencia de los acoplamientos del boson observado con los que predice el modeloestandar han sido estudiados y hasta el momento no se ha encontrado ninguna desviacionsignificativa. El spin de esta nueva partıcula esta siendo estudiado a su vez. El hecho de quese desintegre a dos fotones indica que la nueva partıcula es un boson con un spin distintode 1. Cuando el LHC vuelva a estar operativo en 2015 uno de sus mayores objetivos serala caracterizacion de las propiedades de este nuevo boson.

La Tabla 1.3 muestra la significancia esperada y observada utilizando los datos a 8TeV para 0 jets y 1 jets utilizando el analisis basado en la forma de la distribucion dedistintos observables fısicos para los sucesos con leptones de distinto sabor combinados conlos resultados del analisis basado en cortes para los sucesos con el mismo sabor. Todoslos resultados han sido calculados a un nivel de seleccion donde todavıa no se ha aplicadoningun corte dependiente de la mH excepto las dos ultimas columnas mll (N-1) donde ladistribucion de mll se toma a nivel final del analisis sin aplicar ningun corte en la masainvariante.

Figure 1.3: Significancia esperada y observada utilizando los datos a 8 TeV para 0 jets y 1jets utilizando el analisis basado en la forma de la distribucion de distintos observables fısicospara los sucesos con leptones de distinto sabor combinados con los resultados del analisisbasado en cortes para los sucesos con el mismo sabor.

El proceso WW es muy sensible a busquedas de nueva fısica. En particular, la pro-duccion qq → WW para el canal-s es sensible a las medidas de los TGC (Trilinear GaugeCouplings). Un exceso en la medida de la seccion eficaz de WW puede implicar la presencia

4

de acoplamientos TGC anomalos u otros procesos fısicos con un estado final similar. Elproceso WW es tambien muy importante al tratarse del principal fondo irreducible paralas busquedas del boson de Higgs en el canal H → WW .

Para la estimacion de la seccion eficaz de produccion del WW se seleccionan sucesoscon dos leptones aislados, un elevado valor de Emiss

T y que no contengan jets con altopT . La eficiencia de senal se extrae de la simulacion de Monte Carlo mientras que losprincipales fondos, al igual que en el caso del H → WW , se estiman usando metodosbasados directamente en datos. La estimacion de otros fondos menores como el WZ o elZZ , se obtiene directamente del Monte Carlo. La medida experimental de la seccion eficazde WW utilizando toda la luminosidad recogida a 7 TeV es:

σWW = 52.4 ± 2.0 (stats.) ± 1.2 (lumi.) ± 4.5 (syst.) pb

Este valor esta desviado 1 σ de la ultima prediccion teorica:

σ(WW) = 47.04 pb(

+4.3%−3.2%

)En esta tesis se ha calculado la medida de la seccion eficaz de WW utilizando una

luminosidad de 3.54 fb-1 para una energıa de centro de masas de 8 TeV La seleccion desucesos para esta medida, junto con la de la busqueda del boson de Higgs en el canal H’ WW, ha sido optimizada para hacer frente al incremento de la luminosidad instantaneaen el LHC. La seccion eficaz experimental medida con los primeros 3.54 fb−1 de los datostomados en 2012 a 8 TeV corresponde a:


Este resultado debe ser comparado con el ultimo resultado teorico a 8 TeV:

σ(WW) = 57.3(

+2.4−1.6

)pb

5

1. RESUMEN

6

2

Introduction

Among all the pieces of the Standard Model (SM), the origin of the mass of the elementaryparticles has a potential solution. By adding only one doublet of complex scalar fields,the mass of the SM elementary fermions and bosons can be explained, after spontaneouselectroweak symmetry breaking (EWSB) of the originally massless Lagrangian [1], [2], [3].This minimal approach could be confirmed if the remnant of such a breaking, the Higgsboson, is observed with the couplings and properties predicted in the SM.

Revealing the physical mechanism responsible for the breaking of the EWK symmetrywas one of the main physics goals for the Large Hadron Collider (LHC). The LHC experi-ments were built to discover the Higgs boson, closing a search that started years ago and inwhich several experiments at different colliders have been involved. The large centre of massenergies produced in proton-proton collision at the LHC together with the high luminositiesexpected have allowed the LHC to develop a physics program that will probably give thefinal answer to this search. The LHC has covered a wide range of Higgs searches, fromthe minimal SM Higgs, to beyond the SM through the Minimal Supersymmetric StandardModel(MSSM) extensions and other Super Symmetry (SUSY) models. After the study ofthe full 2011 and 2012 datasets the main result of the LHC has been the observation of anew boson with a mass close to 125 GeV/c2 compatible with the Stardard Model Higgs.

This thesis presents the search of the Standard Model Higgs boson in the H → WWchannel where both W-bosons decay to electrons or muons. The data used for this workhave been collected during 2011 and 2012 by the Compact Muon Solenoid (CMS) exper-iment at the LHC. Detailed description of both the detector and the accelerator can befound in chapter 3. Four different topologies have been taken into account: µµ, ee, eµand µe, all with missing energy due to the undetected neutrinos. After lepton identifica-tion and isolation and requiring the presence of significant missing energy, the dominantbackground comes from non-resonant WW and tt production, the latter of which can begreatly reduced by vetoing all events with jets reconstructed in the central region. Thett background is suppressed by imposing anti-btagging on the reconstructed jets. In therest of the event selection, sets of sequential cuts are applied to each of the four topologies,in order to isolate a signal which exceeds the tt and continuum WW backgrounds. Oneimportant part of this work is in fact the measurement of the WW cross section at 8 TeV.

The event selection used in this analysis is the result of years of optimization aiming fora deep understanding of the channel. It is based on the original selection that was developedin the CMS Physics TDR [4], optimized and completed with the data-driven techniques in

7

2. INTRODUCTION

the 2007 analysis [5] and performed on the first 36 pb−1 of 2010 CMS collisions data [6;7; 8]. The improved analysis techniques needed to cope with the increased instantaneousluminosity and the more challenging pile-up during 2011 and 2012 are also described here.

The final results are given using two different approaches: a straight forward cut andcount analysis and a single variable analysis based on the 1D shape of different physicalvariables.

The document is structured as follows:Chapter 2 contains a dedicated review of the standard model and the experimental

searches of the Higgs boson before the LHC.In Chapter 3 a detailed overview of the LHC accelerator and the CMS detector is

presented together with a description of the CMS computing model. The physics objectchoice requires a deep understanding of the channel in order to stablish their definition toobtain a selection working point with a high signal efficiency and a low background. Afully detailed description of the object selection is also provided at the end of chapter 3together with the results for the lepton and trigger efficiencies.

The Standard Model Higgs phenomenology at the LHC and the description of theH → WW signature and properties are described in chapter 4. The different scenarios interms of integrated luminosity and center of mass energy are also described in this chapter.

The main background contributions (W + jets, WW, top and Drell-Yan) are estimatedusing data-driven methods. These methods are motivated and explained in detail in chapter5. Different sources of systematic uncertainties have been studied. Chapter 6 contains asummary of all of these uncertainties both for the cut based and shape analysis.

The results for the Standard Model Higgs search using the full 2011 and 2012 luminositytogether with the estimation of the WW production cross section at 8 TeV can be foundin chapter 7.

Finally, the conclusions of the work presented in this thesis are stated in chapter 8.

8

3

Standard Model Higgs Boson

Particles Physics is a branch of physics that studies the elementary constituents of matterand radiation, and the interactions between them. It is also called High Energy Physics(HEP), because many elementary particles do not occur under normal circumstances innature, but can be created and detected during energetic collisions of other particles, as isdone in particle accelerators. The development of Quantum Mechanics at the beginningof the 20th century, Quantum Field Theory some decades later and finally the StandardModel of particle physics, formulated in the sixties, represents a major breakthrough inour way to understand matter constituents and their interactions. After about 30 years ofextensive testing, the SM is one of the best theories of modern physics. In fact, most of itsbuilding blocks have been tested up to a very high precision over a large range of energiesand an agreement at the per mil level with the theoretical predictions has been found.

3.1 The Standard Model of Elementary Particles

The Standard Model (SM) provides a description of the structure and interactions of matter[9],[10],[11]. It explains the first three of the four fundamental interactions known : Strong,Weak, Electromagnetic and Gravitational. The standard Model consists of elementaryparticles grouped into two classes: bosons (force carrier particles) and fermions (matterconstituents). The bosons have an integer spin while the fermions have a half-integer spin.Fermions are themselves divided into two groups: leptons (particles that do not suffer thestrong force) and quarks (particles carrying color charge, hence suffering the strong force)grouped on three generations. As for the moment no internal structure has been foundfor these particles, they are considered as elementary particles. There are six quarks (up,down, charm, strange, top, bottom) and six leptons (electron, electron neutrino, muon,muon neutrino, tau, tau neutrino) each of them with its antiparticle. All of them sufferingthe weak force and the charged ones suffering the electromagnetic force as well. Tables 3.1and 3.2 summarize the properties for the different kinds of leptons and quarks.

As can be seen in tables 3.1 and 3.2 each member of a generation has greater mass thanthe corresponding particles of lower generations.

The Gauge Bosons are the particles responsible of carrying the fundamental forcesmentioned before. These bosons are photons (γ), electroweak bosons W± and Z0, andgluons (g). They are summarized in table 3.3.

9

3. STANDARD MODEL HIGGS BOSON

Table 3.1: Properties of the leptons

Generation Flavour Electric charge Mass

First Generation electron e− -e 0.510 MeVelectron neutrino νe 0 < 2.2 eV

Second Generation muon µ− -e 105.6 MeVmuon neutrino νµ 0 < 0.170 MeV

Third Generation tau µ− -e 1776.99 MeVtau neutrino ντ 0 < 15.5 MeV

Table 3.2: Properties of the quarks

Generation Flavour Electric charge Mass

First Generation up u 23e 1.5-3 MeV

down d −13e 3-7 MeV

Second Generation charm c 23e 1.25 GeV

strange s νµ−13e 70-120 MeV

Third Generation top t 23e 173.1 GeV

bottom b −13e 4.7 GeV

Table 3.3: Properties of the bosons

Particle Symbol Force Spin Charge (e) Mass (MeV/c2)Photon γ Electromagnetic 1 0 0

W± Boson W± Weak 1 ±1 80.4Z0 Boson Z0 Weak 1 0 91.2

Gluon Boson g Strong 1 0 0

The particles interact with each other by exchanging a Gauge boson. Particles with anon-zero weak-isospin are able to interact through the weak nuclear force by exchangingeither W± or Z0 and particles having color charge will interact through the strong nuclearforce by exchanging a gluon. Thus, the W Electroweak bosons can also interact one witheach other and with Z0, but this last boson can not couple with itself as it has zeroweak-isospin, neither can the boson of the Electromagnetic force, γ, because it has noelectromagnetic charge. Figure 3.1 shows the interactions between the Standard Modelparticles.

3.2 The Higgs mechanism

The electromagnetic and weak nuclear interactions can be described by a single unifiedquantum field theory based on a gauge group SUL × U(1)Y symmetry. Although thesetwo forces appear to be very different at everyday low energies, the theory models themas two different aspects of the same force. The electromagnetic forces act on the chargeand the weak nuclear forces act on two properties called the weak isospin (T) and the

10

3.3 Higgs searches at LEP

Figure 3.1: Summary of interactions between particles described by the Standard Model

hypercharge(Y). Above the unification energy, on the order of 100 GeV, these two forceswould merge into a single force called the electroweak force. The quantity conserved bythe U(1)Y group is the hypercharge, Y, related with the electrical charge , Q, through thethird isospin component, T3, after :

Q = T3 +Y

2(3.1)

This theory does not explain the mass for neither the weak bosons nor the leptons andquarks. The W and Z have both been measured to be very massive. In order to explain this,new terms must be included in the Lagrangian, but when this is done the SUL(2)×UY (1)symmetry is broken. To solve this problem the Higgs Mechanism is used. It introducesan additional term into the Lagrangian that represents two scalar fields along with anassociated potential energy. This new Lagrangian describes the electroweak interaction interms of three massive weak bosons (W±) and a massless photon (γ) plus an additionalspin zero particle known as the Higgs Boson. Figure 3.2 shows the Higgs potential.

Figure 3.2: Higgs potential

3.3 Higgs searches at LEP

The Large Electron Positron collider (LEP) was a circular e+e− collider with a circumfer-ence of 27 kilometres built in a tunnel 100 m under the border between France and Switzer-land. LEP operated between 1989 and 2000 when it was shut down and then dismantled in

11


order to make room for the construction of the Large Hadron Collider (LHC). Four detectorswere built at LEP around the four collision points: Aleph, Delphi, Opal and L3 [12]. Theywere constructed differently to allow for complementary experiments. The Higgs searcheswere very important at LEP since it was mainly designed aiming for a possible Higgs dis-covery. At LEP the main process for SM Higgs production was the Higgs − Strahlungmechanism, e+e− → HZ, which has a kinematic threshold at mH =

√s −mZ . The main

search topologies are therefore dictated by the dominant Higgs decay modes (mostly bband some ττ .) and the Z decay modes. All four LEP experiments carried out searches for(H → bb)(Z → l+l−, νν, qq) and for the main topologies with taus (H → τ+τ−) (Z → qq)and (H → bb)(Z → τ+τ−).

In the first period of running (LEP1) it was possible to achieve more than a 95% C.Lexclusion for a SM Higgs boson with a mass bellow 65.6 GeV/c2 combining all the topologiesstudied.

The running period since 1996 has been known as LEP II and throughout this period thecenter of mass energy in the e+e− collisions was gradually increased till 206.6 GeV. Takinginto account the results of the statistical combination of all the searches carried out by thefour detectors at LEP a lower limit was set excluding a signal with mH < 114.4 GeV/c2 at95%C.L. Figure 3.3 presents the LEP final plot showing the ratio CLs = CLs+ b = CLbfor the signal plus background hypothesis [13].

At the end of LEP-II era hints for the direct observation of a Higgs signal, correspondingto a Higgs boson mass around 116 GeV/c2 were detected, being this mass value well com-patible with the constraints derived from the precision electroweak measurements. LEPstopped its operations in 2000 and the observation hints could not be confirmed [12].

3.4 Higgs searches at the Tevatron

The Tevatron was a synchroton that accelerated protons and anti-protons in a 6.28 kmring. The Higgs searches took place during Run II (2002−2012) in which it was configuredto collide beams of 36 bunches with 1.96 TeV center of mass energy and provided anintegrated dataset of 10 fb−1 to the CDF and D0 experiments. At the Tevatron, the mostimportant production processes were Higgs boson production in association with W andZ vector bosons and the main decay modes were the leptonic decays of the vector-bosonswith H going to bb, but many other signatures have been studied. The Higgs productioncross section and the delivered luminosity were sufficient to be sensitive at the 95% CL toa Higgs boson having a mass between 90 GeV and 190 GeV, i.e. significant overlap withthe LEP excluded region at low mass, and with the LHC at higher mass. Sensitivity wasstrongest at low mass, 115 − 125 GeV (not considering the excluded LEP region) and atthe H → WW threshold (≈ 160GeV ). At low mass, the associated production channels(WH,ZH) involving H → bb are the most sensitive, with significant contribution fromdirect production WW down to 120 GeV. The WH and ZH channels with H → bb wereparticularly important at the Tevatron since this decay mode will not be measured preciselyat the LHC before the upgrade to the full energy foreseen for 2015. The search strategygave priority to direct production and H → WW decay mode at high mass, which allowedin 2009 to extend the LEP exclusion limit for the first time after almost ten years. Thisresult in combination with the precision electroweak measurements showed, before the LHC

12

3.4 Higgs searches at the Tevatron

Figure 3.3: The ratio CLs = CLs + b = CLb for the signal plus background hypothesis.Solid line:observation; dashed line: median background expectation. The dark and lightshaded bands around the median expected line correspond to the 68% and 95% probabilitybands. The intersection of the horizontal line for CLs = 0.05 with the observed curve is usedto define the 95% confidence level lower bound on the mass of the SM Higgs boson.

13


Figure 3.4: Observed and expected (median, for the backgroundonly hypothesis) 95% C.L.upper limits on SM Higgs boson production as a function of the Higgs boson mass for thecombination of CDF searches. The limits are expressed as multiples of the SM predictionfor test masses in 5 GeV/c2 steps from 90 to 200 GeV/c2 . The points are connected withstraight lines for improved readability. The bands indicate the 68% and 95% probabilityregions where the limits can fluctuate, in the absence of signal. The lighter dashed lineindicates mean expected limits in the presence of a SM Higgs boson with mH = 125 GeV/c2

.

produced significant results, that a mass of the SM Higgs boson between 100 < mH < 103GeV/c2 and 147 < mH < 180 GeV/c2 [14] were excluded at 95%CL. Figure 3.4 showsthe final observed and expected limits at the Tevatron. In june of 2012 Tevatron reportedan excess with a significance of 2.5σ in the mH region of 115 to 135 GeV when combiningCDF and DO results [15].

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4

LHC accelerator, CMS detector andPhysics Objects

The Large Hadron Collider (LHC) [16]is the world largest and highest energy particleaccelerator intended to collide opposing proton beams at an energy of 7 TeV each, providinga total center of mass energy of 14 TeV (

√s = 14 TeV) with an instantaneous luminosity

of 1034cm−2s−1, however these nominal values will be achieved only once it becomes fullyoperational by 2015. It has been built by the European Organization for Nuclear Research(CERN) and it is located in Geneva (Switzerland). The collider is contained in a circulartunnel, with a circumference of 26.7 kilometers, at a depth ranging from 50 to 150 metersunderground. The table 4.1 summarizes the main characteristics of the LHC accelerator.

Figure 4.1: Main characteristics of the LHC

The nominal center of mass energy of (√s = 14 TeV) represents an energy of about

one order of magnitude higher than those corresponding to the previous generation ofaccelerators (Tevatron in Fermilab

√s = 1.96 TeV). Thus, the LHC will allow us to explore

a wide physics ranging from the origin of the mass to the search for new physics beyondthe Standard Model.

The protons are first accelerated by a linear accelerator (LINAC 2) and by the ProtonSynchrotron (PS), then they are injected at the SPS (Super Proton Synchrotron) wherethey reach an energy of 450 GeV. To fill the LHC with protons, 24 cycles from the SPS arerequired. The mean life time of the beam is about 22 hours, but the data taken is limitedto the first 10 hours, after this period the instantaneous luminosity decreases too much tobe useful.

The LHC collides the beams at different points. Different particle detectors are locatedat the collision points to optimize the production of the collisions and allow to cross-check

15

4. LHC ACCELERATOR, CMS DETECTOR AND PHYSICSOBJECTS

the results. Figure 4.2 shows the collision points and the different sectors of the LHCaccelerator.

Figure 4.2: Collision points and different sectors at the LHC accelerator

4.1 LHC detectors

Besides CMS (Compact Muon Solenoid) detector, which will be described in detail on thenext section, at the LHC there are three other detectors of diverse purpose and basedon different technologies: ALICE [17], ATLAS [18] and LHCb [19]. Their location isschematically shown in figure 4.2.

4.1.1 A Large Ion Collider Experiment (ALICE)

It is a heavy ion detector dedicated to exploit the physics potential of nucleus-nucleusinteractions at LHC energies. It studies the physics of strongly interacting matter atextreme densities where the formation of a new phase of matter, the quark-gluon plasma,is expected.

4.1.2 A Toroidal LHC Apparatus (ATLAS)

Situated at point 1, is a general purpose detector as CMS. It is the biggest detector atLHC, with a length of 46 m and a diameter of 25 m.

4.1.3 The Large Hadron Collider beauty experiment (LHCb)

Detector dedicated to the study of B mesons and b-quark physics, specially the CP viola-tion and rare B decays that may be realted with the matter-antimatter assymetry in theuniverse.

4.2 Compact Muon Solenoid (CMS) detector

The Compact Muon Solenoid is located at Point 5. It is a general purpose detector,exploring new physics at TeV scale with special interest in Higgs Physics. Its design

16


is optimized for detecting the Higgs boson and other new particles, in order to do thatCMS features a redundant muon system, a good electromagnetic calorimeter and a highquality tracking system. CMS has specially emphasized muon detection within a largeenergy range. For a correct detection and measurement of the kinematics of the muonsan appropriate magnetic configuration must also be chosen. The big solenoid producesa magnetic field along the beam axis that curves the charges particles in the transverseplane. The curvature radius is important to get a precise measurement of the transversemomentum of the particle, pT, through the following expression:

R(m) =pT

0.3B(T )(4.1)

where R is the radius given in meters and B the magnetic field in Teslas.CMS is composed of the usual parts for a detector [20] in this kind of experiment:

tracker system, calorimeters (electromagnetic and hadronic) and the muon system. Eachtype of particle will interact in a different way with these components according to itsfundamental properties. In Figure 4.3 a schema of these interactions is shown.

Figure 4.3: Behaviour of the different particles while they traverse a section of the CMSdetectors. Neutrinos scape undetected.

4.2.1 Tracker system

The tracking system is composed by two types of silicon layers: the silicon pixel and siliconstrip detectors. It covers the region |η| < 2.5.

4.2.1.1 Pixel Tracker

It is the subdetector which is closer to the beam pipe of the detector. Its configurationallows to reach a 15 µm spatial resolution using interpolation algorithms, so high accuracyis essential in the reconstruction of high momentum muons, electrons and hadrons, as wellas secondary vertex from relatively long-lived particles such as bottom and charm hadronsand tau decays.

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4.2.1.2 Silicon Tracker

The other layers of the tracker have a total length of 5.4 m and a radius of 1.10 m andit is formed of silicon micro-strip detectors. 10 layers in the barrel region and 9 disks ateach endcap result in a minimum of 12 measurement points per charged track over a widerange of pseudorapidity (figure 1.5). The expected hit resolution for the silicon strip isσrφ = 10−60µm and σrz = 500µm. Combining these numbers, the expected CMS trackingresolution ranges from δPt

P 2T

= 0.015 for |η| < 1.6 up to δPt

P 2T

= 0.06 for |η| < 2.5. Thus, a

muon with a PT of 100 GeVc

can be measured with an accuracy of 1.5 for |η| < 1.6.

4.2.2 Calorimeters

4.2.2.1 Electromagnetic Calorimeter

The Electromagnetic Calorimeter (ECAL)[20],[21], measures the energy and direction ofthe electrons, positrons and photons. It is composed of approximately 8000 lead tungstate(PbWO4) crystals, covering a range of |η| < 3.

4.2.2.2 Hadronic Calorimeter

Combined with the ECAL to measure the energy and direction of hadronic showers, or jets,as well as the missing transverse energy. It also helps in the identification of the electrons,photons and muons. The Hadronic Calorimeter (HCAL) [22] consist of a barrel (HB) andendcaps (EH) inside the magnet and an Outer Hadronic Calorimeter (HO) outside thecoil (the refrigeration system). To achieve full hermeticity another part of the HCAL islocated in the forward region (HF) outside the muon system. HB, HE and HO are samplingcalorimeters with copper as absorber and plastic scintillator tiles as active material. Theenergy resolution, combined with the ECAL is σE

E= 120%√

E⊕ 6.9% where E is measured in

GeV.

4.2.3 Muon System

Muons are fundamental particles involved in the main physics processes to be exploredwith the LHC, such as Electroweak, top, Higgs, B mesons physics and also SM extensions(supersymmetry, extradimensions). For this reason, identification, selection and muonreconstruction [23],[24] at high luminosity were crucial in the design and construction ofCMS. Due to their properties, the muons are one of the cleanest objects (few secondaryparticles) to measure at colliders. The main purpose of CMS is to identify and select theseparticles and provide a precise and accurate measurement of their momentum in the rangefrom few GeV/c to few TeV

c. A good efficiency in the pseudorapidity detection is also

required for the detection of the muons product of the Higgs, W, Z and tt decays.The muon system is embedded in the iron return yoke of the magnet [25]. The low

momentum particles, up to 0.1 TeV, can be measured with high precision in the centraltracker using the 4 Tesla magnetic field, but the particles with higher momentum (from 0.1TeV to few TeV) need bigger trace longitudes in order to improve the PT measurement.These last muons must be analyzed with the muon chambers located within the iron returnyoke. The trace longitudes obtained this way are from 6 to 10 m long. The large thickness

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Figure 4.4: Energy deposits on the detector for photons, electrons and positrons, muons,π±, protons and neutrinos

of absorber material in the iron helps to filter out hadrons, so that muons are practicallythe only particles apart from neutrinos (that do not interact) able to escape from thecalorimeter system (see figure 4.4).

4.2.3.1 Drift Tube Chambers

The DTs consist of drift cells filled with a gas mixture of 80% of Ar and 20% of CO2.Due to the high voltage the maximum drift time is ≈ 180 ns with a resolution of ≈ 180µs. Charged particles traversing the tube liberate electrons which move accordingly to theelectric field established in the cell to the anode wire located in its center. Four staggeredlayers of DT cells are combined into a super layer. A schema for a DT can be seen in figure4.5

Figure 4.5: Schematic view of a Drift Tube cell

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4.2.3.2 Cathode Strip Chambers (CSCs)

The CSCs are situated at the endcap and consist of six gas layers (30% Ar, 50% CO2

and 20% CF4). In this region the background due to the thermic neutrons and muons isvery high. The electromagnetic field is also very elevated and inhomogeneous. In theseconditions, the CSCs are the most appropiated detectors to measure time and position.They are multiwire chambers where a cathode plane is segmented in strips which run inthe radial direction and a plane of anode wires running almost perpendicular to the strips.Gas ionization and subsequent electron avalanche caused by a charged particle traversinga layer produces a charge on the anode wire and an image charge on a group of cathodestrips. The signal on the wires is fast and is used for triggering purposes. The spatialresolution provided by each chamber is typically about 200 µm.

4.2.3.3 RPCs

Apart from the DTs and CSCs, used for a precise measurement of the traces, the muonsystem contains the RPC, which are used for muon trigger purposes, thanks to their quicktime response. RPC consists in two parallel resin plates, with a high bulk resistivityseparated by a gas-filled gap of a few millimeters. When a muon crosses along the chamber,the electron avalanche induces a signal in the aluminium strip situated at the cathodeexterior. The RPCs are mount on the DT chambers. Figure 4.6 shows the muon pTresolution given by the full muon system for the pseudorapidity range |η| < 2.

Figure 4.6: Muon System resolution versus p using the muon system only, the inner trackeronly or both (full system), in the barrel (left) and endcap (right)

4.3 Trigger

As it has been already mentioned the amount of events recorded by CMS is very large.Not all the processes are interesting from the physics point of view. For this reason, a

20

4.3 Trigger

proper trigger must be designed to reject these events. This is not easy, as the frecuencyof the bunch crossing is very high, and the decision must be fast enough to consider allthe processes and decide which of them must be kept. So the trigger must be quickly atthe reconstruction and identification of the objects and decide if they are accepted or not.The event rate at LHC is 109 Hz, being impossible to store such an amount of data, therate must be reduced to 100 Hz. The whole process is called the Trigger System and it isdivided into two phases: the Level 1 Trigger (L1) and the High Level Trigger (HLT) [26],[20] .

4.3.1 Level 1 Trigger (L1)

At this level the information is purely hardware based. It is very fast and allows for thefirst rough estimation of relevant quantities. As a consequence only simple calculationscan be processed in the L1 stage of triggering, still, unlike other L1 trigger systems thatrely just on counting objects with energy above some thresholds, the L1 Trigger of CMSis capable of applying sophisticated topological trigger algorithms. The only informationtaken into account is the one coming from the muon chambers and the calorimeters. Thisinformation is used to identify muons, electrons, photons and jets and permits to makea rough estimation of the pT of the particles, using hardware information (for example,if there have been signal at one of these detectors). The L1 trigger is divided in threesubsystems: level 1 for calorimeters, level 1 for muon chambers and Global Trigger (GT).The muon trigger is further divided in three independent systems for the DT, CSC andRPC detectors, respectively. A schematic view of the components of the L1 trigger systemand their relationships is shown in figure 4.7 .

Figure 4.7: Structure of the Level 1 Trigger system

The events accepted in the two first are sent to the last one and they have associatedsome information, as the coordinates in the plane (φ, η), the ET or the pT . The GT mustdecide analyzing these variables which event must pass to the next level. While this occurs,the event is kept with a latency time of 3.2 ms corresponding to 128 bunch crossings. Therate of events that pass to the next level (HLT) must not be higher than ≈ 100 kHz.

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4.3.2 High Level Trigger (HLT)

At Level 1 the rate of events was reduced from 109 to ≈ 100 kHz. At HLT the reductionmust reach 100 Hz, so a factor ≈ 103 reduction must be done by using intermediate stepsL2 and L3. The higher the level of trigger, the most detectors are used in the onlinereconstruction. There are four systems at the HLT, specially designed for the identificationof different types of particles: electrons/photons, quarks b and leptons taus, jets andmissing transverse energy and finally, muons. Here only a brief description of the muonHLT is shown, as we are interested in the processes with two muons in their final state.Once an event has been accepted by Level 1, the L2 makes a more precise reconstructionof the particles based on the hardware information. L2 also uses the calorimeter and muonsystem information and read some information from the tracker system. This level reducesby a factor 10 the data rate. The next step is L3, which uses the full tracker systeminformation to make an accurate reconstruction of the trace of the muon. A muon istriggered if determinate thresholds for the main variables are reached or other parametersare achieved, such as the isolation.

4.4 CMS computing model

CMS presents challenges not just in terms of the physics to discover or the detector to build,but also in terms of the huge amount of data it should be able to record and the computingresources needed to store, process and analyze it. The data sets and the computer resourcesrequired in this experiment are at least an order of magnitude larger than in previousexperiments. In order to cope with all the needs of the CMS detector and scientists,CMS has developed a computing model which is, among other characteristics, distributed,hierarchical and data driven.

It would be impossible to fulfill CMS computing and storage requirements at one singleplace, for both technical and funding reasons. In addition, most CMS collaborators arenot at CERN and they have access to non-CERN resources, something to take advantageof by CMS computing. Therefore, the CMS computing model has been constructed as adistributed system of computing services and resources. Most of these resources interactwith each other as GRID services. The GRID technologies aim at sharing the computing,storage and instrumentation ressources through well defined standards creating a softwarelayer (middleware) between the hardware and the GRID applications.

The main goal of the CMS computing model [27] is to make sure that the CMS collab-oration is able to store, process and analyze the data obtained in the collisions providingthe necessary resources and tools for the scientific exploitation of these data.

4.4.1 Hierarchical architecture

The CMS computing centers available around the world are configured in a tiered architec-ture integrated in the CMS computing model. It is divided into four levels, each of themproviding several resources and services as will be shown next.

• Tier-0

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There is only one Tier-0 located at CERN. All data flowing out of the CMS On-line Trigger and Data Acquisition System (TriDAS) are both archived on tape anddistributed to the Tier-1 centers in order to have backup copy of all the RAW datarecorded in the experiment. During LHC down-times the center contributes to thereprocessing of the data. A prompt reconstruction of the data is also performed atthe Tier-0.

• Tier-1

Currently seven centers are responsible for the safe keeping of a copy of the RAWdata. At the beginning of the data taking two copies of the reconstructed data arekept at the Tier-1 centers and then, as the amount of data increases, only one copyis saved. These centers should have enough CPU power for large-scale reprocessingsteps. Their output data are then distributed to Tier-2 centers. Tier-1s also providea secure storage and redistribution for MC samples generated by the Tier-2.

• Tier-2

A more numerous set of smaller Tier-2 centers, but with substantial CPU resources,provide capacity for user analysis, calibration studies, and Monte Carlo production.Tier-2 centers rely upon Tier-1s for the access of large datasets and for secure storageof the new data (Monte Carlo) produced on their facilities. The MC productionin Tier-2’s is a centrally organized activity, while analysis workflows are controlledindividually by the CMS collaborator.

• Tier-3

Tier-3 sites are an important component of the analysis capability of CMS as theyprovide location and resources for small institutes to perform their work. They areexpected to participate in CMS computing coordinated with specific Tier-2 centersand they provide valuable services such as supporting software development, final-stage interactive analysis or Monte Carlo production. Even if it may seem as if theTier-3 is the bottom of the chain, in some way it could be seen as the top of it sinceit is the first level at which physicist have access to data under their own control.

The majority of CMS users rely upon Tier-2 or Tier-3 resources as their base for analysiswith the Tier-1 centers providing the large-scale facilities. Figure 4.8 shows the flow ofCMS detector data through the Tiers (from T0 to T2).

4.4.2 CMSSW software

For this work the software framework designed at CMS called CMSSW [28] has been used.It is an object oriented framework prorammed with C++. It includes a completely revis-ited event data model and is fully integrated with a database infrastructure for handlingcalibration and alignment data. The whole Event Data Model (EDM) is based on theconcept that all data processing should pass through a single structure called the Event.

It is the user who defines in a job-specific configuration file which data to start from,what tasks to perform and what information finally needs to be stored in a ROOT-file.For each task in the processing of the data, a framework module needs to be implemented.

23


Figure 4.8: Diagram of the flow of CMS detector data through the different Tiers.

The module defines which information is needed for the Event to execute its module-specific task. To be able to fully process an event, one has to take into account potentiallychanging and periodically updated information about the detector environment and status(i.e calibrations, alignments, geometry descriptions...). This information is not tied to agiven event, but rather to the time period for which it is valid.

4.4.3 T3-Oviedo

The computer cluster of the experimental High Energy Physics research group at the Uni-versity of Oviedo is integrated within the CMS computing model as a Tier-3 center. In thissection some of the main tools needed to take part of such a complex distributed systemare described. I have been myself involved in both the installation and configuration ofthose tools and in the administration of the cluster itself.

• FroNTier

The FroNTier tool [29] provides a Squid based cache system serving conditions data(such as alignment and calibration constants) to the local cluster at the CMS cen-ters. Data is distributed once from central databases to each of the FroNTier serverswhen required so to avoid overloading the central CMS servers. Within each site theFroNTier system distributes the data to all the computing nodes. Our Tier-3 is wellbelow that number so only one such machine needed to be set up.

• ROOT

ROOT is an object-oriented program and library developed at CERN. It was orig-inally designed for particle physics data analysis and contains several features [30]specific to this field, but it is also commonly used in other applications such as astron-omy and data mining. ROOT is written in C++. It provides platform independentaccess to a computer’s graphics subsystem and operating system using abstract lay-ers. Parts of the abstract platform are: a graphical user interface and a GUI builder,container classes, reflection, a C++ script and command line interpreter (CINT),which makes this package very versatile as it can be used in interactive, scripted and

24


compiled modes. A key feature of ROOT is a data container called tree, with itssubstructures branches and leaves. A tree can be seen as a sliding window to theraw data, as stored in a file. Data from the next entry in the file can be retrievedby advancing the index in the tree. This avoids memory allocation problems associ-ated with object creation, and allows the tree to act as a lightweight container whilehandling buffering invisibly. ROOT is focused on performance due to the amountof data that the LHC’s experiments collect, estimated to several petabytes per year.The experimental plots and results showed in this work are obtained using ROOT.

• PhEDEx

PhEDEx [31] is a data transfer management system designed to handle the large datavolumes required by the CMS computing model. PhEDEx meets CMS requirementsfor large scale distribution of data by managing a blend of traditional HEP distri-bution infrastructure with new GRID and peer-to-peer replication tools. Ensuringthe data safety and replicating large-scale data are the main aspects that such adata management system accomplishes. Figure 4.9 shows the monthly transfer datavolume to the Oviedo T3 for the last 11 months.

Traditionally data management and data placement are very manpower intensiveoperations. PhEDEx comprises a set of agents, each undertaking a unique task (suchas file replication, routing decision...) in a reliable way allowing to drastically reducethe manpower requirements. This partitioning in subsets of simple tasks is one of thekey elements that makes PhEDEx suitable for an experiment such as CMS havinga huge amount of datasets and a complicated computing infrastructure. Figure 4.10shows the work flow of PhEDEx.

Figure 4.9: Cumulative data volume transfer to the Oviedo T3 in the last years

• Batch system

An experiment with such a huge amount of data as CMS requires a well organizedworking method and a good resource management. Our main goal was to installa batch system based on Torque/Maui for administering on a simple, robust andhomogeneous way the distribution of the computing resources. A tool was developedand deployed allowing to run CMSSW jobs on a parallel way being totally transparent

25


Figure 4.10: Schemas of the PhEDEx Work Flows.

for the user, who only must have a configuration file with the dataset he wants to useand the number of jobs to split it into. A web interface is also available to monitorthe status of the jobs showing the data and graphs (see next section).

• Ganglia

Ganglia [32] is a scalable distributed system monitor tool for high-performance com-puting systems such as clusters and GRID. It allows the user to remotely view liveor historical statistics (such as CPU load averages or network utilization) for allmachines that are being monitored. It relies on a multicast-based listen/announceprotocol to monitor state within clusters and uses a tree of point-to-point connectionsamongst representative cluster nodes to federate clusters and aggregate their state.It leverages widely used technologies such as XML for data representation, XDR forcompact, portable data transport, and RRDtool for data storage and visualization. Ituses carefully engineered data structures and algorithms to achieve very low per-nodeoverheads and high concurrency. The ganglia system comprises two unique daemons,a PHP-based web front-end. Depending on the user needs several useful addons canbe also included, such as Job Monarch.

4.5 Physics Objects

The capabilities of the CMS detector for an efficient and precise reconstruction of thedifferent physical observables is a key aspect to perform all the analysis and speciallythe new physics searches. As already mentioned in the previous chapter, the signatureunder study is defined by a final state with two high pT leptons with opposite charge, nohard jet activity and a significant amount of missing ET . The high level objects neededin the analysis are therefore: primary vertex, leptons (muons and electrons), missing ET(undetectable neutrinos) and jets (quark and gluon hadronization). These objects togetherwith the different techniques of identification and reconstruction will be detailed describednext.

26

4.5 Physics Objects

4.5.1 Vertex

An accurate reconstruction of the primary event vertices [33] is needed to assign tracksto collisions and to determine the event kinematics. Secondary vertices are tools for iden-tifying long-life particles like heavy flavor hadrons and τ leptons. Multiple overlappingevents with high track density and particle interactions are the main challenges for vertexreconstruction.

Vertex reconstruction can be divided in two different steps:

• Pattern recognition or vertex finding This step consists in finding clusters of compati-ble tracks among a set of tracks given as input. The search can either be inclusive, likein the search of a secondary vertex in a b-jet, or be guided by the a-priori knowledgeof the decay channel.

• Fitting This step consists in estimating the vertex position most compatible with theset of tracks given as input, and constraining the momentum vector of the tracksusing the vertex position.

In the case of CMS the track clustering is being performed with the DeterministicAnnealing (DA) algorithm [34]. This method offers an important feature, the ability tofind vertices in a noisy environment without a previous knowledge of the number of verticesto be found. DA algorithm not only gives better spacial resolution, being able to separateinteractions that are 100 µm or less apart, but also a low fake rate (defined as the ratio ofthe number of non-associated reconstructed vertices to the total number of reconstructedvertices). This algorithm is hence able to cope with nearby interactions with the currentLHC conditions, improving discrimination against high pile-up.

For the fitting step the vertex candidates containing at least two tracks are fit withan adaptive vertex fitter to compute the best estimate of vertex parameters, including theposition and covariance matrix, as well as the indicators of the success of the fit, such as thenumber of degrees of freedom of the vertex and track weights of the tracks in the vertex.

4.5.2 Muons

The ability to efficiently reconstruct and identify muons [35], [36] over a wide range ofenergies and in the whole geometric acceptance of the detector is one of the main goals ofthe CMS design.

Muon reconstruction can be categorized into three different types:

• Stand-alone: The reconstruction in the muon spectrometer starts with the recon-struction of hit positions in the DT, CSC and RPC subsystems. Hits within each DTand CSC chamber are then matched to form segments (track stubs). The segmentsare collected and matched to generate seeds that are used as a starting point for theactual track fit of DT, CSC and RPC hits. The result is a reconstructed track in themuon spectrometer.

• Tracker Muon: muon objects reconstructed with an algorithm that starts from asilicon tracker track and looks for compatible segments in the muon chambers.

• Global: Stand-alone muon tracks are matched with tracker tracks to generate globalmuontracks, featuring the full CMS resolution.

27


4.5.2.1 Muon Reconstruction

Track reconstruction in the muon spectrometer is also based on the Kalman filter. Thefirst step is to estimate the seed state from DT and CSC segments, which give a roughestimation of the pT of the candidate. Later, a pattern recognition is performed propagatingthe seed trajectory state parameters to the innermost compatible muon detector layer anda pre-filter is applied in the inside-out pd direction. Its main purpose is to refine the seedstate before the true filter.

The pre-filter and filter are based on the same iterative algorithm, divided into differentsub-steps: search of the next compatible layer and propagation of the track parametersto it, best measurement finding and possibly update of the trajectory parameters withthe information from the measurement. The process stops when the outermost (for thepre-filter) or the innermost (for the filter) compatible layer of muon detectors is reached.

At each step the track parameters are propagated from one layer of muon detectorsto the next. This process correctly includes material effects like multiple scattering andenergy losses due to ionization and bremsstrahlung in the muon chambers and return yoke.

The best measurement is searched for on a χ2 basis. The χ2 compatibility is examinedat the segment level, estimating the incremental χ2 given by the inclusion in the fit of thetrack segment. In case no matching hits (or segments) are found, the search continues inthe next station.

In order to finally accept a trajectory as a muon track, at least two measurements,one of which must be of the DT or CSC type, must be present in the fit. This allowsrejection of fake DT/CSC segments due to combinatorics. Moreover the inclusion of theRPC measurements can improve the reconstruction of low momentum muons and thosemuons which escaped through the inter-space between the wheels (and the DT sectors),leaving hits in only one DT/CSC station.

Finally, after the fake track suppression, the parameters are extrapolated to the pointof closest approach to the beam line. In order to improve the momentum resolution aconstraint to the nominal interaction point (IP) is imposed. This final step gives thecomplete stand-alone muon track.

After this description, the stand-alone muon track is fully described. The secondalgorithm for muon reconstruction is the tracker muon. It works considering all silicontracker tracks and identifying them as muons by looking for compatible signatures in thecalorimeters and the muon system. Once a silicon tracker track is reconstructed the algo-rithms looks for compatible segments in the muon detectors. The energy deposition in thecalorimeter can also be used for muon identification. The momentum vector of a trackermuon is the same as that of the silicon tracker track.

An important ingredient for tracker muons is arbitration. This is the pattern recognitionproblem of assigning segments to tracks. The segment arbitration is based on the best ∆Xmatch or the best ∆R2 = ∆X2 + ∆Y 2 match, where ∆X (∆Y ) is the distance in localX (Y) between the segment and the extrapolated track. This variable is used to betteridentify muons. A brief description of the algorithms of tracker muons used in the analysisis summarized:

• TMLastStationTight Requires at least two muon segments matched at 3σ in local Xand Y coordinates, with one being in the outermost muon station. This algorithm isused to recover events, for instance, when the two muons in the final state are close by

28

4.5 Physics Objects

in the spectrometer, in which the Global muon algorithm is known to be inefficient,see [37].

• TMLastStationAngTight As the previous one with additional angular cuts.

For the global muon track, advantage from both the tracker detector and muon spec-trometer is taken, see Figure 4.11. While each sub-detector is able to measure a part ofthe muon’s properties, the concept of a global muon is to combine information from mul-tiple sub-detectors in order to obtain a more accurate description of it. The momentumresolution of muon tracks up to pT = 200 GeV reconstructed in the muon system alone isdominated by multiple scattering. At low momentum, the best momentum resolution formuons is obtained from the silicon tracker. At higher momentum, however, the character-istics of the muon system allow the improvement of the muon momentum resolution bycombining the muon track from the silicon detector, tracker track, with the muon trackfrom the muon system, stand-alone muon, into a global muon track. The reconstruction ofglobal muon tracks begins after the completion of the reconstruction of the central trackertracks and the muon system tracks.

Figure 4.11: Global Muon track reconstructed in both the Tracker and Muon systems.

The first step in reconstructing a global muon track is to identify the silicon trackertrack to combine with the stand-alone muon track. This process of choosing tracker tracksto combine with stand-alone muon tracks is referred to as track matching. The first stepof the track matching process is to define a region of interest that is rectangular in η − φspace, and to select a subset of tracker tracks that are in this tracking region of interest.The second step is to iterate over the subset of tracker tracks, applying more stringentspatial and momentum matching criteria to choose the best tracker track to combine withthe stand-alone muon.

After the selection of a subset of tracker tracks that match the stand-alone muon track,the next step in making a global muon track is to fit a track using the hits from the trackertrack and the stand-alone muon track. The global refit algorithm attempts to perform atrack fit for each tracker track - stand-alone muon pair. If, after the fit is attempted foreach pair, there is more than one possible global muon track, the global muon track withthe best χ2 is chosen. Thus, for each stand-alone muon there is a maximum of one globalmuon that are reconstructed.

29


In Figure 4.12 the momentum resolution for the tracker, stand-alone and global muonsis shown. For values below 200 GeV the measurement of the momentum is dominated bythe tracker resolution. For higher values, the intrinsic resolution of the muon plus trackersystems starts to become the same order of magnitude as for tracker only, because multiplescattering effects become smaller as pT increases.

Figure 4.12: Muon Momentum Resolution in Monte Carlo, as a function of p, comparingthe results of the tracker track fit, the stand-alone fit and the global fit.

Figures 4.13 and 4.14 show the reconstruction of the dimuon spectra for the whole 2010dataset and the first 1.1 fb−1 of data collected in 2011. The mass peak for several resonancescan be seen, from the low ones, η, ρ, w, φ, moving to higher values of the invariant massin J/φ and Upsilon, to the highest resonance for the Z boson. These figures show the highmuon momentum resolution at the detector, and the large kinematic coverage, from pT∼500 MeV to the TeV momentum.

4.5.2.2 Muon Isolation

For the 2012 analysis the muon isolation is based in the Particle-Flow algorithm. An MVAapproach is considered based on the radial distributions of the Particle-Flow candidatesinside the cone. A cone of 0.5 is considered and splited into 5 isolation rings. Each of themis pile-up corrected by ρ and effective area corrections.

IsoRing = PFIso - ρAeff

Where the ρ is computed rhoIso = cms.InputTag(’kt6PFJets’, ’rho’), and Aeffis one of the values in Table 4.5.2.2. A more extensive explanation on how to apply theeffective area corrections can be found in Ref. [38].

30

4.5 Physics Objects

)2 Dimuon mass (GeV/c1 10 210

Even

ts /

GeV

1

10

210

310

410

510

610

CMS

-1int

= 7 TeVs

ηω,ρ

φψJ/

'ψ Υ

Z

L = 40 pb

Figure 4.13: Invariant mass spectra of opposite-sign muon pairs in 2010 data.

dimuon mass [GeV]

Eve

nts

per

10

MeV

-110

1

10

210

310

410

510

610

10 2101

trigger paths'ψψJ/

-µ+µ → sBΥ

double muonT

low p double muon

Thigh p

= 7 TeVsCMS

-12011 Run, L = 1.1 fb ψJ/

'ψ

ω φ

Υ

Z

sB

Figure 4.14: Invariant mass spectra of opposite-sign muon pairs in the first 1.1 fb−1 2011data.

Variable |η| < 1.0 1.0 < |η| < 1.5 1.5 < |η| < 2.0 2.0 < |η| < 2.2 2.2 < |η| < 2.3 2.3 < |η| < 2.4PFIsoGamma 0.0-0.1 0.004 0.002 0.003 0.009 0.003 0.011PFIsoGamma 0.1-0.2 0.012 0.008 0.006 0.012 0.019 0.024PFIsoGamma 0.2-0.3 0.026 0.020 0.012 0.022 0.027 0.034PFIsoGamma 0.3-0.4 0.042 0.033 0.022 0.036 0.059 0.068PFIsoGamma 0.4-0.5 0.060 0.043 0.036 0.055 0.092 0.115PFIsoNeuHad 0.0-0.1 0.002 0.004 0.004 0.004 0.010 0.014PFIsoNeuHad 0.1-0.2 0.005 0.007 0.009 0.009 0.015 0.017PFIsoNeuHad 0.2-0.3 0.009 0.015 0.016 0.018 0.022 0.026PFIsoNeuHad 0.3-0.4 0.013 0.021 0.026 0.032 0.037 0.042PFIsoNeuHad 0.4-0.5 0.017 0.026 0.035 0.046 0.063 0.135

A muon will be considered to be isolated when its MVA isolation value is greater than0.86 (0.82) for muons with pT < 20 GeV/c in the barrel (endcap) and greater than 0.82(0.86) for muons with pT > 20 GeV/c in the barrel (endcap).

31


Comparison of performance for different algorithms can be found in Ref. [38].In the 7 TeV analysis the particle flow candidate-based isolation variable is used. IsoPF

is defined as the scalar sum of the pT of the particle flow candidates satisfying the followingrequirements:

• ∆R < 0.3 to the muon in the η × φ plane,

• |dz(PFCandidate)− dz(muon)| < 0.1 cm, if the PF candidate is charged,

• pT > 1.0 GeV, if the PF candidate is classified as a neutral hadron or a photon.

IsoPF

pT< 0.13 (0.06) is required for muons in the barrel with pT greater (smaller) than 20

GeV/c. In the endcap, we require IsoPF

pT< 0.09 (0.05) for muons with pT greater (smaller)

than 20 GeV/c.

4.5.3 Electrons

A primary electron is composed of a single track emerging from the interaction vertex andmatched to an electromagnetic supercluster. The electron reconstruction [39] in CMS ishampered by the amount of tracker material which is discretely distributed in front ofthe ECAL. Electrons traversing the silicon layers of the pixel and inner tracker detectorsradiate bremsstrahlung photons and, since the electron direction can change significantly inpresence of the 4 T solenoidal magnetic field, the energy reaches the ECAL with a spread inφ. This spread is pT dependent. The amount of bremsstrahlung emitted when integratingalong the electron trajectory can be very large.

The electron measurements can be further complicated by the conversion of secondaryphotons in the tracker material, which might lead to showering patterns and entail energylost in the tracker material.

4.5.3.1 Electron Reconstruction

The electron reconstruction proceeds in the following main steps:

• Seeding

Electron reconstruction uses two complementary algorithms at the track seedingstage: the ECAL driven seeding and the tracker driven seeding, more suitable forlow pT electrons as well as performing better for electrons inside jets.

The ECAL driven algorithm starts by the reconstruction of ECAL superclusters oftransverse energy ET> 4 GeV and is optimized for isolated electrons in the pT rangerelevant for Z or W decays. The supercluster is a group of one or more associatedclusters of energy deposits in the ECAL, constructed using an algorithm which takesinto account their characteristic narrow width in the η coordinate and their charac-teristic spread in φ, due to the bending in the magnetic field of electrons radiating inthe tracker material.

As a first filtering step, superclusters are matched to track seeds (pairs or triplets ofhits) in the inner tracker layers, and electron tracks are built from these track seeds.

32

4.5 Physics Objects

Trajectories are reconstructed using a dedicated modeling of the electron energy lossand fitted with a Gaussian Sum Filter (GSF) [40].

The tracker driven seeding algorithm can be illustrated with two extreme cases.

1. When an electron does not radiate energy by bremsstrahlung while traversingthe tracker, it gives rise to a single cluster in the ECAL and its track is oftenwell reconstructed by the standard Kalman Filter, which is able in these casesto collect hits up to the ECAL entrance. The track can then be matched with aparticle flow cluster, and its momentum compared to the cluster energy formingan E/p ratio. If this ratio is close to unity, the seed of the track is promoted toelectron seed.

2. When an electron undergoes a significant bremsstrahlung, the standard KalmanFilter is not able to follow the change of curvature, and the track has a smallnumber of hits, and a large χ2. Thus, using the tracker as a preshower, andexploiting the differences of characteristics between a pion track and an electrontrack reconstructed with the standard Kalman Filter algorithm, the electrontracks can be selected.

The variety of situations between the two extreme cases illustrated here requires atreatment more sophisticated than what was just described. In practice, a refinedtreatment of the track is applied, and the pure tracking observables are combinedwith the ECAL-track matching quality variables in a single discriminator with amultivariate analysis.

Seeds from the two algorithms (ECAL driven and tracker driven) are then merged ina single collection, keeping track of the seed provenance.

• Tracking

Electron seeds are then used to initiate a dedicated electron track building and fittingprocedure in order to best handle the effect of bremsstrahlung energy loss. The trackfinding is based on a combinatorial Kalman Filter, with a dedicated Bethe Heitlermodeling of the electron energy losses.

The hits collected in the track finding phase are passed to a GSF for the final estima-tion of the track parameters. In such fit, the energy loss in each layer is approximatedby a weighted sum of Gaussian distributions. The GSF leads to multi-componenttrajectory states for each measurement point, with weights for each component de-scribing the associated probability.

• Preselection

Electron candidates are built from the reconstruction of GSF tracks and their asso-ciated superclusters. In the case of electrons with ECAL driven seeds, the associatedsupercluster is simply the supercluster that initiated the seed reconstruction. For thecases of electrons with seeds only found by the tracker driven seeding algorithm, atracker driven bremsstrahlung recovery algorithm and identification of the electroncluster developed in the context of the particle flow reconstruction are used.

33


Electron candidates are then preselected using available track-cluster matching ob-servables in order to reduce the rate of jets faking electrons. The preselection is madevery loose, so as to efficiently reconstruct electrons and satisfy a large number ofpossible analyses.

For electrons that have an ECAL driven seed, some cuts have been already appliedat the seeding level (i.e. ET > 4 GeV). In addition to this selection, some otherrequirements are also applied in the η and φ distances between the superclusters andthe extrapolated innermost track.

In Figure 4.15 the dielectron mass spectrum for 2010 data is shown. In this case, themass resolution is worse than for muons, especially at low mass.

Figure 4.15: Invariant mass spectra of opposite-sign electron pairs in 2010 data.

4.5.3.2 Electron Isolation

With the advancement of particle flow reconstruction at CMS, one can further improve theperformance of electron isolation requirement by using particle flow isolation, rather thanusing energy measurement from independent sub-detectors. The particle-flow isolationis defined as a scalar sum of the transverse momentum of the particle flow candidatesreconstructed in the chosen ∆R cone, defined as:

isorel. =

∑chargedhadron pT +∑neutralhadron pT +

∑photon pT

pelectronT

. (4.2)

This approach has several advantages over detector-based method:

• it makes use of reconstructed particles, which have been assigned the correct energycalibration depending on the particle hypothesis.

34

4.5 Physics Objects

• the energies assigned to the particle candidates are not double counted (eg. the ECALcluster and the tracks linked to it if they come from a photon conversion)

• handling the footprint of the electron: in the case of ideal particle flow reconstruction,the bremsstrahlung candidates are linked to the electron candidate more efficientlythan a simple strip + internal veto cone

• given that energy deposits are not double-counted, and they are correctly calibrated,pile-up extra-energy can be subtracted with the same algorithm used to correct a jetwith calibrated energy.

For the 7 TeV analysis the Particle Flow based isolation is used in the case of theelectrons. The particle flow candidates taken into account for the calculation of the IsoPF

variable must satisfy the following requirements:

• ∆R < 0.4 to the electron in the η x φ plane.• |dz (PFCandidate) - dz (electron)| < 0.1 cm, if the PF candidate is charged.• pT > 1.0 GeV, if the PF candidate is classified as a neutral hadron or a photon.• For neutral hadron PF candidates, require that it is outside the footprint veto region

of ∆R < 0.07.• For photon or electron PF candidates, require that it is outside the footprint veto

region of ∆η < 0.025.

The electrons are required to have IsoPF < 0.13 (0.09) for electrons in the barrel (end-cap) to be considered isolated.

For the 8 TeV analysis the so called Frixione isolation is used. The sum of all pT

deposits within a fixed cone in ∆R which is used in the traditional approach to particleflow isolation provides a good performance. A further improvement can be reached byusing the η and φ information of all the particle flow candidate within the isolation coneof the electron candidate. As isolation on a signal electron is from the underlying event,while background isolation comes from collimated jets, one expects a significant differencein spatial separation ∆R of the particle flow candidates in the isolation cone from theelectron candidate in signal and background, and thus, it can aid in further improvementin the performance of the isolation requirement. The Frixione isolation is an isolationmethod where a set of successive isolation rings is used rather than one solid isolation coneto estimate the level of isolation of the electron candidate.

All of these variables are then used as inputs to a boosted decision tree (BDT) algorithmthat allows to separate signal electrons from misidentified jets. The BDT is trained on asignal sample of H → ZZ → 4` Monte Carlo simulation, and a background sample fromdata of Z+jets events.

The performance of this BDT is compared to both detector-based and regular particleflow isolation in Figs. 4.16-4.18. In the high-pT region all the algorithms give approxima-tively the same performance, while the gain using particle-based isolation is increasing asthe electron pT lowers, reaching 5-10% at the low-end of the electron pT spectrum. Thegain obtained using rings isolation is also enhancing in the lower pT bins.

35


Figure 4.16: Background (false electrons from the Z+jets 2011 data sample) versus signalefficiency (electrons MC-truth matched in H → ZZ → 4` signal MC) for electrons withpT >20 GeV/c in the barrel (left) and in the endcap (right).

Figure 4.17: Background (false electrons from the Z+jets 2011 data sample) versus signalefficiency (electrons MC-truth matched in H → ZZ → 4` signal MC) for electrons with10 < pT < 20 GeV/c in the barrel (left) and in the endcap (right).

4.5.4 Lepton and Trigger efficiencies

The Tag and Probe TP method is used to measure both the lepton and trigger efficiencies[41]. This technique allows almost an unbiased estimation of the efficiencies at the differ-ent stages of lepton trigger and offine reconstruction. For this technique, an almost freebackground Z sample is used where events with two leptons, an invariant mass within theZ mass window, are selected. One of the leptons fulfill tight requirements (tag lepton), andthe other has very loose requirements (probe lepton), in order not to bias the eciency. The

36

4.5 Physics Objects

Figure 4.18: Background (false electrons from the Z+jets 2011 data sample) versus signalefficiency (electrons MC-truth matched in H → ZZ → 4` signal MC) for electrons with5 < pT < 10 GeV/c in the barrel (left) and in the endcap (right).

tight selection is applied then, to the probe lepton, to measure the efficiency. Althoughthe selection of a resonance leads to a high purity sample of tag-probe pairs, there stillremains some background. This can be consequence of the high pile-up environment orjust the track combinatorial, resulting in fake tag-probe pairs, which can bias the mea-sured effciency. The TP method relies on the counting of the number of passing and failingprobes. Passing probes are those which fulfill the tight selection requirements for the lep-tons. Failing probes, on the contrary, do not pass all the cuts. To correctly account for thebackground, a binned fit to extract the signal events from the background is performed.The efficiency is measured in data and in MC samples to obtain a set of data/simulationscale factors which are then applied to the simulation.

4.5.4.1 Lepton efficiencies

• Electron Efficiencies and Scale Factors

The fit function used for the resonant part of the signal is the convolution of a Breit-Wigner convoluted with a Crystall-Ball function. To take into account the tail at lowMee due to the showering electron, a tail is added to the resonant part : the proportionof the tail with respect to the resonance is then obtained from the simulation. Thebackground is fitted with a 3rd degree Bernstein polynomial.

The scale factors obtained are summarized in Table 4.1.

• Muon Efficiencies

The fit functions used are the sum of 2 voigtians for signal and a 3rd degree Bernstein polynomialfor background.

The scale factors obtained are summarized in Table 4.2.

• Efficiency Decrease During 2012 Data Taking

37


Table 4.1: Electron identification efficiency data/simulation scale factors. Errors are statis-tical only.

0.8 1.4442 1.556 2.0pT range [GeV/c] |ηSC | < 0.8 < |ηSC | < < |ηSC | < < |ηSC | < < |ηSC | <

1.4442 1.556 2.0 2.510 < pT < 15 0.662 ± 0.019 0.730 ± 0.027 0.808 ± 0.094 0.606 ± 0.037 0.644 ± 0.03215 < pT < 20 0.901 ± 0.009 0.942 ± 0.014 0.857 ± 0.066 0.834 ± 0.019 0.759 ± 0.01720 < pT < 30 0.943 ± 0.003 0.950 ± 0.003 0.917 ± 0.010 0.922 ± 0.005 0.972 ± 0.00630 < pT < 40 0.961 ± 0.001 0.944 ± 0.151 0.964 ± 0.005 0.925 ± 0.002 0.981 ± 0.00540 < pT < 50 0.976 ± 0.001 0.967 ± 0.092 0.954 ± 0.004 0.961 ± 0.001 0.982 ± 0.00250 < pT < 200 0.974 ± 0.001 0.970 ± 0.001 0.986 ± 0.009 0.963 ± 0.168 0.970 ± 0.003

Table 4.2: Muons identification efficiency data/simulation scale factors. Errors are statisticalonly.

0.9 1.2pT range[GeV/c] |ηSC | < 0.9 < |ηSC | < < |ηSC | <

1.2 2.510 < pT < 15 0.992 ± 0.012 0.971 ± 0.358 1.002 ± 0.00515 < pT < 20 0.961 ± 0.005 0.951 ± 0.005 0.995 ± 0.00320 < pT < 25 0.982 ± 0.002 0.982 ± 0.001 1.020 ± 0.00225 < pT < 30 1.000 ± 0.001 0.993 ± 0.002 1.019 ± 0.00130 < pT < 50 0.993 ± 0.001 0.991 ± 0.001 1.002 ± 0.00150 < pT < 150 0.994 ± 0.001 0.991 ± 0.001 1.005 ± 0.001

An efficiency loss has been observed during 2012 data taking for the electron selection. For electronin the detector acceptance and pT > 20 GeV/c this efficiency was 0, 773 ± 0.001 during the run Aand decreases to 0.740±0.01 in the run D. The figure 4.19 shows the decrease of the efficiency versustime.

The efficiency loss seems to come partially from the ID part of the selection. The preselection hasalso been found to be responsible for part of the decrease. The figure 4.20illustrates this checkfor low η electrons. To take into account the observed efficiency loss, the scale factors have beencomputed for each data-taking period both for muons and electrons. Detailed tables with the scalefactors by run period can be found in [42]

The decrease of the efficiency has been also observed in other CMS analyses and is still underinvestigation, the increase in the noise in the ECAL during the 2012 data taking could be a possiblereason.

4.5.4.2 Trigger Efficiencies

As already mentioned before, the trigger efficiencies have been also calculated using the TPmethod. Tables with the different trigger efficiencies with respect to the different pT/|η|bins can be found in [42].

• Combination

These separate trigger efficiencies are then combined in order to assign a trigger weight(i.e. a probability of the event passing at least one of the conditions of the different

38

4.5 Physics Objects

Run Number192 194 196 198 200 202 204 206 208

310×

∈

0.7

0.72

0.74

0.76

0.78

0.8|<2.5η>20 GeV/c and |Telectron with P

CMS preliminary 2012 = 8 TeVs

WW electron selection→efficiency of H

runA runB runC runD

Figure 4.19: Efficiency of the electron selection during 2012 data taking.

pt (GeV/c)20 40 60 80 100 120 140 160 180 200

∈

0

0.2

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1

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∈

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∈

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1.2N-1 ID | < 0.8η|SC

runD

runA

runD/runA

Figure 4.20: Comparison between efficiency in run A and D for preselection (a), isolationcut (b) and MVA ID cut (c ) for electron with |ηSC | < 0.8. (b) and (c ) are N-1 efficiencies.

triggers) on an event-by-event basis to the MC samples. The combined efficiency isgiven by

ε (pT , |η|, p′T , |η′|) = εS (pT , |η|) (1− εD,t (p′T , |η′|)) + εS (p′T , |η′|) (1− εD,t (pT , |η|)) +

εD,l (pT , |η|) · εD,t (p′T , |η′|) + εD,t (pT , |η|) · εD,l (p′T , |η′|)−εD,l (pT , |η|) · εD,l (p′T , |η′|)

where εS are the single lepton trigger efficiencies and εD are the double lepton triggerefficiences (for the leading and the trailing leg).

39


• Run Period Dependency

To check for possible time dependencies of the triggers all the efficiencies for thesingle triggers and the individual legs of the double triggers were rederived per runperiod and for different pile-up bins. Some inefficiency is found in the double electrontrigger starting from Run2012B that is recovered (almost) completely with the singleelectron trigger. More details about the trigger efficiency dependency can be foundin [42]

4.5.5 Jets

Because of the QCD confinement, color charged particles cannot exist in a free form. There-fore they fragment into a collimated shower of hadrons called jets. In order to determinethe properties of the original parton these jets need to be measured and studied in thedetector.

4.5.5.1 Reconstruction algorithms

The jets are very difficult objects regarding event reconstruction and many studies of thejet energy scale and object reconstruction were needed, once the first data was available.

For the correct understanding of the next sections it is also necessary to introduce threedifferent types of jet reconstruction: calorimetric jets (’CaloJets’), tracker jets (’TrackJets’),Jet Plus Tracks (’JPT’) and Particle Flow jets (’pfJets’).

• CaloJets. Calorimeter jets [43] are reconstructed using energy deposits in calorimetertowers as inputs. These CaloTowers collect both the charged and the neutral com-ponent of the parton hadronization, however, due to the strong inner CMS magneticfield, CaloTowers fail to collect the energy of low momentum charged particles whichdo not reach the calorimeter.

• JPT. Jet Plus Tracks [44] algorithm exploits the excellent performance of the CMStracking detectors to improve the pT response and resolution of calorimeter jets.Calorimeter jets are reconstructed first as described above, then charged particletracks are associated with each jet based on spatial separation in η − φ between thejet axis and the track momentum measured at the interaction vertex. The momentaof charged tracks are then used to improve the determination of the energy anddirection of the associated calorimeter jet.

• pfJets. The PF jet reconstruction [45] uses the information from all CMS sub-detectors to identify and reconstruct all stable particles in the event: muons, electrons,photons, charged hadrons and neutral hadrons. The jet momentum and spatial res-olutions are expected to be improved with respect to calorimeter jets, as the use ofthe tracking detectors and of the excellent granularity of the ECAL allows to resolveand precisely measure charged hadrons and photons inside jets, which constituteapproximately 90% of the jet energy.

• TrackJets. Tracker jets [46] are reconstructed using only the tracker information, i.echarged particles tracks. The tracking momentum measurements are more accurate

40

4.5 Physics Objects

than the calorimeter measurements or charged particles with energies up to severalhundreds of GeV, and the direction of charged particles at the interaction point isextremely well determined by the track reconstruction. For these reasons a multi-jet event in CMS is expected to be cleaner when looking at the tracks instead ofthe CaloTowers, with less overlap and interference, and less background (e.g. pile-up events). On the other hand, as just 2/3 of the energy of the jet are carried bycharged particles, TrackJets are not optimal to measure jet energies, leading to aworse resolution than PF or Calo Jets.

4.5.5.2 Clustering Algorithms

The are two different kinds of clustering algorithms: sequential and cone-type.

Apart from the reconstruction itself, different clustering algorithms of all stable particlesare also available [47], such as sequential (kT [48], [49], [50] and anti kT [51]) and cone-typeclustering (Iterative Cone and SIS Cone [52]).

• Sequential algorithms

They are all based on successive pair-wise recombination of particles (input fourvectors) according to the distance between any two particles i and j, dij, and thedistance of any particle i to the beam, diB , which are defined as:

dij = min(k2pT i, k

2pTj)

∆2ij

D2(4.3)

kiB = k2pT i (4.4)

where ∆2ij = (yi − yj)2 + (φi − φj)2. kT i, yi and φi are respectively the transverse

momentum, rapidity and azimuth of particle i, and D is the parameter for the jetsize. Each clustering algorithm identifies the smallest distance among all dij and diBin the list of input particles, and if it is a dij recombines particles i and j to formone single new particle by adding their four momenta. If the smallest distance is adiB, particle i is removed from the list of particles and called a jet. After each stepall distances are recalculated and the procedure is repeated until no particles are leftto be clustered. The jet size parameter D rescales the distances dij with respect tothe diB such that any pair of final jets a and b are separated by at least ∆2

ab = D2.According to the general definition of the clustering metrics in the equations shownabove, the parameter p, which governs the relative power of energy versus geometricalscales, distinguishes between the jet finders: p = 1 yields the kT algorithm, while p= -1 corresponds to the anti-kT algorithms.

These algorithms are infrared- and collinear safe: neither soft emissions nor collinearsplitting change the result of the clustering, leading to a robust event interpretationin terms of partons and allowing the application of the algorithms in theoreticalcalculations for comparisons with experimental data.

• Cone-type algorithms

41


– ICone. Calorimeter towers and particles with ET > 1 GeV are considered indescending order as starting points (seeds) for an iterative search for stable conessuch that all inputs with

√∆η2 + ∆φ2 ≤ R from the cone axis are associated

with the jet, R being the cone size parameter. A cone is considered stable if itsgeometric center agrees with the (η, φ) location of the sum of the constituentfour vectors within a certain tolerance. Once a stable cone is found, it is declareda jet and its constituents are removed from the remaining inputs. The algorithmis neither collinear nor infrared-safe.

– SISCone. It is based on an iterative procedure to find stable cones as well butin this case using intermediate seeds for the reconstruction. It is collinear andinfrared-safe to all orders of pQCD.

4.5.5.3 Energy Corrections.

It is known that the calorimeter response to particles is not linear and therefore it is notstraightforward to translate the measured jet energy to the true particle or parton energy.The jet corrections [53] are a set of tools that allows the proper mapping of the measuredjet energy deposition to the analysis desired level. CMS has adopted a factorized solutionto the problem of jet energy corrections, where each level of correction takes care of adifferent effect, shown in Figure 4.21. Each level of correction is essentially a scaling of thejet four momentum with a factor depending on various jet-related quantities, such as PT,eta, flavour, etc... and they are applied sequentially with a fixed order. The correctionsused in this analysis are explained more in detail:

• L1. The goal of the L1 correction is to remove the energy coming from pile-upevents. In principle this will remove any dataset dependence on luminosity so thatthe following corrections are applied upon a luminosity independent sample.

• L2. The goal of the L2 Relative correction is to make the jet response flat vs eta. Es-sentially, the uniformity in pseudorapidity is achieved by correcting a jet in arbitraryη relative to a jet in the central region (|η| < 1.3).

• L3. The goal of the L3 Absolute correction is to make the jet response flat vs pT.Once a jet has been corrected for |η| dependence (L2 relative correction), it is cor-rected back to particle level (this means that the corrected caloJet pT is equal onaverage to the genJet pT).

The derivation of these absolute corrections is done either by using MC truth informationor by employing data driven techniques. The energy of jets considered for the analysisdeveloped in this thesis, as well as for any physics analysis to be performed in CMS,has to be corrected. The combination of L1 (pile-up) + L2(Relative) + L3(Absolute)jet corrections is currently the default correction in CMS, and is therefore required here.L2L3Residual corrections are also applied to data to cope for the differences between dataand MC.

42

4.5 Physics Objects

Figure 4.21: Sequential application of the different levels of correction from Reconstructedto Calibrated Jet in CMS.

4.5.5.4 Bottom quark jets tagging.

Jets coming from bottom quark decays are specially interesting since they are used as a toolfor characterizing top quark processes [54]. Two types of b-tagging used in this analysisare:

• Life time based b quark tagging. Rejects events that contain jets tagged as b-jetsexploiting the large life time of the b quark. Several b-tagging discriminators havebeen compared in terms of signal efficiency as a function of tt background rejection(see Fig. 4.22). The trackCountingHighEffBJetTags algorithm is finally used with acut at 2.1 on the discriminator variable. This b-tagger is based on 3D IP significanceof second track in the event. Jets below 10 GeV are not considered for the b-jet veto.

• Softmuon based b quark tagging. This method has been implemented in order toreduce mainly the backgrounds having a third muon from a b quark decay (mainlyand single-top). The softmuon veto requires that in the event there are no muonsfrom b-decays passing the following cuts:

– the muon is reconstructed as TrackerMuon and pass the TMLastSTationAngTightmuon ID.

– the number of hits of the muon in the silicon Tracker is greater than 10

– the transverse impact parameter of the muon with respect to the primary vertexis less than 0.2 cm.

– if pT > 20 GeV then the muon is required to be non-isolated, Iso/pT > 0.1.

4.5.6 Missing Energy

The Missing Energy refers to energy which is not detected by the detector but is expectedbecause of the conservation of energy and conservation of momentum. This energy isgenerally attributed to particles which escape the detector without being detected, suchas neutrinos, although Missing Energy may be caused by mismeasurements of the en-ergy/momentum of the detected particles. In hadron colliders such a LHC the initial

43


Figure 4.22: Performance of the different b-tagging algorithms studied for 7 TeV (top) and8 TeV (bottom)

momentum of the colliding partons along the beam axis is not known, so the amount oftotal Missing Energy cannot be determined. However, the initial energy in particles trav-eling transverse to the beam axis is zero, so any momentum in the transverse directionindicates the presence of ET . As it was said before, Missing Energy is commonly usedto infer the presence of non-detectable particles such as the standard model neutrino andis expected to be a signature of many new physics events. It is estimated by doing thebalance of the deposited energy in the calorimeter system, measuring the vector sum ofraw energy in all ECAL and HCAL towers. The estimation of this variable is not easy,since various effects can contribute to the ET not corresponding to a real physic objectlike a neutrino. These effects degrade the performance and are machine background fromthe accelerator and beam-gas interactions, noisy or dead calorimeter cells or regions, nonlinearity in the hadronic response and finite energy resolution. Different types of MissingET reconstruction are implemented [55]:

• Calorimetric MET (caloMET). Missing ET based on the calorimetric informationonly.

44

4.5 Physics Objects

• Track Corrected MET (tcMET). This correction replaces, for all well reconstructedtracks, the average energy deposition in the calorimeter by the measured momentumin the tracker.

• Particle Flow MET (pfMET). Particle Flow consists in reconstructing and identifyingall stable particles in the event by combining all detectors in the best possible way.The result will be the sum of the transverse energy vectors of all these particles.

4.5.6.1 MVADY : A multivariate technique to reject Drell-Yan Background

The signal events are expected to have large missing transverse energy, as the neutrinosthat come from the W decay cross the detector without leaving any trace of their presence.On the other hand, processes like Drell-Yan or QCD have no physical source of missingtransverse energy. A multivariate technique has been derived to help rejecting such back-ground with a minimal effect on the signal efficiency. This multivariate technique makes abetter use of some of the differences between the Higgs signal and the Drell-Yan backgroundand a complete descripcion can be found in [56]. The list of variables in the training is thefollowing:

• missing energy variables:

- projected PF EmissT projected track Emiss

T

-- PF EmissT /

∑ET

• kinematic variables:

- dilepton pT

- transverse Higgs mass

- leading jet pT

- recoil, which is the magnitude of the vector sum of PF EmissT and the dilepton

system in the transverse plane

• azimuthal angles differences:

- ∆φ(``, j)

- ∆φ(``, EmissT )∆φ(j, Emiss

T )

-• other variables:

- number of primary vertices,

with the projected EmissT as defined in Equation 4.5.

projected =

{if ∆φmin ≥ π

2

sin(∆φmin) if ∆φmin <π2

(4.5)

with ∆φmin = min(∆φ(`1, EmissT ),∆φ(`2, E

missT ))

45


The projected EmissT exploits the large mass difference between the τ and the Z. Due

to this difference taus are produced with large boost and their decay products, includingthe neutrinos, are aligned with the leptons. In such cases the transverse component of themissing energy with respect to the leptons is a better measure of the true missing energyin the event, not originating from τ decays.

46

5

SM Higgs in the WW ∗ decay channel

5.1 Higgs Phenomenology at the LHC

The Large Hadron Collider has been designed to test the TeV scale and solve the Higgsproblem. The Higgs physics at the LHC is different from previous colliders due mainly tothe larger centre of mass energy considered. The nominal collision energy for the LHC is14 TeV, while the second most energetic accelerator built, the Tevatron, had an energy ofabout 2 TeV. Figure 5.1 shows the production cross-sections [57] as a function of centreof mass energy of the Higgs mass for a centre of mass energy of 7 TeV and 8 TeV.

The dominating Higgs production mechanism at the LHC and at any hadron collideris the Gluon Fusion process, and it dominates for all possible Higgs masses. The processgg → H proceeds through triangular heavy quark loops. In the SM, it is dominantlymediated by the top quark loop contribution, with a bottom quark contribution that doesnot exceed the 10% level at leading order.

The second most important production mode is the Vector Boson Fusion qq → qqh+X,the inelastic scattering of two quarks (antiquarks), mediated by t-channel W or Z exchange,with the Higgs boson radiated off the vector bosons. In this case, the Higgs boson isproduced via the fusion of the weak bosons W and Z and is accompanied by two forwardjets that carry large transverse momentum pT in the final state.

The W,Z associated production qq → Wh+X, qq → Zh+X also called Higgstrahlung,is especially important for low masses.

The tt associated production qq, gg → tth+x at the LHC is an important search channelfor Higgs masses below 125 GeV/c2. The single-top associated production qb → bth willalso be accessible and studied in the LHC.

Different strategies for the Higgs identification can be developed depending on its mass.The decaying modes change also dramatically across the possible range of the Higgs mass.Figure 5.2 shows the branching ratios of the different Higgs decay processes depending onthe mass.

47

5. SM HIGGS IN THE WW ∗ DECAY CHANNEL

Figure 5.1: Production cross-sections as a function of Higgs mass at the LHC at a centreof mass energy of 7 TeV (left) and 8 TeV (right).

Figure 5.2: Higgs Branching Ratios as a function of mH

5.2 Higgs Searches in CMS

Since a new Higgs mass range is accesible with the LHC, CMS has designed its strategyin order to optimize the search of a SM Higgs boson in a mass range that starts from thedirect search limit set by LEP, around 114 GeV/c2, especially stressing the masses thatwere not covered by the Tevatron. The main processes studied in CMS in addition to theH → WW are the following:

1. H → ZZ∗: The main advantage of this channel is the clear mass peak from the two Z

48

5.3 The H → WW ∗ process

bosons. The mass resolution is around 1-2% in the case of the two Z bosons decayingleptonically. The mH range covered by this channel is [110-1000] GeV/c2.

2. H → γγ: This channel shows a very clear signature with two isolated high pT photos.It has a clean peak in the diphoton invariant mass but presents a large continousbackground. The mass resolution is around 1-2%. The mH range covered by thischannel is [110-150] GeV/c2.

3. H → bb: This decay channel presents a very high branching ratio. The mass resolu-tion is around 10% and the mH range covered by this channel is [110-135] GeV/c2.

4. H → ττ : This process is sensitive to all production modes and probes the couplingto leptons. The mH range covered by this channel is [110-145] GeV/c2.

5.3 The H → WW ∗ process

The H → W+W− process is particularly sensitive for Higgs boson searches in the interme-diate mass range (120-200 GeV/c2) [58] and has comparable sensitivity in the low Higgsmass region ≈ 130 GeV/c2) as the diphoton channel. This decay can also be studied whenone of the W bosons is off-shell and still stays the dominant mode for higher masses. Inthe Higgs mass region around 160 GeV/c2 the branching ratio to WW becomes close to1 as has been shown in Figure 5.2. The strategy has gone through several updates andimprovements proving the H → WW to be the dominant process since the beginning of theLHC, till the observation hints showed up, excluding by its own a larger mH range than anyother channel. Even for low Higgs masses (≈ 125 GeV/c2) the H → WW contribution tothe Higgs combination result is of crucial importance for the final significance calculation.Figure 5.3 shows the Feynamn diagram of the gluon-fusion H → WW production whereboth W bosons decay leptonically.

Figure 5.3: Feynman diagram of the gluon-fusion induced Higgs to WW ∗ decaying to twoleptons and two neutrinos.

5.4 Signature of signal and background

The signal, H → WW → 2l2ν, presents a very clear signature with two high pT leptonsin the final state, with opposite charge, small opening angle due to spin correlations and asignificant missing ET due to the undetected neutrinos.

49


The backgrounds considered are processes that can present similar signatures: real orfake multi − lepton final states and missing ET . Figure 5.4 shows the Feynman diagramof some of the main background in the H → WW channel.

Figure 5.4: Background processes: qq (a) and gg (b) WW production, Drell-Yan (c), ttproduction (d) and single-top tW (e), other backgrounds would be diboson production (WZ,ZZ, Wγ/γ∗) and W + jets.

• WW → 2l2ν This is one of the main backgrounds. It is studied when both W bosonsdecay leptonically (W → lν). The W decay mode to leptons supposes a fractionof 10.80 %. The experimental signature is the same as for the signal being thus anirreducible background. For the WW the two leptons tend to be produced back toback while in the case of the signal the angle between the two leptons will tend tobe small due to spin correlations. This feature will be exploited to reduce the WWbackground. No much jet activity is expected though it can have jets at the finalstate due to initial/final state radiation, underlying events or WW+jets processeswhich have lower cross-section. The two production modes, qq and gg, are studiedfor this background.

• tt→ 2W + 2jets→ 2l + 2ν + 2jets

The top quark can decay as t→ W + b→ lν + (at least) 1jet, thus this backgroundhas as signature two leptons, missing ET because of the neutrinos and at least twojets. The contribution to the signal can occur when both tops decay leptonically andthe jets coming from the b quarks are lost in the event. It can be reduced usingthe Jet Veto (JV), which consists on rejecting events with more than zero tight jets.Several methods can be implemented to characterize this background such as the bquark tagging . In this analysis both life time and soft lepton based btagging areused.

• tW± → 2l + 2ν + (at least) 1jet

50

5.5 LHC center of mass energy and integrated luminosity scenarios

As explained before the top quark can decay as t → W + b → lν + (at least) 1jet,thus this background has a signature of two leptons, missing ET and at least one jet.The contribution to the signal occurs when one of the jets coming from the b quarkis lost. As in the previous sample this background can be characterized and reducedusing several methods as the Jet Veto and the b quark tagging.

• WZ± → 3l + 1ν, ZZ → 2l + 2ν and Wγ

The contribution of the WZ background predominantly occurs when both bosonsdecay leptonically and one of the leptons escapes detection. This background canbe rejected partially by using a Z − veto by applying a cut to the invariant massreconstructed from the two leptons removing the Z boson mass window and askingfor two and only two leptons (third lepton veto).

The ZZ background mainly contributes when one Z decays leptonically and the otherinvisibly. As in the previous case this background can be reduced using the recon-structed Z mass peak.

The Wγ background, where the photon decays to an electron-positron pair, is ex-pected to be very small, thanks to the stringent photon conversion requirements.

• Z + jets→ ll + jets

It is an instrumental background having in general two leptons in the final state butnot genuine missing ET as there are no neutrinos produced in the Z decay. Howeverdue to mis-measurements or noise in the calorimeter towers and other effects, thisprocess has usually a non negligible value of reconstructed missing ET . It is importantto estimate the contribution of this background to understand and control the tail ofthe missing ET distribution.

• W + jets→ lν + jets

The origin of this background is one jet misidentified as a lepton in the detector. Ithas an even larger cross-section than Z + jets, and requires a detailed control of thefake leptons that can lead to dileptonic final states. The tight− to− loose method isused to estimate this background and will be explained in detail later.

In order to visualize the topology of the event candidates it is possible to use a dedicatedtool available in CMS, the Physics Analysis Oriented Event Display Fireworks. In figures5.5 and 5.6 the event displays for a HWW candidate and a WW candidate are shown.The already mentioned difference in the angular separation between the two leptons in thecase of the signal and of the WW background can be clearly seen in these figures.

5.5 LHC center of mass energy and integrated lumi-

nosity scenarios

Before the start of the LHC several benchmark energies and luminosities were planned. Ini-tially, a high energy LHC start-up was expected, and the analsis was originally conceived

51


Figure 5.5: Event displays of a Higgs to WW candidate with mH = 125 GeV/c2 decayingto two muons at

√s = 8 TeV

for the LHC design centre of mass energy of 14 TeV assuming 1 fb−1 of integrated lumi-nosity. After the incident in 2008 the LHC start was delayed and the plan was revisited.One of the benchmarks presented in the LHC Performance Workshop at Chamonix in 2009was an integrated luminosity of 200 pb−1 at

√s = 10 TeV. The analysis was optimized and

52

5.5 LHC center of mass energy and integrated luminosity scenarios

Figure 5.6: Event display of a WW candidate decaying to two muons at√s = 8 TeV

performed based on MC only for this scenario. Finally, in the LHC Performance Workshopat Chamonix in 2010, the definite first run conditions were announced and the analysis wasadapted to an integrated luminosity of 1 fb−1 at

√s = 7 TeV.

53


5.6 Datasets and triggers

The dataset used for this thesis corresponds to 4.9 fb−1 for 2011 and 19.6 fb−1 for 2012composed of six data-taking periods: 2011A (2209 pb−1), 2011B (2712 pb−1), 2012A (892pb−1), 2012B (4404 pb−1), and 2012C (7032 pb−1) and 2012D (7273 pb−1). Given the ee, µµ,µe and eµ final states considered in this analysis, the following five Primary Datasets havebeen used for the signal extraction: SingleElectron, SingleMu, Double Electron, DoubleMuand MuEG (Muon-ElectronGamma). For both 2011 and 2012 analysis only the subset ofruns and luminosity blocks which have passed all the quality tests of the Physics ValidationTeam (PVT) are considered. Figure 5.7 shows the final integrated luminosity delivered toCMS at the end of the 2010, 2011 and 2012 data taking.

Figure 5.7: Final integrated luminosity for the full 2010 (left), 2011 (center) and 2012 (right)data taking period.

5.6.1 Datasets

5.6.1.1 2011 period datasets

The 2011 analysis uses exclusively events from the datasets listed in Table 5.1. The full2011 dataset corresponds to 4.9 fb−1 of integrated luminosity of pp collisions.

5.6.1.2 2012 period datasets

For the 2012 analysis only datasets listed in Table 5.2 are used. The full 2012 datasetcorresponds to 19.6 fb−1 of integrated luminosity of pp collisions.

5.6.2 Monte Carlo Samples used in the analysis

The 2011 analysis is based on the 42X CMSSW version while the 53X version is used for the2012 analysis. Three different generators were used for the various samples: Higgs signalsamples were generated with POWHEG [59] while background samples were generated witheither PYTHIA [60], POWHEG or MADGRAPH [61]. All generated events were passedto PYTHIA for fragmentation and hadronization before simulation and reconstruction in

54

5.6 Datasets and triggers

Table 5.1: Datasets used to analyze 2011 data.

/SingleElectron/Run2011A-***/AOD/SingleMu/Run2011A-***/AOD

/DoubleElectron/Run2011A-***/AOD/DoubleMu/Run2011A-***/AOD

/MuEG/Run2011A-***/AOD/SingleElectron/Run2011B-PromptReco-v1/AOD

/SingleMu/Run2011B-PromptReco-v1/AOD/DoubleElectron/Run2011B-PromptReco-v1/AOD

/DoubleMu/Run2011B-PromptReco-v1/AOD/MuEG/Run2011B-PromptReco-v1/AOD

*** == PromptReco-v[4,6], May10ReReco-v1, 05Aug2011-v1

Table 5.2: Datasets used to analyze 2012 data.

/SingleElectron/Run2012A-PromptReco-v1/AOD/SingleMu/Run2012A-PromptReco-v1/AOD

/DoubleElectron/Run2012A-PromptReco-v1/AOD/DoubleMu/Run2012A-PromptReco-v1/AOD

/MuEG/Run2012A-PromptReco-v1/AOD/SingleElectron/Run2012B-PromptReco-v1/AOD

/SingleMu/Run2012B-PromptReco-v1/AOD/DoubleElectron/Run2012B-PromptReco-v1/AOD

/DoubleMu/Run2012-PromptReco-v1/AOD/MuEG/Run2012B-PromptReco-v1/AOD

55


the CMS detector. References about the whole simulated dataset used in this analysis canbe found in [62] for 2011 analysis and in [63] for the 2012 analysis.

5.6.3 Triggers

For the data samples, the events are required to fire one of the unprescaled triggers listedin table 5.3 for the 2011 analysis and table 5.6 for the 2012 analysis. Tables 5.4 and 5.7show the trigger paths used for the fake rate studies for 2011 and 2012 respectively. Thetrigger efficiencies have been studied using the paths in Tables 5.5 and 5.5.

Table 5.3: Trigger paths used to select events in data for the 2011 analysis.

run range trigger pathsSingleElectron

160404-164237 HLT Ele27 CaloIdVT CaloIsoT TrkIdT TrkIsoT165085-166967 HLT Ele32 CaloIdVT CaloIsoT TrkIdT TrkIsoT166968-170901 HLT Ele52 CaloIdVT TrkIdT170902-178419 HLT Ele65 CaloIdVT TrkIdT178420-180252 HLT Ele80 CaloIdVT TrkIdT

SingleMu160404-163261 HLT Mu15163262-165099 HLT Mu24165102-173235 HLT Mu30173236-175972 HLT Mu40175973-180252 HLT Mu40 eta2p1163262-170901 HLT IsoMu17171050-175910 HLT IsoMu2017591160404-175921 HLT IsoMu24175922-180252 HLT IsoMu24 eta2p1

DoubleElectron160404-170901 HLT Ele17 CaloIdL CaloIsoVL Ele8 CaloIdL CaloIsoVL171050-180252 HLT Ele17 CaloIdT CaloIsoVL TrkIdVL TrkIsoVL Ele8

CaloIdT CaloIsoVL TrkIdVL TrkIsoVLDoubleMu

160404-165208 HLT DoubleMu7165364-178419 HLT Mu13 Mu8178420-180252 HLT Mu17 Mu8178420-180252 HLT Mu17 TkMu8

MuEG160404-175972 HLT Mu17 Ele8 CaloIdL175973-180252 HLT Mu17 Ele8 CaloIdT CaloIsoVL160404-167913 HLT Mu8 Ele17 CaloIdL167914-180252 HLT Mu8 Ele17 CaloIdT CaloIsoVL

5.7 Multiple interactions reweight

The simulated samples were produced mixing multiple minimum bias interactions (pile-up). As the luminosity of the LHC is constantly changing, the simulation samples mustbe reweighted to adapt to the LHC conditions. For a given range of analyzed runs, thenumber of pile-up interactions per bunch crossing is estimated per luminosity block using

56

5.7 Multiple interactions reweight

Table 5.4: Trigger paths used in data for studying fake rates.

lepton flavor trigger paths

muon fakesHLT Mu8HLT Mu15HLT Mu24

electron fakesHLT Ele8 CaloIdL CaloIsoVLHLT Ele17 CaloIdL CaloIsoVL

Table 5.5: Trigger paths used in data for studying trigger efficiencies.

lepton flavor trigger pathsmuon efficiency HLT Mu8 v1

electron efficiencyHLT Ele17 CaloIdVT CaloIsoVTTrkIdT TrkIsoVT SC8 Mass30

HLT Ele32 CaloIdT CaloIsoT TrkIdT TrkIsoT SC17

Table 5.6: Trigger paths used to select events in data for the 2012 analysis.

run range trigger pathsSingleElectron

190456-208686 HLT Ele27 WP80SingleMu

190456-208686 HLT IsoMu24 eta2p1DoubleElectron

190456-208686 HLT Ele17 CaloIdT CaloIsoVL TrkIdVL TrkIsoVLEle8 CaloIdT CaloIsoVL TrkIdVL TrkIsoVL

DoubleMu190456-208686 HLT Mu17 Mu8190456-208686 HLT Mu17 TkMu8

MuEG190456-208686 HLT Mu17 Ele8 CaloIdT CaloIsoVL TrkIdVL TrkIsoV190456-208686 HLT Mu8 Ele17 CaloIdT CaloIsoVL TrkIdVL TrkIsoV

Table 5.7: Trigger paths used in data for studying fake rates.


muon fakesHLT Mu8HLT Mu17

electron fakesHLT Ele8 CaloIdL CaloIsoVLHLT Ele17 CaloIdL CaloIsoVL

57


Table 5.8: Trigger paths used in data for studying trigger efficiencies.


muon efficiency

HLT IsoMu24 eta2p1HLT IsoMu30 eta2p1HLT Mu40 eta2p1HLT Mu50 eta2p1

electron efficiency HLT Ele27 WP80

the instantaneous luminosity provided by the LHC, integrated over the entire run range andnormalized. This distribution is then used to reweight the simulated pile-up distribution.Only the in-time pile-up distribution in the Monte Carlo is used to reweight the events. InFigure 5.8 the data and simulation distributions of the number of reconstructed primaryvertices are compared for 2011 and 2012 dataset, where the reweighting has being applied.The plots are done requiring only two identified and isolated leptons to enhance the Z+jetscontent of the sample. A good agreement between data and MC is observed assuring thecorrect description of pile-up events.

Figure 5.8: Distribution of the number of vertices after the simulation has been pile-upreweighted: 2011 data period (left) and 2012 data period (right).

58

6

Event selection and backgroundestimation using data driven methods

The major backgrounds in the analysis present a production cross section several orders ofmagnitude higher than the Standard Model Higgs signal. Additionally, the Higgs signal hasto be separated from the almost irreducible non-resonant W+W− background continuum.As it was already mentioned fully leptonic signature includes two prompt, isolated leptonsand large missing energy due to the undetected neutrinos. The events are classified in threedifferent categories depending on the number of high pT jets in the final state. For eachcategory the events are split in same flavour (µµ and ee) and different flavour (eµ and µe).The first lepton using this notation always refers to the most energetic one.

The selection is divided in two steps. The first one selects W+W− like events, rejectingmainly Z and top backgrounds. This selection is common to all Higgs mass hypotheses andis used as a control region where one can verify the background prediction without beingaffected by signal contamination. The second step consists on a selection optimized withrespect to the Higgs mass in order to achieve the best separation of the Higgs signal fromthe backgrounds

6.1 Common WW selection

1. Lepton selection

Events with two leptons (electrons or muons) are selected. The lepton selection isoptimized to obtain a performant lepton identification in high luminosity conditions.

Muons:

• pT > 20 GeV/c for the leading lepton. For the trailing lepton, the transversemomentum is required to be larger than 15 GeV for ee and µµ at 7 TeV, andlarger than 10 GeV otherwise.

• |η| < 2.4.

• Number of tracker inner hits > 10, with at least one hit in the Pixel detector.

• Global fit χ2/n.d.o.f < 10. This is a powerful tool to reject both decays in flightand punch-through [64].

59

6. EVENT SELECTION AND BACKGROUND ESTIMATIONUSING DATA DRIVEN METHODS

• Impact parameter in the transverse plane |d0|< 0.02 cm for muons with pT greaterthan 20 GeV, calculated with respect to the primary vertex. This cut providesan efficiency for prompt muons higher than 93% for pT > 20 GeV, while rejectsa 87% of fake muons.

• Longitudinal impact parameter |dz| < 0.1 cm, calculated with respect to theprimary vertex. This cut, together with the previous one, ensures the muonsare coming from the W decay and the hard-scattering event. Also, it ensuresthe selection of events coming from the primary vertex.

• Relative pT resolution better than 10%. This requirement reduces the numberof Z → µµ events where one of the muons is poorly measured and moves off thedimuon mass peak, providing a fake missing transverse energy.

• Kink-finder algorithm χ2/n.d.o.f < 20. This algorithm looks for kicks along thereconstructed muon trajectory, to remove decay-in-flight particles. The cut isapplied in the largest χ2 per track leading to a fake background reduction ofabout a 5% with practically no signal loss.

To further reduce the muon fakes due to jet contamination, isolation is required. Forthis purpose, a MVA based algorithm is used (see section 4.5.2.2).

Electrons:

Electron reconstruction is explained in detail in section 4.5. A first identificationis done using a multivariate (MVA) approach, specifically a Boosted Decision Tree(BDT) method. The training of the multivariate algorithm is performed with observ-ables used in a standard cut based selection of the electrons:

• |η| < 2.5

• σiηiη: Supercluster η width, as taken from the covariance matrix using logarith-mic weights. Practically unaffected by the spreading due to the magnetic fieldof the showering in the tracker material.

• ∆ηin: Distance in η plane between the track and the supercluster.

• ∆φin: Distance in φ plane between the track and the supercluster.

• fbrem: the fraction of the total momentum carried away by bremsstrahlung.

• σiφiφ: Supercluster φ width.

• Number of additional clusters from bremsstrahlung.

• 1/Esupercluster - 1/pGSFTrack.

After the pre-selection with the MVA method, further requirements are applied to theelectrons, making sure that they are tighter than trigger selection to avoid possiblebias:

• pT > 20 GeV and |η| < 2.5.

• σiηiη < 0.15/0.03 (barrel/endcap) electrons.

60

6.1 Common WW selection

• |∆φin| < 0.15/0.010 and |∆ηin| < 0.007/0.009.

• H/E < 0.12/0.10, with H (E) the energy deposited in the HCAL (ECAL).

• Σtrk ET/pT < 0.2, ΣECAL ET/pT < 0.2 and ΣHCAL ET/pT< 0.2.

As for muons, isolation cuts are applied to reduce as much as possible fake con-tributions. The Particle Flow isolation is used, see Section 4.5.3.2. The isolationrequirement is IsoPF/pT< 0.13 (0.09), for barrel (endcap) electrons.

To reduce fake electrons from non-prompt sources, the transverse and longitudinalimpact parameters with respect to the primary vertex must be less than 0.02 and 0.1cm respectively.

Apart from the electron fakes coming from misidentified jets, another source areelectrons produced by photon conversion, due to the large material budget of theCMS tracking system [65][66]. Electrons from photon conversions can constituteapproximately 15 - 35% in QCD. They will have, on average, a longer transversedistance from the beam spot, d0, than prompt electrons. While the photon conversionshould occur in the budget material, the prompt electrons come from the beam pipe,see Figure 6.1.

Figure 6.1: Right side shows the impact parameter d0 for an electron product of a photonconversion. On the left side, the corresponding for a prompt electron.

The first valid hit of the track for a photon converted electron may not necessarily belocated in the innermost tracker layer, so extrapolating this track back to the beamline, one could find detector layers which do not have hits compatible with the track.In order to veto these converted electrons, than can lead to an increase of the numberof fakes, a conversion vertex is performed with two tracks, one being compatible withan electron. The vertex fit probability is required to be higher than 10−6. Also, theelectron candidates must not have missing expected hits in their track.

2. Extra lepton veto: the event is required to have two and only two opposite-signleptons passing the lepton selection.

3. EmissT preselection: PF Emiss

T > 20 GeV.

4. Low mass resonances rejection: m`` > 12 GeV and m`` > 20 GeV for ee and µµ at 7TeV.

5. Z-peak veto: |m`` −mZ| > 15 GeV for ee and µµ events.

61


6. Soft projected EmissT selection: themin(projected PFEmiss

T ,projected track EmissT ),with

the two type of missing transverse energies described in 4.5, is required to be largerthan 20 GeV. For the 7 TeV analysis, the MET cut depends on the number of vertex.min(projected PF Emiss

T ,projected track EmissT ) is required to be larger than (37 +

Nvtx/2) GeV for ee and µµ events, with Nvtx the number of vertices in the event.

7. Azimuthal separation between the dilepton system and the (di)jet:

- 0/1-jet bins, 7 TeV analysis: ∆φ(``, jet) < 165 degrees for jets with pT > 15GeV.

- No selection is applied for the 8 TeV analysis in the 0/1-jet bins

8. Soft muon veto: the event is required to not have soft muons likely to come fromb-jets.

9. Anti b-tagging: the event is required to not have any jet passing the b-tagging selec-tion.

10. Kinematical cut: the event is required to have p``T > 30(45) GeV for the shape (cutbased) analysis.

11. Hard EmissT selection at 8 TeV: a multivariate approach to reject the remaining DY

is applied in the 0/1-jet bins.

- 0-jet bin: MVADY > 0.88

- 1-jet bin: MVADY > 0.84

The lepton selection reduces the background from W+jets events and almost completelyremoves events from QCD. The extra lepton veto suppresses the di-boson ZZ and ZWbackgrounds, while the low mass resonances cut rejects J/ψ and Υ events. After these cutsthe dominant background is Drell-Yan, which is heavily suppressed by the Z-peak vetoand the cuts on Emiss

T related variables. While a large fraction of the top background issuppressed by a series of b-jet veto criteria, a sizeable contribution from single top and ttproduction remains in 1 jet bin. The rest of the events after the full set of mH independentselection cuts are W+W−background.

6.2 mH dependent analysis

After all the cuts in the WW selection level have been applied, two different approachesare used in order to discriminate against the remaining background: a straightforward cut-and-count experiment using a dedicated selection depending on the Higgs mass hypothesisor a single variable shape analysis based on some of the kinematical variables with thegreater discriminating power: mll, mT and the unboosted Razor variable 2MR [67] [68].

62


6.2.1 Cut based analysis

6.2.1.1 7 TeV analysis

The following handles are used to discriminate against the remaining background, speciallythe WW continuum. Table 6.1 shows the cut values for the different Higgs masses.

• Lower cut on the transverse momentum of the leading and trailing leptons.

• Upper cut on the invariant mass of the lepton-pair.

• The angle ∆φ`` between the two selected leptons in the transverse plane. This variableprovides the best discriminating power between the Higgs signal and the majority ofthe backgrounds in the low Higgs mass range. Leptons originating from H → WWdecays tend to have a relatively small ∆φ`` opening angle due to spin correlations,while those from backgrounds are preferentially emitted back-to-back. The impor-tance of this variable decreases for high masses, since the boost of the W bosonsdilutes the angular correlation.

• The Higgs transverse mass mT, computed with the two leptons and the missingenergy:

mT =√

2p``TEmissT [1− cos(∆φ``−Emiss

T)]

Where ∆φ``−EmissT

is the angle between the dilepton system direction and the EmissT

in the transverse plane.

6.2.1.2 8 TeV analysis

In the case of the 8 TeV analysis, the same handles were used for the mass dependentanalysis but with some small changes. Some of the low mass Higgs hypothesis wereremoved since the analysis was mainly focused in the mH =125 GeV region afterthe hints of a Higgs boson around that mass appeared at the end of the 7 TeV datataking. Table 6.2 shows the cut values for the different Higgs masses.

6.2.2 MVA analysis

Multivariate discriminant using Boosted Decision Tree (BDT) algorithm have beenthe most performant shape analysis since 2011 to set exclusion limits across a widemass range. The BDT algorithm has been implemented in TMVA [69] and has beenchosen among all the possible multivariate techniques since it requires less trainingand is insensitive to poorly discriminating input variables.

This MVA approach was first used applying a cut maximizing the signal to back-ground ratio to the output distribution of the BDT. As the analysis evolved, the fullshape of the classifier output started to be used as the final discriminant variable.Even if the BDT are wildely used in High Energy Physics to discriminate signal tobackground in classification problems. In this analysis it has been shown that the dis-crimination power of a single variable such as mll is comparable with respect to those

63


Table 6.1: Cut-based selection for events in the 0- and 1-jet bins for the 7 TeV analysis.The cuts in parenthesis are applied only to the same flavor final states.

mH pTlead pT

trail m`` ∆φ`` mT

[GeV/c2] [GeV/c] [GeV/c] [GeV/c2] [◦] [GeV/c2]110 > 20 > 10 (15) < 40 < 115 [ 80 - 110]115 > 20 > 10 (15) < 40 < 115 [ 80 - 110]118 > 20 > 10 (15) < 40 < 115 [ 80 - 115]120 > 20 > 10 (15) < 40 < 115 [ 80 - 120]122 > 21 > 10 (15) < 41 < 110 [ 80 - 121]124 > 22 > 10 (15) < 42 < 105 [ 80 - 122]126 > 23 > 10 (15) < 43 < 100 [ 80 - 123]128 > 24 > 10 (15) < 44 < 95 [ 80 - 124]130 > 25 > 10 (15) < 45 < 90 [ 80 - 125]135 > 25 > 12 (15) < 45 < 90 [ 80 - 128]140 > 25 > 15 < 45 < 90 [ 80 - 130]150 > 27 > 25 < 50 < 90 [ 80 - 150]160 > 30 > 25 < 50 < 60 [ 90 - 160]170 > 34 > 25 < 50 < 60 [110 - 170]180 > 36 > 25 < 60 < 70 [120 - 180]190 > 38 > 25 < 80 < 90 [120 - 190]200 > 40 > 25 < 90 < 100 [120 - 200]250 > 55 > 25 < 150 < 140 [120 - 250]300 > 70 > 25 < 200 < 175 [120 - 300]350 > 80 > 25 < 250 < 175 [120 - 350]400 > 90 > 25 < 300 < 175 [120 - 400]450 > 110 > 25 < 350 < 175 [120 - 450]500 > 120 > 25 < 400 < 175 [120 - 500]550 > 130 > 25 < 450 < 175 [120 - 550]600 > 140 > 25 < 500 < 175 [120 - 600]

from the multivariate techniques. The use of a variable like the dilepton invariantmass provides an easy and direct physical interpretation of the final result.

After the 5σ observation it was decided to run the LHC till the end of the yearwith an expectation of having more than 20 fb−1 for each of the two experiments.This luminosity was intended to allow the study of the properties of the recentlydiscovered boson in more detail. In the H → WW final state several posibilitieshave been checked to maximize the final significance. In addition, to establish thepresence of the standard model Higgs signal this final state allows us to check thedifferent spin hypothesis. One posibility to make this study consists in adding to themll another variable as mT. The details of the 2D shape analysis can be found in B.

For the 7 TeV analysis, in addition to the WW preselection, loose cut on the maximummll is applied to enhance the signal-to-background ratio shown in Table 6.3 and a cuton mT > 80 GeV/c2 to supress the DY → ττ and W +γ backgrounds. In addition tothe selection variables for the cut-based analysis, the multivariate signal extraction

64


Table 6.2: Cut-based selection for events in the 0- and 1-jet bins for the 8 TeV analysis.The cuts in parenthesis are applied only to the same flavor final states.

mH pTlead pT

trail m`` ∆φ`` mT

[GeV/c2] [GeV/c] [GeV/c] [GeV/c2] [◦] [GeV/c2]110 > 20 > 10 < 40 < 115 [ 80 - 110]115 > 20 > 10 < 40 < 115 [ 80 - 110]120 > 20 > 10 < 40 < 115 [ 80 - 120]125 > 22 > 10 < 42 < 115 [ 80 - 122]130 > 25 > 10 < 45 < 90 [ 80 - 125]135 > 25 > 10 < 45 < 90 [ 80 - 128]140 > 25 > 15 < 45 < 90 [ 80 - 130]145 > 25 > 15 < 45 < 90 [ 80 - 130]150 > 27 > 25 < 50 < 90 [ 80 - 150]155 > 27 > 25 < 50 < 90 [ 80 - 150]160 > 30 > 25 < 50 < 60 [ 90 - 160]170 > 34 > 25 < 50 < 60 [110 - 170]180 > 36 > 25 < 60 < 70 [120 - 180]190 > 38 > 25 < 80 < 90 [120 - 190]200 > 40 > 25 < 90 < 100 [120 - 200]250 > 55 > 25 < 150 < 140 [120 - 250]300 > 70 > 25 < 200 < 175 [120 - 300]350 > 80 > 25 < 250 < 175 [120 - 350]400 > 90 > 25 < 300 < 175 [120 - 400]450 > 110 > 25 < 350 < 175 [120 - 450]500 > 120 > 25 < 400 < 175 [120 - 500]550 > 130 > 25 < 450 < 175 [120 - 550]600 > 140 > 25 < 500 < 175 [120 - 600]700 > 140 > 25 < 600 < 175 [120 - 700]800 > 140 > 25 < 700 < 175 [120 - 800]900 > 140 > 25 < 800 < 175 [120 - 900]1000 > 140 > 25 < 900 < 175 [120 - 1000]

procedure uses the following ones:

– ∆R ≡√

∆η2ll + ∆φ2

ll between the leptons.

– Lepton flavors (µµ, ee, eµ or µe)

– For the 1-jet bin, the azimuthal angles between the dilepton system and EmissT ,

and between the dilepton system and the highest pT jet, are included

– m < mH.

The training has been carried out separately in the 0-jet and 1-jet bins for differentHiggs masses using the corresponding signal samples. The training is performed todiscriminate Higgs signal events from the dominant irreducible background WW.Using other backgrounds for the training is fairly complicated due to the lack of

65


mH (GeV/c2) <=120 130 140 150 160 170 180 190 200 210mll (GeV/c2) 70 80 90 100 100 100 110 120 130 140

mH (GeV/c2) 220 230 250 300 350 400 450 500 550 600mll (GeV/c2) 150 230 250 300 350 400 450 500 550 600

Table 6.3: mll upper limits requirement as a function of the Higgs mass. These samples areemployed in the training of the multivariate classifier used for the signal extraction.

samples with a large enough number of events. The tests performed did not showany significant benefit in training against backgrounds other than WW (see [63]).

The same BDT method using a loose mass-dependent selection has been tested for2012 data and found to show good performance [62].

6.2.3 Single variable shape analysis

The single variable analysis is based on the 1D shape of different physical variables:the invariant mass of the two leptons (mll), the transverse mass (mT) and an un-boosted Razor variable (2MR). For the 7 TeV analysis the shape of the BDT outputhas also been used. The preselection for this study consists of the WW selectiondescribed in Sec. 6.1. The final result is then calculated applying some loose mH

dependent cuts on the pllT, mT and mll. These additional cuts can be seen in Table6.4

Table 6.4: Additional cuts for the single variable shape analysis after the WW selection.

mH [GeV/c2] mT [GeV/c2] mll [GeV/c2] pllT [GeV/c]≤ 250 [60 - 280] < 200 > 30≥ 300 [80 - 380] < 450 > 30

In order to improve the analysis, an approach using the mll shape applying the fullsequential analysis selection except for the cuts on the m`` variable itself has alsobeen studied. The goal of this approach is to maintain as much discriminating poweras possible without distorting too much the shape of the variable used for the signalextraction. All backgrounds are estimated with the techniques described in Sec. 6.3and then propagated for each Higgs mass dedicated selection.

6.2.3.1 Comparison between the different shape approaches with 2011data

The use of single variables for the shape analysis, to be compared with the combinedBDT output, was studied at the beginning of 2011. The luminosity taken into accountfor this study is 1.5 fb−1. The shapes used are the BDT output, ∆φll, mT, the Razorvariable and mll. To understand which shape has the largest discrimination power,the mean expected limits for the low mass range (120, 130 and 140 GeV/c2) have

66


been calculated. They are given in Table 6.6 and shown in Figure 6.2. These resultsare calculated at the WW level, including the loose m`` cuts given in Table 6.5.For the 0-jet bin the Razor variable is the one giving the best discriminating power,after the BDT output. In the case of the 1-jet bin, mT and m`` present the bestperformance. The Razor variable as it is currently defined does not give competitiveresults in the 1-jet bin, where there are three hard objects instead of two. Theseresults already show that it is possible to perform an analysis with better sensitivitythan the cut-based analysis using the shape of a single variable.

Table 6.5: m`` upper limits and mT range requirements as a function of the Higgs mass,used on top of the WW level selection to preselect the samples entering the shape analysisfor the 7 TeV analysis.

mH [GeV/c2] m`` < [GeV/c2] mT > [GeV/c2] mT < [GeV/c2]110 50 80 110115 60 80 115120 70 80 120130 80 80 130140 90 80 140150 100 80 150160 100 80 160170 100 80 170180 110 80 180190 120 80 190200 130 80 200250 250 80 250300 300 80 300350 350 80 350400 400 80 400450 450 80 450500 500 80 500550 550 80 550600 600 80 600

Table 6.6: Mean expected limits for the different shapes using BDT and single variables,together with the cut-based.

0-jet bin

mH [GeV/c2] BDT ∆φ`` mT Razor m`` cut-based120 1.90 4.51 2.92 2.75 2.85 2.90130 1.01 2.09 1.49 1.39 1.49 1.48140 0.66 1.21 0.97 0.92 1.00 0.92

1-jet bin


67


Figure 6.2: Mean expected limits for the different shapes using BDT and single variablesfor the 0 jet bin (top) and 1 jet bin (bottom), together with the cut-based, with respect tothe Higgs mass.

As it was mentioned previously it is possible to further improve the sensitivity ofthe single variable shapes by adding some additional preselection cuts. The followingresults have been calculated using the full cut-based requirements (see Section 4 in[70]) but removing the cut in the variable to be studied. In the case of the Razorvariable, all cuts but the mll one are applied, due to the strong correlation betweenRazor and mll. Also the tight mT cut has been replaced with a looser cut, mT > 80GeV/c2 for all masses. The results for the BDT case are still at the WW level. Themedian expected limits are summarized both in Table 6.7 and in Figure 6.3. Theselimits show that it is possible to improve the discrimating power of the single variableshapes by applying a preselection. In the case of the 0-jet bin, the Razor variable

68

6.3 Background estimation using data driven methods

presents again the best performance. In the 1-jet bin both mll and mT give the bestresult.

Table 6.7: Mean expected limits for the different shapes at the final selection level, removingthe cut in the variable studied. The results for the BDT and the cut-based are also shown.

0-jet bin


1-jet bin


6.3 Background estimation using data driven meth-

ods

6.3.1 Drell-Yan background

The Drell-Yan contribution is estimated from data, measuring the amount of eventsin a Higgs signal-free control region, and then propagating this number to the signalregion using Monte Carlo. The control and signal regions are defined based on thedilepton invariant mass. The contribution in the control region from processes otherthan DY is estimated from the number of e±µ∓events. The correction factor k, definedin Equation 6.1, is applied on the sum of the ee and µµ final states, to normalize therelative efficiencies for electrons and muons.

k =1

2·

√N controlee

N controlµµ

+

√N controlµµ

N controlee

(6.1)

The number of events measured in the control region is propagated to the signalregion in the following way,

N signal,dataDY =

(N control,data`` − k ·N control,data

eµ −N control,MCZV

)·Rout/in

MC

(6.2)

Rout/inMC ≡ N control,MC

DY

N signal,MCDY

with N control,MCZV the expected peaking ZZ and ZW contributions, estimated from

simulation. To measure Rout/inMC and not run out of statistics the analysis selection

without the mT cut is applied.

69


Figure 6.3: Mean expected limits for the different shapes for the 0-jet bin (top) and 1-jetbin (bottom) at the final selection level, removing the cut in the variable studied.

The value of Rout/inMC is estimated applying a relaxed selection with respect to the

nominal one. The selections listed in Table 6.8 are used.

The nominal value of Rout/inis estimated using the values in the third column ofTable 6.8. For both the low and the high mass selection in case of lack of statisticsthe estimate is done with a relaxed selection. A systematics is associated to theRout/inestimate corresponding to the difference between the value obtained with theused selection and the one in column N-1 of Table 6.8.

To estimate the number of Drell Yan in the in-peak and out-peak region in datathe number of WZ, ZZ expected events in simulation and the number of oppositeflavor events in the same region in data (the remaining backgrounds are symmetricin opposite and same flavor) is subtracted. In the Emiss

T bin used for Rout/inestimation

70

6.4 Top backgrounds

Table 6.8: Top: bins in min(projected PF EmissT ,projected track Emiss

T )used for theRout/inestimate in the 7 TeV analysis. Bottom: bins in MVADY used for the Rout/inestimatein the 8 TeV analysis. The nominal analysis cut is MVADY > 0.88 in the 0 jet bin andMVADY > 0.84 in the 1 jet bin at 8 TeV.

jet bin bin 0 bin 1 bin 2 signal region0, 1 (7 TeV) : min(p-met) – – 30, (37 + Nvtx/2) GeV >(37 + Nvtx/2)

0, 1 (8 TeV) : MVADY -0.9, -0.85 -0.86, -0.6 -0.6, 0.88 (0.84) > 0.88 (0.84)

a good statistical agreement is found.

The Rout/inMC values estimated applying the Higgs selection (excluding the mT cut) are

presented in Figure 6.4 at 8 TeV, for three reference Higgs mass points (mH = 115,

130, 160 GeV). The Rout/inMC estimations for several Higgs masses, together with the

yields estimated on data are summarized in Table 6.9 and 6.10.

6.3.2 Drell-Yan to ττ background

The low threshold in e±µ∓ final state requires the consideration of the contribu-tion from Z/γ∗ → τ+τ− that is estimated from data. This is accomplished byusing Z/γ∗ → µ+µ−events and replacing muons with a simulated τ → lντ νe decay.Recorded collisions are used if they have been selected by the lowest unprescales sin-gle muon trigger at the time without any isolation requirement on the isolation ofthe muon. Events with two opposite charged muons are selected. The two muonsare required to fullfil the isolation requirements and to have an invariant mass insidede Z mass window (60 GeV ≤ mµµ ≤ 120 GeV). Once the pure Z → µµ sample isselected from data the muons are removed from the event and replaced by τ leptons.After replacing muons from Z/γ∗ → µ+µ− decays with simulated τ decays, the set ofpseudo τ → lντ νe events undergoes the reconstruction step. This method has beenfoun to describe all the relevant kinematic distributions very well when comparing theembedded sample whith a Monte Carlo based sample. [71] The global normalizationof pseudo Z/γ∗ → τ+τ−events is checked in the low mT spectrum where a ratherpure Z/γ∗ → τ+τ−sample is expected.

6.4 Top backgrounds

The general strategy for determining the residual top events in the signal region isto first measure the top tagging efficiencies from an orthogonal region of phase spacein data. Then, using this efficiency, propagate from the control region defined as theinversion of one of the top rejection cuts in that particular jet bin (see below). Thenumber of surviving top events would then be:

N signalbveto = N control

btag · 1− εtop

εtop

(6.3)

71


Figure 6.4: RatioRout/infor µµ and ee combined, in Drell-Yan simulation and data. Selectionfor mH = 115 GeV (top), selection for mH = 125 GeV (center) and selection for mH =160 GeV (bottom). 0-jet bin (left) and 1-jet bin for 8 TeV (right).

72

6.4 Top backgrounds

Table 6.9: Estimation of the Drell-Yan background at the Higgs selection level, for various

Higgs masses at 7 TeV. The first uncertainty on Rout/inMC represents the statistical uncertainty in

the simulation. The second value is the systematic uncertainty due to the MET dependency.

0-jet bin

mH [GeV] ndatain RMC ndataDY nMCDY

110 50 0.05 ± 0.03 ± 0.10 1.75 ± 3.64 0.58 ± 0.42115 50 0.05 ± 0.03 ± 0.10 1.75 ± 3.64 0.58 ± 0.42120 71 0.05 ± 0.03 ± 0.10 2.15 ± 4.48 0.58 ± 0.42125 42 0.15 ± 0.08 ± 0.19 3.09 ± 3.79 1.21 ± 0.61130 29 0.26 ± 0.14 ± 0.26 3.30 ± 4.54 1.21 ± 0.61135 31 0.26 ± 0.14 ± 0.26 3.97 ± 5.31 1.21 ± 0.61140 33 0.26 ± 0.14 ± 0.26 4.39 ± 5.02 1.21 ± 0.61145 42 0.26 ± 0.14 ± 0.26 5.21 ± 5.95 1.21 ± 0.61150 36 0.38 ± 0.08 ± 0.16 8.23 ± 3.93 0.62 ± 0.45155 40 0.38 ± 0.08 ± 0.16 8.59 ± 4.11 0.62 ± 0.45160 10 0.86 ± 0.28 ± 0.06 2.74 ± 1.70 0.62 ± 0.45170 9 0.92 ± 0.34 ± 0.13 3.00 ± 1.71 0.38 ± 0.38180 13 0.58 ± 0.22 ± 0.31 1.65 ± 1.45 0.38 ± 0.38190 34 0.36 ± 0.11 ± 0.22 4.67 ± 3.25 0.38 ± 0.38200 46 0.12 ± 0.09 ± 0.07 1.05 ± 1.11 0.38 ± 0.38250 76 0.03 ± 0.02 ± 0.03 0.05 ± 0.20 0.15 ± 0.14300 50 0.17 ± 0.11 ± 0.12 -0.22 ± 0.84 0.46 ± 0.32

1-jet bin


110 55 0.06 ± 0.01 ± 0.02 3.10 ± 1.06 1.30 ± 0.58115 55 0.06 ± 0.01 ± 0.02 3.10 ± 1.06 1.30 ± 0.58120 95 0.06 ± 0.01 ± 0.02 5.37 ± 1.83 1.90 ± 0.63125 59 0.08 ± 0.02 ± 0.04 4.43 ± 2.47 2.64 ± 0.80130 41 0.12 ± 0.03 ± 0.06 4.16 ± 2.45 2.99 ± 0.81135 51 0.12 ± 0.03 ± 0.06 5.28 ± 3.11 2.99 ± 0.81140 54 0.12 ± 0.03 ± 0.06 5.60 ± 3.30 2.99 ± 0.81145 78 0.12 ± 0.03 ± 0.06 8.14 ± 4.79 3.66 ± 0.92150 77 0.10 ± 0.01 ± 0.03 6.77 ± 2.29 2.20 ± 0.69155 82 0.10 ± 0.01 ± 0.03 7.20 ± 2.43 2.20 ± 0.69160 30 0.24 ± 0.03 ± 0.06 5.89 ± 1.77 1.37 ± 0.56170 33 0.23 ± 0.03 ± 0.05 6.54 ± 1.71 0.63 ± 0.28180 40 0.21 ± 0.03 ± 0.01 6.86 ± 0.88 0.97 ± 0.49190 79 0.16 ± 0.01 ± 0.01 10.49± 1.39 2.14 ± 0.77200 114 0.15 ± 0.03 ± 0.03 13.54± 3.96 2.14 ± 0.77250 142 0.11 ± 0.02 ± 0.05 11.48± 6.23 3.61 ± 0.90300 107 0.12 ± 0.03 ± 0.04 9.73± 4.03 2.28 ± 0.66

73


Table 6.10: Estimation of the Drell-Yan background at the Higgs selection level, for various

Higgs masses at 8 TeV. The first uncertainty on Rout/inMC represents the statistical uncertainty

in the simulation. The second value is the systematic uncertainty due to the DY MVAdependency.

0-jet bin


110 198 0.32 ± 0.02 ± 0.09 47.01 ± 14.38 9.06 ± 5.23115 198 0.32 ± 0.02 ± 0.09 47.01 ± 14.38 9.06 ± 5.23120 369 0.32 ± 0.04 ± 0.09 85.52 ± 26.13 16.54 ± 6.26125 223 0.65 ± 0.04 ± 0.09 103.64 ± 18.29 16.54 ± 6.26130 173 0.91 ± 0.06 ± 0.09 111.54 ± 19.36 16.54 ± 6.26135 176 0.86 ± 0.05 ± 0.09 99.77 ± 16.49 14.63 ± 6.00140 173 0.80 ± 0.05 ± 0.06 88.46 ± 13.28 17.34 ± 6.57145 217 0.80 ± 0.05 ± 0.06 101.25 ± 15.37 17.34 ± 6.57150 171 0.31 ± 0.03 ± 0.22 30.79 ± 18.42 4.73 ± 3.38155 183 0.31 ± 0.03 ± 0.22 31.14 ± 18.65 4.73 ± 3.38160 54 0.74 ± 0.11 ± 0.29 15.18 ± 4.05 4.73 ± 3.38170 45 0.67 ± 0.10 ± 0.25 5.99 ± 2.72 4.73 ± 3.38180 57 0.54 ± 0.08 ± 0.11 2.63 ± 2.52 2.71 ± 2.71190 173 0.29 ± 0.04 ± 0.11 19.12 ± 3.67 4.99 ± 3.54200 281 0.21 ± 0.02 ± 0.01 20.82 ± 4.30 2.78 ± 2.28250 571 0.05 ± 0.01 ± 0.01 9.22 ± 2.49 7.05 ± 4.06300 347 0.08 ± 0.01 ± 0.03 8.01 ± 5.45 7.05 ± 4.06

1-jet bin


110 55 0.17 ± 0.01 ± 0.01 4.45 ± 0.63 2.22 ± 2.20115 55 0.17 ± 0.01 ± 0.01 4.45 ± 0.63 2.22 ± 2.20120 119 0.17 ± 0.01 ± 0.01 11.88 ± 1.10 4.54 ± 3.21125 87 0.25 ± 0.01 ± 0.01 12.93 ± 1.26 4.54 ± 3.21130 68 0.33 ± 0.02 ± 0.02 12.57 ± 1.45 4.54 ± 3.21135 76 0.30 ± 0.02 ± 0.02 13.38 ± 1.35 4.54 ± 3.21140 79 0.27 ± 0.02 ± 0.02 12.62 ± 1.38 4.54 ± 3.21145 105 0.27 ± 0.02 ± 0.02 16.14 ± 1.72 4.54 ± 3.21150 111 0.17 ± 0.02 ± 0.01 10.50 ± 1.30 2.33 ± 2.33155 125 0.17 ± 0.02 ± 0.01 11.85 ± 1.44 2.33 ± 2.33160 37 0.38 ± 0.03 ± 0.06 7.35 ± 1.45 2.33 ± 2.33170 36 0.35 ± 0.03 ± 0.05 5.59 ± 1.19 2.33 ± 2.33180 54 0.30 ± 0.02 ± 0.05 7.75 ± 1.62 0 ± 0190 141 0.22 ± 0.01 ± 0.03 16.47 ± 2.53 0 ± 0200 202 0.16 ± 0.01 ± 0.02 17.31 ± 2.24 0 ± 0250 302 0.09 ± 0.01 ± 0.01 12.23 ± 1.45 2.79 ± 2.79300 206 0.10 ± 0.01 ± 0.01 7.98 ± 1.38 5.20 ± 3.68

74

6.4 Top backgrounds

where N controlbtag is the number of events in the inverted control region and εtop is the

efficiency as measured in data. In the case of the zero and one jet bins, the data/MCscale factors evaluated with the mass-independent selection are applied to the MonteCarlo estimates of tt and tW after the full Higgs selection is applied.

– 0-jet bin

Most of the top background, composed of tt and tW processes, is rejected in the0-jet bin by the jet veto. The top-tagging efficiency in the zero jet bin, ε0−jettag ,is the probability for a top event to fail one of either the b-tagging veto or thesoft muon veto, and is defined as:

εtag =N control

tag

N control(6.4)

where N control is the number of events in the top control sample, one countedand b-tagged jet, and N control

tag the subset of those events that are tagged byeither the soft muon tagging or the low-pT b-jet tagging. The purity of thiscontrol sample, as estimated from simulation, is about 97%. The remaining3% background contribution is subtracted from the numerator and denominatorN control

tag and N control respectively. ε0−jettop can then be estimated using the followingformula:

ε0−jettop = ft·ε2b + ftW · (x · ε2b + (1− x) · εtag)

(6.6)

(6.7)

ε2b = 1− (1− εtag)2 (6.8)

where ft and ftW are the tt and tW event fractions, respectively, x is the fractionof tW events containing two b-jets, and ε2b is the efficiency for a top event withzero counted jets (i.e. two soft b-jets) to pass the top-veto. An importantingredient is the ratio of tt and tW cross-sections, for which an uncertainty of17% [72] is assumed. Using the NLO tt and tW Monte Carlo samples a ft∼ 64%is estimated after all WW requirements except the top veto.

The inverted control region for which the efficiency is used to propogate backinto the signal region is defined as events with zero counted jets which fail eitherthe soft-muon or the soft b-tagging veto. The details of the 0-jet bin calculationare summarized in Tables 6.11 to 6.14.

– 1-jet bin

In the 1-jet bin the top processes are the main background contributions. Theextrapolation method is similar to the 0-jet bin, using as a control sample eventswith two jets to measure the top veto efficiency (denominator). As numeratorfor the efficiency all the events for which the maximum value of the b-tag dis-criminator on all the jets excluding the leading jet exceeds the analysis threshold

75


are considered. The leading jet is excluded from this measurement in order tonot bias the sample.The value for the tagging efficiency, defined in this bin as:

ε1−jettop =

N controltag

N control(6.9)

is found to be 0.65 ± 0.01, in good agreement with the expectation from MonteCarlo. The inverted control region for which the efficiency is used to propogateback into the signal region is defined as events with one counted and b-tagged jetthat have passed the soft tagging vetos. The details of the 1-jet bin calculationare summarized in Tables 6.11 and 6.12 for p``T > 45 GeV and Tables 6.13and 6.14 for p``T > 30 GeV.

Table 6.11: Estimation of top backgrounds in the 0- and 1-jet bins at 7 TeV for p``T > 45GeV.

0-jet bin 1-jet binN control (bkg. sub.) 1009 3482N control

tag (bkg. sub.) 349 2400εtag 0.35 ± 0.01 -ft (%) 66 ± 26 -ε2b 0.57 ± 0.01 -tagging efficiency, εtop (%) 0.52 ± 0.04 0.68 ± 0.01top-tagged events in data 193 912background events in control region 38.8 ± 1.3 52.9 ± 2.6estimated top events in simulation 108.6± 1.2 355.5 ± 2.0data-driven top background estimate 139.9± 24.8 387.3 ± 14.6data/MC 1.29 ± 0.23 1.09 ± 0.04



tag (bkg. sub.) 1679 9039εtag 0.32 ± 0.01 -ft (%) 66 ± 26 -ε2b 0.54 ± 0.01 -tagging efficiency, εtop (%) 0.49 ± 0.04 0.65 ± 0.01top-tagged events in data 1020 4908background events in control region 330.2 ± 40.1 373.5 ± 25.1estimated top events in simulation 743.8± 6.9 2224.6 ±11.0data-driven top background estimate 717.6±124.9 2420.5 ± 44.4data/MC 0.96 ± 0.17 1.09 ± 0.02

76

6.4 Top backgrounds



tag (bkg. sub.) 403 2400εtag 0.34 ± 0.01 -ft (%) 66 ± 26 -ε2b 0.57 ± 0.01 -tagging efficiency, εtop (%) 0.52 ± 0.04 0.69 ± 0.01top-tagged events in data 245 1052background events in control region 62.2 ± 1.5 65.6 ± 2.6estimated top events in simulation 128.1± 1.3 411.8 ± 2.1data-driven top background estimate 167.3± 29.7 444.7 ± 16.7data/MC 1.31 ± 0.23 1.08 ± 0.04



tag (bkg. sub.) 1960 9039εtag 0.32 ± 0.01 -ft (%) 66 ± 26 -ε2b 0.53 ± 0.01 -tagging efficiency, εtop (%) 0.49 ± 0.04 0.65 ± 0.01top-tagged events in data 1313 5783background events in control region 511.4 ± 47.6 483.6 ± 29.2estimated top events in simulation 862.9± 7.4 2615.4 ±11.9data-driven top background estimate 847.9±147.9 2828.8 ± 51.8data/MC 0.98 ± 0.17 1.08 ± 0.02

77


6.4.1 WW background

The non-resonant WW production is dominated by the qq → WW process, which isestimated from a control region in data for Higgs masses below 200 GeV. The controlregion is defined as m`` > 100 GeV, and extrapolated to the signal region followingEquation 6.10.

N signalWW = RWW ·N control

WW (6.10)

with the ratio RWW estimated on Monte Carlo. This procedure is described in moredetail in [73]. Since the measurement of the WW yield with the luminonsity used isnot totally statistically dominated, we account also for the systematic on RWW due tothe uncertainty on the shape of the m`` distribution for WW events. The differencein RWW between the nominal sample (MADGRAPH) and a sample at NLO is takenas an estimation of the uncertatinty. The difference is 10% and it is propagated tothe WW estimation.

The other background contributions in the control region (Drell-Yan, top, W+jets)are subtracted to extract N control

WW . The W+jets is estimated from the tight-fail sample.For the other processes the estimation in the full m`` region, described in the previoussections, is extrapolated to the control region with a ratio estimated from simulation.Since the measurement from mll sidebands is not sensitive to the kinematics differencebetween qq→WW and gg→WW, the scale factor with respect to the Monte Carloexpectation of the sum of the two contributions is estimated together. The latesttheoretical cross section

σ(gg→WW + qq→WW) = 57.25 pb(

+4.1%−2.8%

)[74]

is used. The fraction of gg→WW with respect to the total WW production is 0.0305,consistent with what has been used in the official CMS Monte Carlo production(0.0328). The WW estimation after the mass-independent selection is showed inTable 6.15 and 6.16. The WW is then estimated following the same procedure withthe full Higgs selection applied, except the mT cut.

6.4.2 W+jets background

The W+jets background has a real prompt lepton coming from the W decay. Oneor more jets can be mis-identified as a lepton in for such background. The QCDbackground are events with multiple jets where the final signature can be signal likewhen two of these jets fake a lepton each. The rate for which a jet can be mis-identified as a lepton is not properly simulated by Monte Carlo, leading to a datadriven method to estimate these backgrounds directly from data. These backgroundscontaining one or two fake leptons are estimated from events selected with relaxedlepton quality criteria, using the efficiencies for real and fake leptons to pass the tightlepton quality cuts of the analysis.

A sample of events dominated by dijet production is taken and a set of loosely selectedlepton-like objects (referred to as the ’fakeable object’ or ’denominator’ from here on)is defined.

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6.4 Top backgrounds

Table 6.15: Estimation of the WW background at the mass-independet selection level at 7TeV .

0-jet bin, p``T > 45 GeVm`` region data all bkg Ndata

WW NMCWW data/MC

control 485 116.1 ± 13.8 368.9 ± 26.0 323.7 ± 2.4 1.1± 0.1all 1363 - 1045.4 ± 97.1 917.4 ±4.0 -


WW NMCWW data/MC

control 359 189.1 ± 8.5 169.9 ± 20.8 146.2 ± 1.6 1.2 ± 0.1all 430 - 429.5 ± 100.8 369.6 ± 2.5 -


WW NMCWW data/MC

control 660 155.4 ± 17.6 504.6 ± 31.1 434.0 ± 2.8 1.2± 0.1all 1957 - 1455.3 ± 125.7 1251.6 ±4.7 -


WW NMCWW data/MC

control 406 215.0 ± 9.5 191.0 ± 22.3 170.9 ± 1.7 1.1 ± 0.1all 497 - 496.6 ± 115.1 444.5 ± 2.8 -

Table 6.16: Estimation of the WW background at the mass-independet selection level at 8TeV .


WW NMCWW data/MC

control 2399 620.2 ± 73.6 1778.8 ± 88.4 1641.3 ± 9.6 1.08± 0.05all 6902 - 4775.2 ± 373.5 4406.1 ±15.5 -


WW NMCWW data/MC

control 1719 1110.0 ± 38.4 609.0 ± 56.5 688.8 ± 6.2 0.88 ± 0.08all 1522 - 1522.3 ± 336.0 1721.5 ± 9.7 -


WW NMCWW data/MC

control 3119 844.6 ± 91.9 2274.4 ± 107.5 2170.7 ± 11.1 1.05± 0.05all 9677 - 6254.4 ± 479.2 5969.1 ±18.1 -


WW NMCWW data/MC

control 2014 1287.1 ± 43.2 726.9 ± 62.3 806.5 ± 6.7 0.90 ± 0.08all 1875 - 1875.0 ± 408.4 2080.1 ± 10.7 -

79


The fake rate accounts for how many fakeable objects pass the full lepton selectionof the analysis as a function of η and pT .

The ratio of the fully identified lepton, referred as ’numerator’, to the fakeable objectsis taken as the probability for a fakeable object to fake a lepton:

Fake Rate =#of fully reconstructed leptons

#of fakeable objects(6.11)

It is then used to extrapolate from the loose leptons sample to a sample of leptonssatisfying the full selection.

The systematic uncertainty of the method strongly depends on the denominator def-inition, mainly due to the fact that the sample dependence uncertainties for extrap-olating in different isolation and lepton quality criteria are typically different. Thehigher instantaneous luminosity delivered by the LHC in 2012 leads to tighter selec-tion requirements in the high level trigger for electrons, thus limiting the choice ofpossible denominator object definitions. The loose definition used in 2012 data havebeen chosen to keep the same fake rate as in 2011 data. The final denominator objectdefinition used, for electrons and muons respectively is shown below:

– σiηiη < 0.01/0.03 (barrel/endcap)

– |∆φin| < 0.15/0.10

– |∆ηin| < 0.007/0.009

– H/E < 0.12/0.10

– full conversion rejection

– |d0| < 0.02 cm

–∑

trk ET

p Tele < 0.2

–∑

ECAL ET

p Tele < 0.2

–∑

HCAL ET

p Tele < 0.2

The loose muon selection requirements can differ from the tight selection, only in lessstringent cuts on d0 and MVA based isolation. The following definition is considered.

– |d0| < 0.2 cm

– MVA output > −0.6

No MC subtraction is necessary since the prompt rate already takes into account thereal lepton contamination. Both the prompt rate and fake rate are measured in data,using Z→ `` events and di-jet events, respectively. The prompt rates for both muonsand electrons are summarized in Tables 6.17 and 6.18.

The lepton fake rates are measured in a QCD dominated sample dominated, wherereal leptons from W or Z leptonic decays can still be found. The QCD sample isselected using the single lepton trigger paths listed in table 6.19.

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6.4 Top backgrounds

Table 6.17: Measured prompt rate for muons in bins of η, pT . Errors are statistical only.

Muon prompt ratepT range [GeV] 0 < η ≤ 1.5 1.5 < η ≤ 2.510 < pT≤ 15 0.7119 ± 0.0003 0.7582 ± 0.000615 < pT≤ 20 0.8049 ± 0.0018 0.8495 ± 0.000120 < pT≤ 25 0.9027 ± 0.0008 0.8948 ± 0.001225 < pT≤ 50 0.9741 ± 0.0001 0.9627 ± 0.000250 < pT 0.9900 ± 0.0001 0.9875 ± 0.0003

Table 6.18: Measured prompt rate for electrons in bins of η, pT . Errors are statistical only.

Electron prompt ratepT range [GeV] 0 < η ≤ 1.4442 1.4442 < η ≤ 1.566 1.566 < η10 < pT≤ 15 0.5738 ± 0.0045 0.5366 ± 0.0204 0.2947 ± 0.004715 < pT≤ 20 0.7091 ± 0.0020 0.5484 ± 0.0185 0.4477 ± 0.003420 < pT≤ 25 0.7175 ± 0.0013 0.6297 ± 0.0067 0.6200 ± 0.000125 < pT≤ 50 0.9219 ± 0.0002 0.8404 ± 0.0007 0.8509 ± 0.000150 < pT 0.9693 ± 0.0002 0.9398 ± 0.0021 0.9385 ± 0.0005

The event is required to have PF EmissT < 20 GeV in order to remove muons from

W decays. Also the W transverse mass has to be lower than 20 GeV. The muonsfrom Z decays are removed with the mµµ > 20 GeV and the mµµ /∈ [76, 106] GeVconstraints. For electrons the W transverse mass cut is not applied, and the Z-peakveto is enlarged to mee /∈ [60, 120] GeV. Finally, both muon and electron candidatesare required to be well separated from the leading jet of the event, ∆φ(``, j) > 1.

The remaining real lepton contamination from EWK (W/Z+jets) events, primarilybias the full lepton selection sample (’numerator’) and clearly biases the fake rateat high pT , although only pT bins up to 35 GeV are considered. To correct for thiseffect, the EWK (W+jets and Z+jets) contamination is estimated from two MonteCarlo samples, using the expected cross section and the effective luminosity of thelepton triggers, and substracted from the ’denominator’ and ’numerator’ samples.This method has being already used in past analysis and is describe in [73].

In Figures 6.5 and 6.6 the comparison of the fake rate estimation from data beforeand after removing the EWK contribution estimated from MC in pT and η bins isshowed, both for electrons and for muons. The subtraction have a significant effectfor pT > 20 GeV. In addition the fake rates are given in Table 6.20 after the EWKcorrection of the smaples.

The resultant background yield estimates at the WW selection level are listed, for thedifferent number of jet bins, in Table 6.21 for a real+fake lepton and in Table 6.22for the double fake lepton backgrounds. The systematic uncertainty is evaluated byvarying the jet thresholds in the di-jet control sample, and by performing a closuretest in the same-sign data sample. In both cases it is about 36%.

In case of electrons the sample obtained with a threshold on the leading jet of 35 GeV

81


Table 6.19: Single lepton trigger paths used for selecting the enriched QCD sample.

Electron triggersHLT Ele17 CaloIdT CaloIsoVL TrkIdVL TrkIsoVL v*HLT Ele8 CaloIdT CaloIsoVL TrkIdVL TrkIsoVL v*

Muon triggersHLT Mu8 v*HLT Mu17 v*

Table 6.20: Measured fake rates in bins of η and pT , after the EWK correction. Errors arestatistical only.

electron fake ratepT range [GeV] 0 < η ≤ 1 1 < η ≤ 1.479 1.479 < η ≤ 2 2 < η ≤ 2.510 < pt <= 15 0.045 ± 0.005 0.033 ± 0.004 0.008 ± 0.002 0.021 ± 0.00515 < pt <= 20 0.044 ± 0.003 0.049 ± 0.003 0.017 ± 0.001 0.017 ± 0.00220 < pt <= 25 0.041 ± 0.002 0.064 ± 0.003 0.025 ± 0.002 0.025 ± 0.00225 < pt <= 30 0.059 ± 0.003 0.101 ± 0.005 0.041 ± 0.003 0.043 ± 0.00330 < pt <= 35 0.084 ± 0.006 0.111 ± 0.009 0.058 ± 0.006 0.066 ± 0.005

muon fake ratepT range [GeV] 0 < η ≤ 1 1 < η ≤ 1.479 1.479 < η ≤ 2 2 < η ≤ 2.510 < pt <= 15 0.131 ± 0.002 0.154 ± 0.004 0.194 ± 0.005 0.241 ± 0.00915 < pt <= 20 0.143 ± 0.007 0.191 ± 0.012 0.235 ± 0.016 0.308 ± 0.02720 < pt <= 25 0.198 ± 0.005 0.239 ± 0.009 0.221 ± 0.011 0.271 ± 0.02125 < pt <= 30 0.182 ± 0.011 0.228 ± 0.018 0.195 ± 0.022 0.287 ± 0.04530 < pt <= 35 0.170 ± 0.021 0.244 ± 0.036 0.195 ± 0.041 0.289 ± 0.111

matches the W+jets spectrum the best, and it is taken for the central value of thefake rate measurement. The systematic uncertainty is estimated by using fake ratesfrom the sample defined by thresholds of 20 and 50 GeV, since they are observedto cover the correct W+jets spectrum. In case of muons the central value is takenfrom a sample with a threshold on the leading jet of 15 GeV, while the systematicuncertainty is estimated by using fake rates from the sample defined by thresholdsof 5 and 30 GeV. Resuts of the W+jets estimation at WW selection level and usingdifferent samples can be found in Table 6.23.

The region obtained by reversing the opposite sign lepton requirement in the WW

Table 6.21: Real+fake (i.e. W+jets) lepton yields at WW selection cuts. Errors are statis-tical only.

mu mu e mu mu e e e total0 jet 64.80 ± 5.86 282.75 ± 8.77 56.26 ± 3.15 62.79 ± 2.74 466.60 ± 11.341 jet 48.69 ± 4.67 223.21 ± 8.25 66.12 ± 3.42 23.07 ± 1.71 361.09 ± 10.222 jet 74.77 ± 5.80 151.28 ± 7.12 35.97 ± 2.74 20.73 ± 1.78 282.75 ± 9.75

82

6.4 Top backgrounds

(a) (b)

(c) (d)

Figure 6.5: Electron fake rate for different η bins as a function of pT , before and after EWKcorrection.

Table 6.22: Fake+fake (i.e. QCD) lepton yields at WW selection cuts. Errors are statisticalonly.

mu mu e mu mu e e e total0 jet 0.38 ± 0.34 4.37 ± 0.45 0.10 ± 0.11 0.01 ± 0.07 4.86 ± 0.581 jet 0.58 ± 0.28 19.88 ± 0.73 0.74 ± 0.15 0.12 ± 0.05 21.32 ± 0.802 jet 2.17 ± 0.51 13.21 ± 0.58 0.47 ± 0.11 0.22 ± 0.06 16.07 ± 0.78

selection is enriched with W+jets events where one of the jets is misidentified as alepton. The fake rate procedure can be applied to the same-sign control region asdata-driven closure test of the method.

The results of the closure test on same-sign events presents a good agreement withthe expectations, as shown in Table 6.24. A correction taken from MC is applied tothe observed number of events to account for the different background contributions

83


Figure 6.6: Muon fake rate as function of the loose lepton pT (left) and η (right), for muons,before and after EWK correction.

Table 6.23: Dependence of fake lepton background yields after WW selection (0-jet bin)on the electron and muon fake rates computed from different jet-pT thresholds samples (seetext).

Channel Nominal DOWN UP Relative diferenceMuon + Muon 64.80 ± 5.86 75.29 ± 6.69 46.77 ± 4.45 +15 -28 %

Electron + Muon 282.75 ± 8.77 333.56 ± 10.61 147.40 ± 5.12 +18 -48 %Electron + Electron 62.79 ± 2.74 69.33 ± 3.13 28.07 ± 1.34 +10 -54 %

Muon + Electron 56.26 ± 3.15 73.71 ± 3.79 40.56 ± 2.78 +29 -28 %Total 330.7 ± 10.8 213.5 ± 12.4 182.7 ± 7.3 -35 +45 %

not taken into account in the fake rate method: WZ, ZZ, Wγ, Wγ* and other minorbackgrounds in the same-sign data sample. The uncertainty on the predicted numberof events include the statistical uncertainty.

As a rough check of the agreement of the same-sign closure test, the comparison ofvarious distributions at the WW selection level in the 0-jet bin, for same-sign events,reweighted to the data-driven estimates is shown in Figure 6.7.

6.4.3 ZZ, WZ and W + γ backgrounds

The WZ and ZZ backgrounds are partially estimated from data when the two selectedleptons come from the same Z boson. If the leptons come from different bosonsthe contribution is expected to be small. The WZ component is largely rejectedby requiring only two high pT isolated leptons in the event. The missing energyrequirement makes the ZZ → 4` component almost negligible. As the extra leptonveto and the cuts do not remove the ZZ → 2`2ν decays, a non-negligible fraction ofthese events survives the selection. The W+γ∗ background, where the photon decays

84

6.4 Top backgrounds

Table 6.24: Summary of fake lepton background yields in the same sign sample after WWselection (0-jet bin), for low Higgs mass selection. .

Sample YieldsObserved SS events in data 400 ± 20

MC WZ 118.8 ± 1.2MC ZZ 0.19 ± 0.08MC Wγ 36.8 ± 9.0MC Wγ* 72.0 ± 5.7MC WW 14.7 ± 1.0MC DY 11.6 ± 5.4MC top 0.19 ± 0.08

Observed SS events corrected by MC 145.7 ± 2.33

Estimated events (data-driven) 195.6 ± 6.1

to an electron-positron pair, is expected to be very small, thanks to the stringentphoton conversion requirements. Since the WZ simulated sample has a generationlevel cut on the di-lepton invariant mass (m`` > 12 GeV) and the cross-section raisesquickly with the lowering of this threshold, a dedicated sample has been producedwith lower momentum cuts on two of the three leptons (pT > 5 GeV) and no cuton the third one. The surviving contribution estimated with this sample is still verysmall, and since the uncertainty on the cross-section for the covered phase space islarge, a conservative 100% uncertainty has been given to it. The contribution ofthis background is also constrained by a closure test with same sign leptons on data,which reveals a good compatibility of the data with the expected background. Theestimated values of these background will be shown later.

85


(a) (b)

(c) (d)

Figure 6.7: Various distributions for the the 0-jet bin at the WW selection level in thesame-sign control region, as described in the text.

86

7

Systematic Uncertainties

The systematic uncertainties are a crucial point in any analysis [75]. Especially whenusing a shape analysis, where the interpretation of a result is based on the shape ofsome discrinating variables, it is important to have a very good understanding on theeffects that could affect the signal and background distributions.

One must distinguish between two different kind of uncertainties:

– Normalization uncertainties, where a systematic effect is changing the normal-ization assuming the shape is not affected. These uncertainties enter the shapeanalysis as a constant normalization factor. The normalization uncertainties arethe same for the cut based and shape based analysis.

– Shape uncertainties, where the change in the shape of the distribution is takeninto account. These systematic uncertainties enter the analysis in form of threehistograms (nominal histogram, −σ and +σ)

The main sources of systematic uncertainties are experimental, theoretical an statis-tical uncertainties.

– Experimental uncertainties are driven by the performance of the detector tomeasure the observables used in the analysis.

– Theoretical uncertainties are due to the limitations of the model used to describethe different physical processes.

– Statistical uncertainties come from the finite size of the Monte Carlo samplesused in the analysis.

7.1 Experimental uncertainties

The experimental uncertainties are applied by scaling and/or smearing certain vari-ables, followed by a recalculation of all the correlated variables. This is done forMonte Carlo simulation, to avoid possible systematic mismeasurements of the data.

87

7. SYSTEMATIC UNCERTAINTIES

For the scale uncertainties, as the jet energy scale or the lepton momentum scale,the pT of the objects is scaled by some factor and again all the correlated variablesrecalculated.

7.1.1 Lepton identification efficiencies

The lepton identification efficiencies are measured using the Tag and Probe methodin data. In order to correct for the difference in the lepton identification efficiencesbetween data and MC, a scale factor is applied to MC. The systematic uncertaintyon the lepton identification efficiency is estimated by shifting the mean scale factorby its statistical error up and down (all bins in the same direction). The resultingnormalization uncertainty at the shape analysis level is Higgs mass dependent for lowHiggs masses, and becomes constant at around 200 GeV. This is mainly due to thefact that the error on the scale factor is larger for low pT leptons than for leptons withhigher pT. This effect is enhanced by the increasing lepton pT cut which is appliedin the event selection. For the 1D shape analysis the lepton efficiency uncertainty istreated as a shape uncertainty.

7.1.2 Missing transverse momentum resolution

The effect of the missing transverse momentum resolution on the event selectionis taken into account by applying a Gaussian semaring of 10% on the x- and y-components of the missing transverse momentum. All correlated, like the transversemass, are recalculated. The effect in the same flavour channels is found to be around2% for higher Higgs mass points, increasing to about 4 − 6% for the lower Higgsmass points. For the different flavour channels the uncertainty is observed to besmaller, around 1% and constant for all the Higgs mass points. For the 1D shapeanalysis the missing transverse momentum resolution uncertainty is treated as a shapeuncertainty.

7.1.3 Lepton momentum scale

The momentum scale of leptons have relatively large uncertainties due to differentdetector effects. For electrons a scale uncertainty of 2% for the barrel and 4% for theendcaps is assigned. For muons, a momentum scale uncertainty of 1% independent ofits pseudorapidity is assigned. The effect on the lepton scale uncertainty is estimatedby scaling the lepton momentum up and down by the associated uncertainty. Thecorrelated variables (mll, mT , dilepton pT and the missing transverse momentum)are recalculated. The lepton scale uncertainty is increasing for low masses and fairlyconstant from 200 GeV on. The normalization uncertainty is larger for the electronscale than for the muon scale. The magnitude of the normalization uncertainty isdriven by the leading lepton (i.e larger uncertainty due to the electron scale for thedi-electron and the electron-muon channel and larger uncertainty due to the muonscale for the di-muon and muon-electron channels). The lepton momentum scale is

88


treated as a shape uncertainty. Figures 7.1 and 7.2 show the muon and electron energyscale measured in Z resonance using di-muon and di-electron events respectively inBarrel-Barrel, Barrel-Endcap and Endcap-Endcap configuration.

Figure 7.1: Muon momentum scale measured in Z resonance using di-muon events in Barrel-Barrel (top), Barrel-Endcap (middle) and Endcap-Endcap (bottom) configuration.

7.1.4 Jet energy scale uncertainty

The jet energy scale uncertainty is studied by scaling (up and down) the jet momen-tum by a pT and η dependent factor, which varies between 2 and 5%. Once againafter scaling, all correlated variables are recalculated. The uncertainty arises mainly

89


Figure 7.2: Electron energy scale measured in Z resonance using di-electron events in Barrel-Barrel (top), Barrel-Endcap (middle) and Endcap-Endcap (bottom) configuration.

due to the bin migration between the 0 and 1 jet bin, and causes a slightly Higgsmass dependent difference of about 2-4% on the event selection efficiency. The jetenergy scale is treated as a shape uncertainty.

7.1.5 Electron energy resolution

The electron energy resolution is 2% (4%) in the barrel (endcaps). This uncertainty isstudied by applying a random smearing of the electron pT assuming a Gaussian witha width of 2% (4%) of the actual electron momentum. The uncertainty is around 1%

90


for all channels containing an electron in the final state, independently of the Higgsmass. The electron resolution is treated as a shape uncertainty.

7.1.6 Luminosity

The luminosity uncertainty is 4.5% and it is treated as a normalization uncertainty.

7.1.7 Pile-Up

The number of pile-up events is measured in data, and thus affected by the instan-taneous luminosity per bunch crossing and the total pp cross section, leading to atotal uncertainty of 8% on the number of interactions in data. The Monte Carlo sim-ulation is reweighted to the measured number of interactions in data by run period.A conservative approach to estimate the effect of the pileup is to compare the re-weighted with the non-reweighted Monte Carlo. The estimated uncertainty is foundto be around 0.5% and is treated as a normalization uncertainty.

7.1.8 Uncertainties on background estimates

The uncertainties coming from the data-driven estimation are all treated as normal-ization uncertainties. More details about these methods can be found in section 6.3.Table 7.1 summarizes the uncertainties associated with the data-driven estimate.

source 1 σ uncertainty (%) notes0-jet 1-jet 2-jet

W+jetsStat. in Ndata

LooseLoose [4, 10] [5, 13] [20, 50] uncorrelated in all channelsFake rate (separate e and µ) 36 36 36 correlated in jet binsZ/γ∗ → ``Stat. in Ndata

ctrl [5, 30] [7, 50] [20, 30] uncorrelated in jet binsRout/in Extrapolation [20 , 300] [10 , 300] [20 , 300] separated in ee/µµ for 2-jettt/tWStat. in Ndata

ctrl 4 0.0 [25 , 30] uncorrelated in jet binsTop tagging efficiency [13, 15] [3 , 5] [10 , 45] uncorrelated in jet binsFraction of ``′ and `` -2 / +6 -2 / +6 -7 / +12 anti-correlate in ``′/`` channelsStat. in MC extrap. [3 , 25] [3 , 7] - uncorrelated in all channelsgg/qq→WWStat. in Ndata

ctrl 3 3 (MC) uncorrelated in jet binsExtrapolation using m`` 7.5 15 (MC) correlated in jet binsFraction of ``′ and `` -5 / +3 -6 / +3 (MC) anti-correlate in ``′/`` channelsStat. in MC extrap. [2 , 10] [3 , 18] (MC) uncorrelated in all channels and gg/qq

Table 7.1: Uncertainties associated with data-driven estimates.

91


7.2 Theoretical uncertainties

The main theoretical uncertainties taken into account are listed next:

– Higgs signal cross sections: Taken from the Higgs cross section working group.The effect on the selection efficiency varies between 1-12% depending on theHiggs mass. This uncertainty is taken as a normalization uncertainty.

– PDF uncertainties: Different sets of Parton Density Functions (PDFs) havebeen tested leading to different acceptances of the measurement. The PDFuncertainties are treated as normalization uncertainties.

– WW shape: The analysis is strongly relying on theoretical models since theshape of the main background, the WW production, is taken entirely from MCsimulation. Especially higher order QCD radiation effects have an influenceon the generated WW shape. For this reason, the shapes of the distributionsusing the default WW sample in the analysis are compared with the WW shapecoming from the MC generators available. The difference between these shapesis directly taken as the shape uncertainty in the shape analysis.

Table 7.1 summarizes the theoretical systematic uncertainties.

Source process 1 σ uncertainty (%) notes0-jet 1-jet 2-jet

QCD scale gg→H [15 , 20]qq→qqH [0.2 , 1.5]

VH 1.5gg→WW 30VV, Vγ(∗) 3 uncorrelated

QCD scale gg→H [-5 , -22] [+35 , +56] - anti-correlated in jet bins(jet migration) - [-5 , -15] [+10 , +20] anti-correlated in jet bins

QCD scale gg→H 2(acceptance) qq→qqH 2

PDF (gg) gg→H [7.5 , 10] correlated in all gg→Xgg→WW 4 correlated in all gg→X

PDF (qq) qq→qqH [2.2 , 4.5] correlated in all qq→XVH [0.2 , 3.2] correlated in all qq→XVV 4 correlated in all qq→X

UEPS gg→H [-4 , -8] [+5 , +13] [-14, +30] correlated in jet binsVBF fraction qq→WW - - 50 MC prediction in 2-jet bin

Table 7.2: Theoretical uncertainties. For Higgs mass dependent values, the minimum andthe maximum are given.

7.3 Statistical uncertainties

The statistical uncertainties are taken into account for each distribution going asinput into the shape analysis. The +σ and −σ shapes have been obtained by

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7.3 Statistical uncertainties

adding/subtracting the statistical error in each bin and renormalizing it to the nom-inal distribution. In addition, a constant normalization uncertainty is also assigneddue to the finite statistics of the sample used to extract the shape.

For the 1D shape analysis, the effect of replacing the constant normalisation system-atics (the ones used in the cut based analysis) by shape systematics is found to bearound 10% in the median expected limits.

93


94

8

Results

In the first part of this chapter the WW production cross section measurement ispresented. The WW process is the major and almost irreducible background forthe Higgs searches in the H → WW channel and its proper understanding is anessencial piece to properly establish the Higgs boson observation in this decay modeand therefore in the final combined result. The WW cross section measurementpresented in this thesis has led to two publications at 7 TeV [8] and at 8 TeV [76].

The results of the H → WW searches using the full Run I data delivered by the LHCfor both the cut based and 1D shape analysis are presented in the second part of thechapter. The H → WW has been the main channel in terms of exclusion range atthe beginning of the LHC data taking. In a Higgs hunting scenario, as it was the caseduring 2012, this channel has also been one of the key pieces in the final combinationresult to claim the Higgs boson discovery.

8.1 WW production cross section

As it has already been mentioned before, a proper estimation of the WW productioncross section is needed not only to test the Standard Model but also to perform Higgssearches, especially in the H → WW channel where the non resonant WW is themain background. The cross section is estimated with the expression:

σWW =NData − Nbkg

Lint · ε · (3 · BR(W→ `ν))2(8.1)

where N Data is the number of data events, Nbkg is the total number of estimatedbackground events, ε is the efficiency for signal selection. For the leptonic final stateestimation, the branching ratio for W boson decaying to each lepton family is takeninto account, with a value BR(W → `ν) = (0.1080 ± 009) [77].The uncertaintyassociated to the cross section is computed as:

∆σ = ∆σ (stats.) ⊕ ∆σ (syst.) ⊕ ∆σ (lumi.)

=

√(NData)

σ · Lint · ε⊕ ∆Nbkg

Lint · ε⊕ ∆ε

εσ ⊕ ∆Lint

Lint

σ

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8. RESULTS

where ∆Nbkg is the error of the background estimation, ∆ε the uncertainty of thesignal efficiency and ∆Lint the uncertainty of the luminosity value. In this chapter thefinal result for the cross section estimation is presented, together with the estimationperformed in each of the leptonic final states, and compared with the theoreticalprediction.

8.1.1 Previous results at the LHC

A measurement of the WW cross section has already been done with 7 TeV datafor a luminosity of 4.92 fb−1 [78]. Table 8.1 summarizes the data yields and back-ground estimation after the full event selection for the whole 2011 running periodat 7 TeV. The expectation for the signal is also shown in this table. The main

Sample Yield ± stat. ± syst.gg→WW 46.03± 0.60± 14.16qq→WW 750.86± 4.11± 53.13

tt +tW 128.46± 12.79± 19.55W+jets 59.45± 3.93± 21.40WZ+ZZ 29.40± 0.43± 2.03

Z/γ∗ 10.98± 5.05± 2.59W+γ 18.84± 2.84± 4.68

Z/γ∗ → ττ 0.0± 1.0± 0.1Total Background 247.13± 14.62± 29.54

Signal + Background 1044.02± 15.20± 62.41

Data 1134

Table 8.1: Data yields and expected background for 4.92 fb−1 at 7 TeV. The prediction forthe WW process assumes the SM cross section value.

background contribution comes from top processes, which accounts for 50% of thetotal background, followed by the W+jets and dibosons. The Drell-Yan process hasbeen reduced greatly thanks to the tight Emiss

T requirements and some kinematic cutsoptimized for this purpose. The final result with the full 2011 data taking is :


The cross section measurement at 7 TeV is to be compared with the current NLOtheoretical prediction [79]:

σ(gg→WW + qq→WW) = 47.04 pb(

+4.3%−3.2%

)The measured cross section is then about 1-σ deviated from the Standard Modelprediction.

96


8.1.2 WW cross section measurement at 8 TeV

The pp → WW production cross section result has been calculated using the first3.54 fb−1 of data at 8 TeV in 2012 [76]. The WW cross section is measured using thesample of events preselected for HWW (the so called WW level) with some minimumchanges. Since the size of the data sample is not an issue in the case of the WW crosssection and aiming for a reduction of the systematic uncertainty, the pT threshold ofthe training lepton is raised up to 20 GeV. The event is required to have a minpmet >45 GeV for the same flavour channels. The WW production cross section has beenmeasured in the so called 0-jet bin since this is the phase space region where thesystematic uncertainty is the lowest.

The efficiency for WW is calculated separately for each process, qq →WW andgg→WW, being (3.112 ± 0.024) % and (6.692 ± 0.148)% respectively. The totalefficiency for WW is obtained from the weighted sum of the two processes. Theweight comes from the theoretical cross section, being gg a 3% of the total value.The estimated total efficiency is (3.220± 0.220 (stat + syst))%.

The uncertainty in the signal acceptance for cross section measurement due to varia-tions in the parton distribution functions and the value of αs is estimated by followingthe pdf4lhc prescription [80]. Using CT10 [81], MSTW08 [82], and NNPDF [83]sets, the uncertainty is 2.3%.

The effects of higher-order corrections are found by varying the QCD renormalisationand factorisation scales simultaneously up and down by a factor of two according tothe recommendations of the LHC Cross Section Working group using the mcfmprogram [84]. The variations in the acceptance are found to be around 1.5%.

The WW jet veto efficiency in data is estimated from simulation, and multiplied bya data-to-simulation scale factor derived from DY events in the Z peak: εdata

W+W− =εMC

W+W− × εdataZ /εMC

Z . The uncertainty is thus factorized into the uncertainty in the Zefficiency in data and the uncertainty in the ratio of the W+W− efficiency to the Zefficiency in simulation (εMC

W+W−/εMCZ ). The former, which is statistically dominated,

is 0.3%. Theoretical uncertainties due to higher-order corrections contribute most tothe W+W−/Z efficiency ratio uncertainty, which is estimated to be 4.6% for WWproduction. The data-to-simulation correction factor is found to be close to one andis not applied.

Simulated events are scaled according to the lepton efficiency correction factors mea-sured using data control samples, which are typically close to one. The uncertaintiesin the measured identification and isolation efficiencies are found to be 1–2% formuons and electrons. The uncertainty in the trigger efficiency is 1.5%. The uncer-tainty in the lepton energy scale is about 1–2.5% and 1.5% for electrons and muons,respectively.

The systematic uncertainties in the W + jets, Z + jets, and top backgrounds areestimated to be 36%, 24%, and 15%, respectively. The theoretical uncertainties inthe WZ and ZZ cross sections are calculated following the same prescription as for thesignal acceptance. For the WZ and ZZ backgrounds an uncertainty of approximately10% is obtained including the experimental systematic contribution.

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8. RESULTS

The uncertainty assigned to the pile-up reweighting procedure amounts to 2.3%. Theuncertainty in the integrated luminosity is 4.4% [85].

The background estimation methods have already been described in Section 6.3. Thedetails of the predicted yields for top, W+jets and Z+jets backgrounds are listed inTables8.2, 8.3 and 8.4 respectively.

ValueNDatacontrol 1385 ± 37.2NDatacontrol

tag 422 ± 20.5εData

top−tag (%) 36.8 ± 2.5εtWtop−tag (%) 16.1 ± 1.4ft (%) 69.7 ± 9.1

Tagging efficiency 0-jet, ε0−jettop−tag (%) 53.0 ± 3.7

Top-tagged events in Data 189Background events in control region 40.6 ± 4.2Estimated top events in simulation 121.2 ± 6.5Data-driven top background estimate 131.7 ± 12.7Data/MC Ratio 1.09 ± 0.20

Table 8.2: Estimation of top backgrounds in the 0-jet bin

µµ ee eµ µe Total10.8 ± 2.4 9.1 ± 1.2 28.7± 2.9 11.4 ± 1.8 60.0 ± 4.3

Table 8.3: Estimation of the W+jets background at the final selection level for differentlepton flavour final states.

Final state Rout/inMC N control,data

`` N signal,dataDY N signal,MC

DY data/MCsame flavour 0.182 ± 0.019 372 41.0 ± 6.0 10.2 ± 1.8 4.0

Table 8.4: Estimation of the Drell-Yan background at the final selection level for sameflavour final state.

Table 8.5 lists the data-driven background estimates and data yields for the selection.

Finally, for an integrated luminosity of 3.5 fb−1 collected by CMS during 2012 at 8TeV, the measured cross section is:

σWW = 69.86± 2.79 (stat.)± 5.58 (syst.)± 3.07 (lumi.) pb

(8.2)

to be compared with the current NLO theoretical prediction at 8 TeV [79]:

σ(gg→WW + qq→WW) = 57.25 pb(

+4.1%−2.8%

)(8.3)

The total systematic uncertainty is approximately a 8.0%.

98


Figure 8.1: b-tagging discriminator for jets with 10 < pT < 30 GeV in the 1-tagged highpT jet defined to estimate the top tagging efficiency. Events in the denominator (left) and inthe nominator (right).

sample yield ± stat. ± syst.gg → WW 43.3 ± 1.0 ± 13.4qq → WW 640.3 ± 4.9 ± 47.4tt+tW 131.6 ± 12.7 ± 19.5W+jets 60.0 ± 4.3 ± 21.6WZ+ZZ 27.4 ± 0.5 ± 2.9Z/γ∗ 42.5 ± 6.0 ± 9.9Wγ + Wγ∗ 13.6 ± 2.4 ± 4.3total background 275.2 ± 14.9 ± 31.2signal + background 958.8 ± 15.7 ± 58.3data 1111

Table 8.5: Yields and expected predictions for 3.5 fb−1 at 8 TeV. The prediction for theWW signal processes assumes the SM cross section value.

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8. RESULTS

Figure 8.2: Distributions of the leading lepton transverse momentum (pTmax), the trailinglepton transverse momentum (pTmin) the dilepton transverse momentum (pT ll) and the in-variant mass (mll) at the final selection level, reweighted to the data-driven estimates. WWdistribution has been reescaled to the measured cross section. All four channels (ee, µµ, eµand µe) are combined, and the uncertainty band corresponds to the statistical and systematicuncertainties on the predicted yield.

100


8.1.3 WW cross section measurement at 8 TeV in each lep-tonic channel

The cross section estimation is done for each of the four channels considered in theanalysis (µµ, µe, eµ and ee) since not all the channels are equally affected by thedifferent systematic uncertanties. Drell-Yan and W+jets estimation are taken directlyfrom their channel estimation. For top estimation, the value for the inclusive scalefactor is taken.

– µµ Channel

The efficiencies are weighted correctly for gg and qq processes and the totalefficiency for the signal is found to be (0.715± 0.01 (stat.)± 0.06 (syst.))%.

Sample Yield ± stat. ± syst.gg→WW 10.2 ± 0.5 ± 3.2qq→WW 141.6 ± 2.3 ± 10.5tt+tW 28.7 ± 3.3 ± 4.2W+jets 10.8 ± 2.4 ± 3.9WZ+ZZ 9.8 ± 0.3 ± 0.8

Z/γ∗ 25.4 ± 4.5 ± 3.7W+γ 0.4 ± 0.1 ± 0.1

Total Background 75.1 ± 6.1 ± 6.9Signal + Background 226.9 ± 6.5 ± 12.9

Data 243

Table 8.6: Data yields and expected predictions in 3.5 fb−1 for µµ channel. The predictionfor the W+W− process assumes the SM cross section value.

Hence, the estimated cross section for the µµ channel, considering backgroundand data yields from Table 8.6 is:

σWW = 64.36 ± 5.87 (stat.) ± 3.22(lumi.) ± 5.65 (syst.) pb

– µe Channel

The total efficiency for the WW process is (0.931± 0.01 (stat.)± 0.07 (syst.))%.The estimated cross section for µe channel is found to be:

σWW = 73.74 ± 5.09 (stat.) ± 3.69(lumi.) ± 5.63 (syst.) pb

– eµ Channel

The total efficiency for the WW process is (1.130± 0.01 (stat.)± 0.07 (syst.))%.

The estimated cross section for eµ channel is:

σWW = 74.56± 4.76 (stat.) ± 3.73 (lumi.) ± 6.07 (syst.) pb

– ee Channel

The total efficiency for the WW process is (0.444± 0.01 (stat.)± 0.03 (syst.))%

The estimated cross section for ee channel is:

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8. RESULTS


Z/γ∗ 0.2 ± 0.2 ± 0.03W+γ 3.2 ± 0.7 ± 0.5


Data 310

Table 8.7: Data yields and expected predictions in 3.5 fb−1 for µe channel. The predictionfor the W+W− process assumes the SM cross section value.


Z/γ∗ 1.3 ± 0.4 ± 0.2W+γ 4.9 ± 0.8 ± 0.8


Data 399

Table 8.8: Data yields and expected predictions in 3.5 fb−1 for eµ channel. The predictionfor the WW process assumes the SM cross section value.


Z/γ∗ 15.5 ± 2.9 ± 3.5W+γ 5.1 ± 2.0 ± 0.9


Data 159

Table 8.9: Data yields and expected predictions in 3.5 fb−1 for ee channel. The predictionfor the WW process assumes the SM cross section value.

102


σWW = 67.82 ± 7.64 (stat.) ± 3.39 (lumi.) ± 6.53 (syst.) pb

All the different WW cross-section estimations are compared with the inclusive ex-pected NLO value in Figure 8.3.

The results presented in this section represent the first measurement of the productioncross section of this diboson final state at 8 TeV.

Figure 8.3: WW cross-section estimated values with 3.5 fb−1 and compared with the NLOexpectation.

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8. RESULTS

8.2 H → WW results

In this section the final results of the search for the SM Higgs boson in the H →WW → 2l2ν are presented.

8.2.1 Cut based analysis

The analysis method has already been described in 6. Figures from 8.4 to 8.6 showthe the comparison of kinematic distributions between the prediction and the dataafter the full mass-dependent selection but the cut on the distributions shown, in the0- and 1-jet bins splitted in same-flavour and different flavour for a Higgs mass of 125GeV/c2. The simulation is scaled to the data-driven estimates. In the mll, mT and∆φ distributions a clear excess is observed over the background prediction.

In order to statistically quantify the compatibility of the observation with S+B hy-pothesis the CLs expected and observed limits are shown in Figure D.2 and Table D.3in the Higgs mass range of 110 GeV to 600 GeV, combining all channels and all jetcategories using an integrated luminosity of 4.9 fb−1 of 7 TeV data. Figure 8.7 showsthe observed and expected limits at the end of 2011, the [127.5-600] GeV/c2 massrange was excluded at that time at 95% C.L.

The results for the 19.5 fb−1 of 8 TeV data are found in Figure D.3 and Table D.5.The yields with the different data-driven estimation for the backgrounds for both 7TeV and 8 TeV can be found in Appendix D.

Table 8.10 and Figure 8.8 show the expected and observed 95% CL upper limits onthe cross section times branching fraction, relative to the SM Higgs expectation, forthe cut-based approach using the full 2011 and 2012 dataset.

104


Higgs mass Observed Median 68% Range 95% Range Observed ExpectedGeV/c2 limits limits significance significance

110 6.62 3.45 [2.39, 4.98] [1.80, 6.90] 2.03 0.65115 3.21 1.68 [1.17, 2.42] [0.88, 3.36] 2.04 1.30120 1.76 1.02 [0.72, 1.45] [0.53, 2.00] 1.79 2.09125 1.28 0.70 [0.50, 0.99] [0.37, 1.35] 1.98 2.97130 1.03 0.52 [0.37, 0.74] [0.28, 1.01] 2.19 3.91135 0.80 0.40 [0.29, 0.56] [0.21, 0.76] 2.37 5.03140 0.59 0.32 [0.23, 0.45] [0.17, 0.62] 2.02 6.01150 0.43 0.22 [0.16, 0.31] [0.12, 0.42] 2.56 7.98160 0.22 0.11 [0.08, 0.16] [0.07, 0.22] 2.30 11.24170 0.18 0.12 [0.09, 0.17] [0.07, 0.23] 1.47 10.33180 0.26 0.18 [0.13, 0.25] [0.10, 0.34] 0.00 8.12190 0.35 0.29 [0.21, 0.41] [0.16, 0.56] 0.63 5.90200 0.55 0.41 [0.29, 0.58] [0.22, 0.79] 1.04 4.61250 0.72 0.71 [0.50, 1.01] [0.38, 1.40] 0.14 2.83300 0.85 0.83 [0.59, 1.19] [0.44, 1.64] 0.00 2.40350 0.69 0.69 [0.49, 0.98] [0.36, 1.37] 0.00 2.89400 0.66 0.68 [0.48, 0.97] [0.36, 1.35] 0.00 2.85450 0.58 0.74 [0.53, 1.05] [0.40, 1.46] 0.00 2.54500 0.70 0.96 [0.68, 1.39] [0.51, 1.95] 0.00 1.99550 1.15 1.25 [0.88, 1.84] [0.65, 2.65] 0.00 1.65600 1.51 1.65 [1.13, 2.48] [0.83, 3.70] 0.00 1.33

Table 8.10: Expected and observed cut-based upper limits for all the lepton flavour channelsand 0 and 1 jet bins combined using 4.9 fb−1 of 7 TeV and 19.5 fb−1 of 8 TeV data.

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8. RESULTS

Figure 8.4: mll distributions at the mH = 125 GeV/c2selection level in the 0-jet (left)and 1-jet (right) bins in the same-flavour (top) and different flavour (bottom) final states,reweighted to the Higgs selection level data-driven estimates. Cuts on the plotted variableare omitted.

106


Figure 8.5: ∆φ distributions at the mH = 125 GeV/c2 selection level in the 0-jet (left)and 1-jet (right) bins in the same-flavour (top) and different flavour (bottom) final states,reweighted to the Higgs selection level data-driven estimates. Cuts on the plotted variableare omitted.

107

8. RESULTS

Figure 8.6: mT distributions at the mH = 125 GeV/c2 selection level in the 0-jet (left)and 1-jet (right) bins in the same-flavour (top) and different flavour (bottom) final states,reweighted to the Higgs selection level data-driven estimates. Cuts on the plotted variableare omitted.

108


Figure 8.7: Expected and observed limits at the end of the 2011 data taking for the fullmass range (up) and for the low mass range (bottom).

109

8. RESULTS

Higgs mass [GeV]

SM

σ/σ95

% C

L lim

it on

-110

1

10

210

110 200 300 400 500 600

CMS preliminaryν 2l2→ WW →H

(8 TeV)-1 (7 TeV) + 19.5 fb-14.9 fb

median expectedσ 1± expected σ 2± expected

observed=125GeV)

H signal injection (m

Figure 8.8: Expected and observed cut-based upper limits for the 0 and 1 jet bins combined.

110


Figure 8.9: The input distributions for the mll shape analysis for DF events and for a Higgsmass of 130 GeV/c2with the 7 TeV luminosity.

8.2.2 Single variable analysis

– Results at 7 TeV

The preselection for the 1D shape analysis consists on the WW selection plusthe full selection used for the sequential analysis except for the cuts on the mll

variable itself as described in section 6.2.3. In figure 8.9 the distribution of mll

at the same level for the Higgs mass 130 GeV/c2 selection is shown.

In Figure 8.10 the expected and observed exclusion limits with the mll shapeanalysis in the Higgs mass range of 110 GeV to 600 GeV are showed. All thechannels and all jet bins are combined. For the 2 jets bin the same sequential cuts

111

8. RESULTS

selection presented in [70] has been used. While expected limits are computedonly with the CLs approach, the observed exclusion range both for the bayesianand the CLs approach is showed.

The results show a good statistical agreement between the data and the back-ground only hypothesis in the region where this analysis is sensitive to the SMHiggs boson. An exclusion is derived in the mass range [140-230] GeV/c2 at 95%C.L. with the Bayesian approach. With the CLs method, the observed exclusionrange is [133-230] GeV/c2at 95%. In absence of signal the expected exclusionmass range is [126-230] GeV/c2 at 95% C.L (CLs).

– Results at 8 TeV

The following section details the results obtained for the mll shape at N-1 se-lection level using 19.5 fb−1 of 8 TeV data. Further studies using differentkinematic variables and selections can be found in Appendix A. The sensitivityof the analysis depends on the separation power the variable has for the signalagainst various backgrounds. The results for the different cases are found tobe compatible to one another, with some difference in observation at low mass,which arises from the constraints the shapes have on various backgrounds.

The data to simulation comparison of the m`` distribution for different-flavourevents can be seen in Figure 8.11. Bayesian limit calculation with the full m``

output distributions for the different flavour is used. These limits can be seenin 8.12.

112


Figure 8.10: Expected and observed mll shape-based upper limits for the 0, 1 and 2 jet binscombined for the 7 TeV luminosity.

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8. RESULTS

Figure 8.11: The input distributions for the mll shape analysis for DF events and for aHiggs mass of 125 GeV/c2with the 8 TeV luminosity.

114


Figure 8.12: Expected and observed upper limits for the 0 jets and 1 jet DF bins combinedfor m`` shape analysis at N − 1 selection level for the 8 TeV luminosity (cut based results areused for the SF).

115

8. RESULTS

– Results with the full Run I dataset

The results obtained using the full Run I dataset (4.6 fb−1 at 7 TeV and 19.5fb−1 at 8 TeV) have been combined. For the SF events the cut based analysishas been used while for the DF events the 2D approach in which the mT is addedto the mll as input distribution to optimize the significance result has been used.More details about the mll-mT approach (2D shape analysis) can be found inAppendix B. Table 8.11 shows the results for 7+8 TeV analysis using 2D inputsfor the eµ channel in 0/1-jet bins together and the cut based approach for allthe other channels. Figure 8.13 shows the observed and expected significance foreach Higgs mass hypothesis for the combined 7+8 TeV analysis together. Thesignificance value for a Higgs mass of 125 GeV/c2 is 4.32 using the full 2011 and2012 dataset. The best fit value of the signal strength (µ) for the combined 7+8TeV analysis is shown in Figure 8.14 as a function of the Higgs mass. The bestfit value for mH = 125 GeV/c2 is µ = 0.68+0.35

−0.35.

Figure 8.13: The observed and expected significance for each Higgs mass hypothesis for thecombined 7+8 TeV analysis. The dashed line shows the significance expected for the searchfor a Higgs boson with a mass mH if a Higgs boson of this mass exists. The solid line andcolored bands show the expected significance at a mass mH if the true Higgs boson mass is125 GeV. The dots show the observed significance of the excess for the search for a Higgsboson with a mass mH .

116


Table 8.11: Expected and observed upper limits for all the 0, 1 and 2 jet bins combinedusing 4.9 fb−1 of 7 TeV and 19.5 fb−1 of 8 TeV data. For eµ channel in 0/1-jet bins the 2Dinputs are used, and for the rest of the channels cut-based inputs are used.


110 6.61 2.46 [1.78, 3.42] [1.34, 4.54] 2.91 0.96115 3.52 1.23 [0.89, 1.71] [0.67, 2.28] 3.84 1.74120 2.09 0.71 [0.51, 0.98] [0.38, 1.30] 3.93 2.86125 1.27 0.48 [0.34, 0.66] [0.26, 0.88] 3.08 4.20130 0.90 0.33 [0.24, 0.46] [0.18, 0.61] 3.40 5.94135 0.73 0.26 [0.19, 0.36] [0.14, 0.48] 3.56 7.45140 0.58 0.21 [0.15, 0.29] [0.11, 0.38] 3.68 8.95150 0.44 0.15 [0.11, 0.20] [0.08, 0.27] 3.24 12.10160 0.21 0.08 [0.06, 0.12] [0.05, 0.16] 2.99 18.90170 0.20 0.09 [0.07, 0.13] [0.05, 0.17] 2.25 16.83180 0.23 0.13 [0.10, 0.18] [0.07, 0.24] 1.41 12.57190 0.33 0.21 [0.15, 0.29] [0.11, 0.38] 1.20 8.82200 0.50 0.28 [0.20, 0.39] [0.15, 0.52] 1.56 6.66250 0.58 0.51 [0.37, 0.71] [0.28, 0.94] 0.00 3.96300 0.46 0.51 [0.37, 0.71] [0.28, 0.95] 0.00 3.54350 0.28 0.48 [0.35, 0.67] [0.26, 0.88] 0.00 4.01400 0.25 0.51 [0.37, 0.71] [0.28, 0.95] 0.00 3.70450 0.27 0.57 [0.41, 0.79] [0.31, 1.06] 0.00 3.04500 0.45 0.80 [0.58, 1.12] [0.44, 1.48] 0.00 2.31550 0.79 0.95 [0.68, 1.32] [0.51, 1.75] 0.00 1.94600 0.90 1.12 [0.81, 1.55] [0.61, 2.06] 0.00 1.63

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8. RESULTS

Figure 8.14: The best fit value of the signal strengh (µ) for the combined 7+8 TeV analysis.

118

8.3 Higgs combination: Observation of a new particle

8.3 Higgs combination: Observation of a new par-

ticle

One of the milestones of the 2012 LHC data taking was to collect a similar amountof luminosity as in the full 2011 run. Once this goal was achieved, both the CMS andATLAS collaborations examined the result and combined [86] the five most importantHiggs decay modes using the data samples corresponding to integrated luminositiesof up to 5.1 fb−1 at 7 TeV and 5.3 fb−1 at 8 TeV. The five decay modes included inthis combination were: γγ, ZZ, WW, ττ and bb. An excess of events was observedabove the expected background, with a local significance of 5.0 σ, at a mass near125 GeV/c2, indicating the production of a new particle [87]. The expected localsignificance for a standard model Higgs boson of that mass is 5.8 σ. The observedlocal p-value for the five decay modes and for the combination at the time of theobservation can be seen in figure 8.15. The p-value is defined as the probabilityto obtain a certain value at least as large as the one observed in data under thebackground-only hypothesis.

For this combination the H → WW expected local significance for mH = 125 GeV/c2

was 2.4σ while the observed one was 1.6 σ.

Figure 8.15: The observed local p-value for the five decay modes and the overall combinationas a function of the SM Higgs boson mass. The dashed line shows the expected local p-valuesfor a SM Higgs boson with a mass mH . Dark blue line corresponds to the H → WWcontribution to the final p-value.

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8. RESULTS

As a consequence of the observation of this new particle the next milestone of theLHC running was to provide enough luminosity to start measuring its properties andto consolidate the observation. The results for the combination of the different Higgssearches at CMS has recently been updated with the full 2011 and 2012 data [88].

The four main Higgs boson production mechanisms can be associated with eitherfermion couplings (gluon-gluon fusion and ttH) or vector boson couplings (VBF andVH). Therefore, a combination of channels associated with a particular decay modeand explicitly targeting different production mechanisms, can be used to test therelative strengths of the couplings to the vector bosons and the top quark. Figure8.16 shows 68% CL intervals for the signal strength associated with the gluon-gluon-fusion-plus-ttH and the VBF-plus-VH production mechanisms, µggH,ttH and µVBF,VH,respectively. The five sets of contours correspond to the five combinations by decaymode. The SM Higgs boson point (1,1) is within the 68% CL regions for each of thesechannels. The mass of the new boson has been measured from the γγ and H → ZZchannels since they present an excellent mass resolution. The measured mass valueis mH =125.7 ± 0.3 (stat.) ± 0.3 (syst.) GeV/c2.

Figure 8.16: The 68% CL intervals for signal strength in the gluon-gluon-fusion-plus-ttH andin VBF-plus-VH production mechanisms: µggH,ttH and µVBF,VH respectively. The differentcolors show the results obtained by combining data from each of the five analayzed decaymodes: γγ (green), WW (blue), ZZ(red), ττ (violet), bb (cyan). The crosses indicate thebest-fit values. The diamond at (1,1) indicates the expected values for the SM Higgs boson.

Table 8.12 summarises the median expected and observed local significance for a SMHiggs boson mass hypothesis of 125.7 GeV from the individual decay modes. Thelow probability for an excess at least as large as the observed one coming from a

120


statistical fluctuation of the background leads to the conclusion that the observationof a new particle with a mass near 125 GeV in the γγ, ZZ → 4l and WW → 2l2νchannels is confirmed. The excess in the bb is consistent with expectation in the bband ττ channels. The γγ, ZZ → 4l decay modes indicate that the new particle is aboson, and the diphoton decay implies that its spin is different from one.

Decay mode Expected (σ) Observed (σ)ZZ 7.1 6.7γγ 3.9 3.2

WW 5.3 3.9bb 2.2 2.0ττ 2.6 2.8

Table 8.12: The median expected and observed significances of the excesses in the com-bination of individual decay modes for a SM Higgs boson mass hypothesis of 125.7 GeV.

Once the observation is made the first thing to check is the compatibility of theobservation with the SM Higgs prediction. This can be quantified in terms of thesignal strenth µ = σ/σSM . The µ as a function of the Higgs mass when the fivechannels are combined can be seen in Figure 8.17. The results can be also computedfor the different decay modes (Figure 8.18) and production modes (Figure 8.19). Theplots show a good level of compatibility between all the channels contributing tothe combination. None of the sub-combinations departs from the SM Higgs bosonhypothesis,µ = 1, by a significant deviation with respect to their current individualsensitivities. The final combined result is found to be µ = 0.80±0.14 for mH = 125.7GeV/c2.

To determine the identity of the new boson, it is crucial to measure its quantumnumbers. Information from the spin can be obtained from H → WW , H → ZZ andH → γγ separately. Figure 8.20 show the post-fit model distributions of the spintest statistic for the WW and ZZ combined. The observed results indicate that thespin and parity of the new boson observed is compatible with 0+ as is expected for aStandard Model Higgs.

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8. RESULTS

Figure 8.17: Values of µ = σ/σSM for the combination (solid vertical line) and for con-tributing channels (points). The vertical band shows the overall µ value 0.80 ± 0.14. Thehorizontal bars indicate the ±1σ uncertainties on the µ values for individual channels. Theyinclude both statistical and systematic uncertainties.

122


Figure 8.18: Values of µ = σ/σSM for the sub-combinations by decay mode. The horizontalbars indicate the ±1σ uncertainties on the µ values for individual channels. They includeboth statistical and systematic uncertainties. The vertical dashed line indicates the predictionfor a SM Higgs boson.

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8. RESULTS

Figure 8.19: Values of µ = σ/σSM for the sub-combinations grouped by a signature enhanc-ing specific production mechanisms. The horizontal bars indicate the ±1σ uncertainties onthe µ values for individual channels; they include both statistical and systematic uncertainties.The vertical dashed line indicates the prediction for a SM Higgs boson.

124


Figure 8.20: Post-fit model distributions of the test statistic for the WW and ZZ combinedcomparing the signal JP hypotheses 0+ and 2+

m(gg) in the best fit to the data. The observedvalue is indicated by the arrow and disfavours the 2+

m(gg) signal hypothesis with a CLs valueof 0.6%.

125

8. RESULTS

The next step in the characterization of the new boson properties is to check thecompatibility of the observed data with the SM Higgs boson couplings. The Higgsboson couplings have been tested in different scenarios. Event yields in a specific(production) × (decay) channel are assumed to be related to production cross-sectionand decay widths:

σ(H)×BR(jj→ Hxx) = σ × Γ/ΓH

Introducing effective couplings κj such that Γjj = κ2j ·ΓSMjj is possible to measure devi-

ations from the SM couplings by measuring ratios with respect to the SM prediction.

The tree-level relations between the W and Z boson masses, mW/mZ , and theircouplings to the Higgs boson are protected against large radiative corrections, aproperty known as ”custodial symmetry”. The H → WW process together withthe H → ZZ is then fundamental to check these couplings. Checking the custodialsymmetry by measuring H→WW/H→ZZ couplings indicates us if the new observedboson is Higgs-like. Figure 8.21 shows the 1D statistics q(λWZ) scan with respect tothe coupling modifier ratio λWZ.

Figure 8.21: 1D test statistics q(λ(WZ)) scan with respect to the coupling modifier ratioλ(WZ), profiling the coupling modifier κZ and all other nuisances. The coupling to fermionsis taken to be the SM one (κ = 1).

The measured result for λWZ = κW/κZ , λWZ ∈ [0.62, 1.19] at 95% C.L, is compatiblewith the custodial symmetry as it is predicted in the Standard Model.

126


Other tests have been performed regarding the SM boson couplings. A summary ofthese compatibility studies can be found in 8.22.

Figure 8.22: Tests of the compatibility of the data with the SM Higgs boson couplings andthe 95% CL intervals for evaluated scaling factors. When one of the scaling factors (κi) in agroup is evaluated, the other are treated as nuisance parameters. Scaling factors not listedexplicitly in a group are taken to be one.

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8. RESULTS

128

9

Conclusions

This thesis presents the search for the Standard Model Higgs in the H → WWchannel when both W bosons decay leptonically using the full luminosity collectedduring 2011 and 2012 by the CMS detector at the LHC. The analysis describedin this document is the result of years of optimization and exhaustive studies alwaysadapting to the changing conditions and scenarios in LHC [89]. To claim the discoveryof new physics, an excess in the significance of at least 5σ must be obtained. Theculmination of all this work is gathered in [87], where the observation of a new particle,potentially the Higgs boson, with a mass of around 125 GeV/c2 is reported with anobserved significance of 5σ. This major physics achievement has been performedcombining the result in this thesis with other four decay channels in CMS: γγ, ZZ,ττ and bb. Details about the Higgs combination leading to the final result can befound in [88]. The local significance in the H → WW channel at the time of theobservation publication for a mH = 125 GeV/c2 was 1.6 σ. The observation tookplace in the middle of 2012 using the full luminosity from the 2011 data taking (5.1fb−1) and 5.3 fb−1 from the 2012 dataset. This corresponds to less than half of thetotal luminosity collected at the end of 2012.

In this work the results of the SM Higgs search in the H → WW channel using allthe luminosity at 7 TeV and 8 TeV (around 25 fb−1) have been presented togetherwith the WW production cross section measurement. The analysis approach changedfrom 2011 to 2012. During the most part of 2011 the main goal of the H → WWanalysis was to narrow the Higgs mass window by excluding as much mass regions aspossible within the mH range studied. After the first hints of the presence of the SMHiggs at the end of 2011, the analysis carried out in 2012 was focused on optimizingthe sensitivity of the channel for the low mass region.

The WW process is sensitive to searches for New Physics and the main backgroundprocess for the Higgs boson search in the decay channel H→WW, therefore a essentialpiece in the observation and characterization of the Standard Model Higgs boson.The qq→WW production mode via s-channel in particular is sensitive to WWZ andWWγ trilinear gauge couplings (TGC) measurements. A significant higher value forthe measured cross section for WW, compared with the expectations, could mean thepresence of anomalous TGC, or other new physics with similar final states.

129

9. CONCLUSIONS

Events with two high pT isolated leptons, large amount of EmissT and no high pT

jets, were selected for the estimation of the WW production cross section. Thesignal efficiency was extracted from simulation while the major background, as in theH → WW case, have been estimated using data driven methods. Minor backgrounds,such as WZ or ZZ, were taken directly from Monte Carlo.

The cross section experimental value using the full 2011 dataset [90] was found to be:


This value is 1-σ deviated from the latest theoretical prediction:

σ(WW) = 47.04 pb(

+4.3%−3.2%

)During 2012 the WW cross section was also measured at a center of mass energy of8 TeV for 3.54 fb−1. The analysis was adapted to the new running conditions of theLHC and the selection reoptimized. The first 3.54 fb−1 of integrated luminosity at 8TeV was used for the WW cross section measurement. The measured value [76] wasfound to be:


to be compared with the SM expectation value at 8 TeV:

σ(WW) = 57.3(

+2.4−1.6

)pb

The fully leptonic signature in the H → WW channel includes two high pT isolatedleptons and large missing energy due to the neutrinos that can not be detected. Inorder to maximize the significance the events are classified in three different categoriesdepending on the number of high pT jets in the final state. For each category theevents are split into same flavour events(µµ and ee) and different flavour events (eµand µe). The top quark background is mainly rejected by applying two different kindsof b quark veto: lifetime based and softmuon based. The Drell-Yan background isdrastically reduced by removing the most part of Z events in a mass window closeto mZ and applying a tight cut in the Emiss

T variable for the same flavour events.The WW background is almost irreducible but is controlled with a specific set of cutsoptimized for each of the Higgs masses under study. The main discriminating variableto reduce this background is the ∆φ between the two selected leptons. This observabletends to be flat in the case of the WW background and close to zero in the case of thesignal due to the scalar nature of the SM Higgs boson and spin correlations. Data-driven methods are used to estimate the main background contributions (W+jets,top, DY and WW).

The result obtained in this thesis can be summarized in Figure 10.1 where the ob-served and expected significance for each Higgs mass hypothesis for the combinationof the 7 TeV and 8 TeV analysis is showed. The value of the significance for a Higgsmass of 125 GeV/c2 is 4.32 using the full 2011 and 2012 dataset. The best fit value

130

Figure 9.1: The observed and expected significance for each Higgs mass hypothesis for thecombined 7+8 TeV analysis. The dashed line shows the significance expected for the searchfor a Higgs boson with a mass mH if a Higgs boson of this mass exists. The solid line andthe colored bands show the expected significance at a mass mH if the true Higgs boson massis 125 GeV. The dots show the observed significance of the excess for the search for a Higgsboson with a mass mH .

of the signal strength (µ) is shown in Figure 10.2 as a function of the Higgs mass.For mH = 125 GeV/c2 the best fit value is µ = 0.68+0.35

−0.35.

The final result in this work has been performed for two different selections: a cutbased approach and a shape analysis based on the full shape of a single discriminatingvariable. Detailed explanations and studies can be found in [91].

The results for the single variable approach with the 2011 dataset were obtained usingthe full mll shape at the so called N-1 level. An exclusion was derived in the massrange [140–230] at 95% C.L. with the Bayesian approach. With the CLs method, theexclusion range is [133–230] at 95%. In absence of signal the expected exclusion massrange is [126–230] at 95% C.L (CLs).

For the 2012 dataset, the final results for the 1D shape analysis are given using theshape of three different variables: mT , an unboosted razor variable (2MR) and mll.The shapes were taken at WW selection level (see Section 6.1) adding some looseadditional cuts. The same N-1 approach as in 2011 was also used for the mll variable.

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9. CONCLUSIONS

Figure 9.2: The best fit value of the signal strengh (µ) for the combined 7+8 TeV analysisas a functin of the Higgs mass.

The results in this thesis were combined with those from the ZZ, γγ, ττ and bbdecay modes giving excess of events above the expected background at a mass near125 GeV/c2, indicating the presence of a new particle with the properties of a boson.The consistency of the couplings of the observed boson with those predicted for theSM Higgs boson has been tested and no significant deviations have been found. Thespin of this new particle is also under study. The decay to two photons indicatesthat the new particle is a boson with spin different from one. Up to now all the testsperformed in terms of spin and possible couplings indicates that the boson observedis the Standard Model Higgs boson. The restart of the LHC operations foreseen for2015 will allow to study more deeply and precisely the properties of this new boson.

In summary, the work presented in this thesis has produced several relevant resultsin the first period of the LHC operation, leading among others to the first Higgspublication [89] at a energy scale never explored before. The analysis has evolvedfollowing the LHC conditions and at the end of 2011 [91] the H → WW channel wasable to exclude by itself the full mass range under study except for the masses between[114.4-127.5] GeV/c2 at 95% CL where an excess started already to arise. During2012 all the Higgs analysis at CMS and ATLAS were focused in maximizing thesensitivity in that mass region and understanding the most important backgrounds inthe different Higgs searches. The continuum WW production is the main background

132

to the H → WW process. The first measurement of its production cross section at 8TeV has been performed in this work and is published in [76]. In the middle of 2012the luminosity collected at 8 TeV was similar to the full 7 TeV dataset. At that timethe observation of a new boson compatible with the Standard Model Higgs boson wasmade [87] combining the results presented in this thesis with those from the othermain decay modes. This observation was presented at the same time by CMS andATLAS leading to one of the major physics achievement of the last decades.

133

9. CONCLUSIONS

134

10

Conclusiones

Esta tesis presenta la busqueda del boson de Higgs del Modelo Estandar en el canalde H → WW donde los dos bosones W se desintegran leptonicamente utilizandotoda la luminosidad recogida durante 2011 y 2012 por el detector CMS en el LHC. Elanalisis descrito en este documento es el resultado de anos de optimizacion y estudiosexhaustivos adaptandose a las condiciones y escenarios cambiantes del LHC [89]. Paradeclarar nueva fısica, se debe observar un exceso con una significancia estadıstica de almenos 5σ. La culminacion de todos estos anos de trabajo esta recogida en [87], dondese presenta la observacion de una nueva partıcula, potentialmente el boson de Higgs,con una masa alrededor de 125 GeV/c2 con una significancia observada de 5σ. Esterelevante logro para la fısica se ha conseguido combinando los resultados de esta tesiscon otros cuatro canales de desintegracion en CMS: γγ, ZZ, ττ y bb. Los detalles dela combinacion que dio lugar al resultado final pueden verse en [88]. La significancialocal en el canal H → WW en el momento de publicarse la observacion para mH =125 GeV/c2 era 1.6 σ. La observacion tuvo lugar a mediados de 2012 usando toda laluminosidad recogida durante 2011 (5.1 fb−1) y 5.3 fb−1 de los datos de 2012. Estaluminosidad corresponde a menos de la mitad del total de datos recogidos al final de2012.

En este trabajo se han presentado los resultados de la busqueda del boson de Higgsen el canal H → WW usando toda la luminosidad a 7 TeV y 8 TeV (aproximada-mente 25 fb−1) junto con la medida de la seccion eficaz de produccion del procesoWW. La estrategia ha cambiado de 2011 a 2012. Durante la mayor parte de 2011 elprincipal objetivo del analisis en el canal H → WW era cerrar la ventana de masadel boson de Higgs, excluyendo la mayor region de masa posible dentro del rangoestudiado.Despues de los primeros indicios de la presencia del boson de Higgs delmodelo estandar a finales de 2011, el analisis llevado a cabo en 2012 estuvo focalizadoen optimizar la sensibilidad del canal en la region de baja masa.

El proceso WW es sensible a busquedas de nueva fısica y el principal fondo parala busqueda del boson de Higgs en el canal de desintegracion H → WW, y por ellouna pieza esencial en la observacion y caracterizacion del boson de Higgs del modeloestandar. La produccion qq → WW mediante el canal-s es particularmente sensiblepara la medida de los Acoplamientos Gauge Triliniales (AGT) WWZ y WWγ. Unvalor significativamente mas alto de la seccion eficaz de WW, comparado con las

135

10. CONCLUSIONES

expectativas, podrıa ser un indicio de la presencia de AGT anomalos u otros procesosde nueva fısica con un estado final similar.

Para la estimacion de la seccion eficaz de produccion de WW se han seleccionadosucesos con dos leptones de alto momento transverso (pT ), energıa transversa fal-tante (Emiss

T ) y sin ningun jet de alto pT . La eficiencia senal ha sido obtenida de lasimulacion mientras que los principales fondos, como en el caso del analisis H → WW ,han sido estimado utilizando metodos basados en datos. Los fondos menos impor-tantes, como el WZ o el ZZ, han sido tomados directamente de la simulacion de MonteCarlo.

La seccion eficaz medida utilizando todos los datos recogidos en 2011 [90] es:


Este valor tiene una desviacion de 1-σ respecto de la ultima prediccion teorica.

σ(WW) = 47.04 pb(

+4.3%−3.2%

)Durante 2012 la seccion eficaz del proceso WW ha sido medida para una energıa decentro de masas de 8 TeV y una luminosidad de 3.54 fb−1. El analisis ha sido adaptadoa las nuevas condiciones de funcionamiento del LHC y la seleccion reoptimizada. Elvalor medido obtenido es:


A comparar con el valor teorico a 8 TeV:

σ(WW) = 57.3(

+2.4−1.6

)pb

El estado final del proceso H → WW cuando ambos W se desintegran leptonicamentepresenta dos leptones aislados con alto pT y Emiss

T debida a la presencia de los neutri-nos que escapan la deteccion. Para maximizar la significancia los sucesos se clasificanen tres categorıas diferentes dependiendo del numero de jets de alto momento. Paracada categorıa los sucesos estan dividido en sucesos con el mismo sabor leptonico(µµ y ee) y sucesos con diferente sabor leptonico (eµ y µe). El fondo procedente deprocesos asociados con el quark top se rechaza principalmente aplicando dos tipos deveto al quark b: uno basado en su largo tiempo de vida medio y otro basado en laidentificacion de un muon producto de la desintegracion de un quark b. El fondo deDrell-Yan se reduce drasticamente eliminando los sucesos en una ventana de masacercana a la masa del Z y aplicando un corte duro en la variable de Emiss

T para lossucesos con dos leptones del mismo sabor. El fondo de WW es casi irreducible perose puede controlar con una seleccion optimizada para cada masa de Higgs que se estaestudiando. La variable con el mayor poder discriminante para reducir este fondo esel angulo en el plano transverso entre los dos leptones (∆φ). Este observable tiendea ser plano en el caso del fondo de WW y cercano a cero en el caso de la senal debido

136

a la naturaleza escalar del Higgs del modelo estandar y a correlaciones de spin. Losmetodos basados en datos (data-driven) se utilizan para estimar la contribucion delos principales fondos (W+jets, top, DY y WW).

El resultado obtenido en esta tesis esta resumido en la Figura 10.1 en la que semuestra la significancia esperada y observada para cada hipotesis de masa para lacombinacion del analisis a 7 y 8 TeV. El valor de la significancia para un boson deHiggs con masa de 125 GeV/c2 es 3.32 utilizando todos los datos recogidos en 2011y 2012. El mejor valor del ajuste para la intensidad de senal (µ) se muestra en laFigura 10.2 en funcion de la masa del Higgs. Para mH = 125 GeV/c2 el valor delmejor ajuste es µ = 0.68+0.35

−0.35.

Figure 10.1: La significancia esperada y observada para cada hipotesis de masa del Higgspara el analisis combinado de 7+8 TeV. La lınea discontinua muestra la significancia esperadapara la busqueda del boson de Higgs con una masa mH si dicho boson existiera. La lıneasolida y las bandas de colores muestran la significancia esperada para una masa mH si elboson de Higgs tuviera una masa de 125 GeV. Los puntos muestran la significancia observadadel exceso en la busqueda del boson de Higgs con masa mH .

El resultado final de este trabajo ha sido obtenido con dos selecciones diferentes:una seleccion secuencial y una seleccion basada en la forma de la distribucion deuna variable cinematica discriminante. Explicaciones detalladas y estudios se puedenencontrar en [91].

Los resultados del analisis basado en la forma usando los datos de 2011 fueron

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10. CONCLUSIONES

obtenidos utilizando la distribucion de la masa invariante al nivel conocido comoN-1, derivando un rango de exclusion en el intervalo de masa [140–230] al 95% C.L.con la aproximacion bayesiana. Con el metodo CLs, el intervalo de exclusion es [133–230] al 95%. En ausencia de senal el rango esperado de exclusion es [126–230] al 95%C.L (CLs).

Figure 10.2: El valor del mejor ajuste de la intensidad de senal (µ) para el analisis de 7+8TeV combinado en funcion de la masa del boson de Higgs.

Los resultados finales para el analisis unidimensional usando los datos de 2012 utilizanla distribucion de tres observables diferentes: mT , una variable razor (2MR) y mll.Las distribuciones se toman al llamado nivel WW (ver Seccion 6.1) anadiendo algunoscortes adicionales.

Los resultados de esta tesis fueron combinados con los obtenidos en los canales ZZ,γγ, ττ y bb obteniendose un exceso de sucesos sobre el fondo esperado para una masacercana a 125 GeV/c2, indicando la presencia de una nueva partıcula con propiedadesbosonicas. La consistencia de los acoplamientos del boson observado con los que seesperan del boson de Higgs del modelo estandar han sido estudiados y no se haencontrado ninguna desviacion significativa. El spin de esta nueva partıcula estatambien siendo estudiado. La desintegracion en dos fotones indica que la nuevapartıcula es un boson con spin distinto de 1. Hasta ahora los test que se han llevadoa cabo en cuanto a spin y acoplamientos indican que el boson observado es el bosonde Higgs del modelo estandar. Cuando el LHC vuelva a retomar su funcionamiento

138

hacia el ano 2015 se podran estudiar mas profundamente y con mayor precision laspropiedades de este nuevo boson.

El trabajo presentado en esta tesis ha dado lugar a varios resultados relevantes duranteel primer periodo de funcionamiento del LHC, llevando entre otras cosas a la primerapublicacion sobre la busqueda del boson de Higgs [89] a una energıa que no habıasido explorada nunca antes. El analisis ha evolucionado siguiendo las condicionesdel LHC y al final del ano 2011 [91] el canal H → WW fue capaz de excluir por sısolo todo el rango de masa estudiado excepto el intevalo entre [114.4-127.5] GeV/c2

al 95% CL donde un exceso empezaba a emerger. Durante 2012 todos los analisisde Higgs en CMS y ATLAS se centraron en maximizar la sensibilidad en esa regionde masa y en entender los fondos mas importantes en las diferentes busquedas deHiggs. La produccion de WW es el fondo principal para el proceso H → WW . Laprimera medida de su seccion eficaz de produccion a 8 TeV se ha llevado a cabo enesta tesis y ha sido publicada en [76]. A mediados de 2012 la luminosidad recogida a8 TeV era similar a la de todo el ano 2011 a 7 TeV. En ese momento se produjo laobservacion de un nuevo boson compatible con el boson de Higgs del modelo estandar[87] combinando los resultados presentados en esta tesis con los de los principalesmodos de desintegracion. La observacion fue presentada al mismo tiempo por CMSy ATLAS llevando a uno de los mayores logros para la fısica de las ultimas decadas.

139

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148

Appendix A

Further studies using the 1D shapeanalysis

This appendix presents the results for the 1D shape analysis using the distributionof the mT , 2MR and mll at preselection level as input.

A.1 Results with mT -shape analysis

In this subsection the data to simulation comparison of the mT distributions at 2Dshape selection, for different-flavor events, and for the 0- and 1-jet bins is reported.This comparison is shown in Figure A.1. Bayesian limit calculation with the full mT

output distributions for the different flavour is used. Table A.1 and A.2 report thevalues of these limits. The Pre-Post fit normalisation ratio is shown in A.3.

149

A. FURTHER STUDIES USING THE 1D SHAPE ANALYSIS

Figure A.1: The input distributions for the mth-shape analysis in the different flavourchannel for 0 jets (left) and 1 jet (right) for mH = 125 GeV/c2 at 2D shape selection .

150


Figure A.2: Expected and observed upper limits for the 0 jets and 1 jet DF bins combinedfor mT shape analysis at 2D shape selection and cut based results for the SF.

151


Higgs mass Observed Expected 68% Range 95% Range Observed ExpectedGeV/c2 limits limits significance significance

110 9.27 5.14 [3.67, 7.33] [2.74, 10.22] 1.93 0.41115 4.50 2.49 [1.78, 3.56] [1.33, 4.94] 1.90 0.84120 2.46 1.38 [0.99, 1.97] [0.74, 2.72] 1.81 1.49125 1.81 0.87 [0.62, 1.24] [0.47, 1.72] 2.31 2.35130 1.31 0.61 [0.44, 0.87] [0.33, 1.21] 2.43 3.32135 1.08 0.47 [0.34, 0.67] [0.25, 0.93] 2.78 4.22140 0.91 0.39 [0.28, 0.55] [0.21, 0.76] 2.99 5.11145 0.75 0.33 [0.23, 0.46] [0.18, 0.63] 2.93 5.96150 0.52 0.29 [0.21, 0.40] [0.16, 0.55] 2.29 6.11155 0.44 0.23 [0.17, 0.33] [0.13, 0.44] 2.48 7.14160 0.29 0.14 [0.10, 0.20] [0.08, 0.27] 2.70 10.87170 0.27 0.15 [0.11, 0.21] [0.08, 0.29] 2.32 10.44180 0.36 0.21 [0.15, 0.29] [0.11, 0.40] 2.05 8.55190 0.54 0.34 [0.24, 0.48] [0.18, 0.66] 1.61 5.40200 0.68 0.44 [0.32, 0.63] [0.24, 0.86] 1.44 4.22250 1.24 0.93 [0.66, 1.31] [0.49, 1.82] 0.93 2.10300 1.49 0.97 [0.69, 1.40] [0.51, 1.94] 1.17 2.04350 1.22 0.81 [0.57, 1.17] [0.42, 1.64] 1.24 2.52400 1.03 0.79 [0.56, 1.13] [0.42, 1.57] 0.89 2.60450 0.90 0.86 [0.61, 1.23] [0.46, 1.72] 0.14 2.19500 1.40 1.23 [0.87, 1.77] [0.65, 2.52] 0.43 1.58550 2.52 1.60 [1.12, 2.37] [0.83, 3.44] 1.31 1.37600 2.83 2.16 [1.48, 3.29] [1.09, 4.92] 0.74 1.05

Table A.1: Expected and observed upper limits for the 0 jets and 1 jet DF bins combinedfor mT shape analysis at 2D shape selection and cut based results for the SF.

152


Figure A.3: Pre-Post fit normalisation ratio for 0-jet (top) and 1-jet processes (bottom)from B-only (left) and S+B (right) fit to all channels for 8 TeV data. Shape-based (mth at2D shape level) for DF.

153


A.2 Results with 2MR-shape analysis

In this subsection the data to simulation comparison of the 2MRdistributions at 2Dshape selection, for different-flavor events, and for the 0- and 1-jet bins is reported.This comparison is shown in Figure A.4. Bayesian limit calculation with the full2MR output distributions for the different flavour is used. Table A.2 and A.5 reportthe values of these limits. The Pre-Post fit normalisation ratio is shown in A.6.

Figure A.4: The input distributions for the 2MR shape analysis in the different flavourchannel for 0 jets (left) and 1 jet (right) for mH = 125 GeV/c2 at N-1 selection.

154


Figure A.5: Expected and observed upper limits for the 0 jets and 1 jet DF bins combinedfor 2MR shape analysis at 2D shape selection and cut based results for the SF.

155



110 3.96 2.88 [2.06, 4.09] [1.55, 5.64] 0.94 0.70115 2.09 1.51 [1.09, 2.13] [0.82, 2.91] 1.09 1.28120 1.18 0.90 [0.65, 1.27] [0.49, 1.73] 0.93 2.06125 0.91 0.61 [0.44, 0.87] [0.33, 1.18] 1.33 2.98130 0.73 0.46 [0.33, 0.64] [0.25, 0.88] 1.61 4.04135 0.65 0.37 [0.26, 0.52] [0.20, 0.71] 2.10 5.05140 0.56 0.31 [0.22, 0.43] [0.17, 0.59] 2.26 6.12145 0.48 0.26 [0.19, 0.37] [0.14, 0.51] 2.28 7.08150 0.38 0.23 [0.17, 0.33] [0.13, 0.45] 1.96 7.82155 0.33 0.19 [0.14, 0.27] [0.11, 0.37] 2.12 9.16160 0.24 0.13 [0.09, 0.18] [0.07, 0.24] 2.57 13.13170 0.22 0.14 [0.10, 0.19] [0.08, 0.26] 1.95 11.79180 0.29 0.19 [0.14, 0.27] [0.10, 0.37] 1.14 9.21190 0.45 0.30 [0.21, 0.42] [0.16, 0.58] 1.49 6.39200 0.56 0.39 [0.28, 0.56] [0.21, 0.77] 1.20 4.91250 1.11 0.86 [0.62, 1.22] [0.46, 1.69] 0.90 2.43300 1.00 0.85 [0.60, 1.22] [0.45, 1.69] 0.55 2.30350 0.80 0.68 [0.48, 0.98] [0.36, 1.38] 0.49 2.93400 0.74 0.68 [0.49, 0.98] [0.36, 1.37] 0.28 2.89450 0.66 0.82 [0.58, 1.16] [0.44, 1.62] 0.00 2.25500 1.08 1.14 [0.78, 1.68] [0.56, 2.40] 0.27 1.56550 2.13 1.60 [1.12, 2.37] [0.83, 3.44] 0.80 1.33600 2.51 2.18 [1.49, 3.30] [1.09, 4.95] 0.40 1.03

Table A.2: Expected and observed upper limits for the 0 jets and 1 jet DF bins combinedfor 2MR shape analysis at 2D shape selection and cut based results for the SF.

156


Figure A.6: Pre-Post fit normalisation ratio for 0-jet (top) and 1-jet processes (bottom)from B-only (left) and S+B (right) fit to all channels for 8 TeV data. Shape-based (2MR at2D shape level) for DF.

157


A.3 Results with m``-shape analysis

In this subsection the data to simulation comparison of the mll distributions at 2Dshape selection, for different-flavor events, and for the 0- and 1-jet bins is reported.This comparison is shown in Figure A.7. Bayesian limit calculation with the full m``

output distributions for the different flavour is used. Table A.3 and A.8 report thevalues of these limits. The Pre-Post fit normalisation ratio is shown in A.9.

Figure A.7: The input distributions for the mll-shape analysis in the different flavour channelfor 0 jets (left) and 1 jet (right) for mH = 125 GeV/c2 at 2D shape selection.

158

A.3 Results with m``-shape analysis

Figure A.8: Expected and observed upper limits for the m`` shape 0 jets DF and 1 jet DFbins combined at 2D shape selection and cut based results for the SF.

Figure A.9: Pre-Post fit normalisation ratio for 0-jet (top) and 1-jet processes (bottom)from B-only (left) and S+B (right) fit to all channels for 8 TeV data. Shape-based (mll at2D shape selection) for DF.

159



110 6.74 2.90 [2.07, 4.16] [1.55, 5.78] 2.95 0.76115 3.54 1.51 [1.08, 2.17] [0.81, 3.01] 2.99 1.43120 2.08 0.89 [0.64, 1.28] [0.48, 1.77] 2.87 2.35125 1.44 0.62 [0.44, 0.88] [0.33, 1.22] 2.97 3.34130 1.16 0.46 [0.33, 0.66] [0.25, 0.91] 3.00 4.35135 0.90 0.36 [0.26, 0.51] [0.19, 0.70] 3.08 5.43140 0.76 0.31 [0.22, 0.43] [0.17, 0.60] 3.09 6.21145 0.56 0.26 [0.19, 0.37] [0.14, 0.51] 2.81 7.11150 0.41 0.23 [0.16, 0.32] [0.13, 0.43] 2.37 7.92155 0.37 0.19 [0.14, 0.27] [0.11, 0.36] 2.60 8.95160 0.26 0.12 [0.09, 0.17] [0.07, 0.24] 2.86 12.72170 0.27 0.14 [0.10, 0.19] [0.08, 0.27] 2.49 11.08180 0.38 0.21 [0.15, 0.29] [0.11, 0.40] 2.11 8.51190 0.52 0.35 [0.25, 0.49] [0.19, 0.68] 1.30 5.27200 0.56 0.45 [0.32, 0.64] [0.24, 0.88] 0.72 4.16250 0.91 0.80 [0.57, 1.14] [0.43, 1.58] 0.45 2.51300 0.63 0.67 [0.48, 0.97] [0.36, 1.35] 0.00 2.97350 0.44 0.59 [0.42, 0.85] [0.31, 1.20] 0.00 3.48400 0.42 0.60 [0.43, 0.87] [0.32, 1.22] 0.00 3.32450 0.42 0.72 [0.51, 1.03] [0.38, 1.44] 0.00 2.64500 0.77 1.01 [0.72, 1.48] [0.54, 2.08] 0.00 1.95550 1.31 1.31 [0.91, 1.94] [0.68, 2.81] 0.00 1.64600 1.83 1.74 [1.20, 2.65] [0.88, 3.99] 0.09 1.26

Table A.3: Expected and observed upper limits for the m`` shape 0 jets DF and 1 jet DFbins combined at 2D shape selection and cut based results for the SF.

160

Appendix B

Two Dimensional Shape Analysis

The two-dimensional template fit is used to extract the Higgs boson signal from data.For the low mH analysis, variable bin widths are chosen to obtain a good resolutionon the signal shape and location while keeping the bins reasonably populated bythe background statistics. Examples 2D distributions are shown in Figure B.1 toillustrate the binning.

The performance of the 2D shape analysis in eµ channel in 0 and 1-jet bins combinedwith the cut-based ee/µµ channels is shown in Figure B.2 and Table B.1 for 8 TeVdata and Figure B.7 and Table B.2 for the 7 TeV data.

The distribution of the signal and the background subtracted data after the S+B fitin the 2D plain are shown in Figure B.3 and B.6. The fit results is reflected on thenormalisation and the shape of each signal and background inpute templates.

Figure B.5 shows the expected and observed 95% CL upper limits on the cross sectiontimes branching fraction, relative to the SM Higgs expectation, for the cut-basedapproach using the fulll 2011 and 2012 dataset.

161

B. TWO DIMENSIONAL SHAPE ANALYSIS

Table B.1: Expected and observed upper limits for all the 0 and 1 bins combined using5.1 of 8 TeV data. For eµ channel in 0/1-jet bins the 2D inputs are used, and for the restof the channels cut-based inputs are used.


110 6.28 2.24 [1.60, 3.22] [1.20, 4.50] 3.42 0.93115 3.19 1.14 [0.81, 1.62] [0.61, 2.26] 3.55 1.80120 1.81 0.66 [0.47, 0.94] [0.35, 1.30] 3.31 3.09125 1.27 0.44 [0.32, 0.63] [0.24, 0.87] 3.50 4.62130 0.91 0.32 [0.23, 0.45] [0.17, 0.62] 3.58 6.41135 0.75 0.25 [0.18, 0.35] [0.14, 0.49] 3.91 8.09140 0.61 0.21 [0.15, 0.29] [0.11, 0.40] 3.93 9.70145 0.51 0.17 [0.13, 0.25] [0.10, 0.34] 3.82 11.39150 0.40 0.15 [0.11, 0.21] [0.09, 0.30] 3.34 12.54155 0.33 0.13 [0.09, 0.18] [0.07, 0.24] 3.28 14.22160 0.22 0.09 [0.07, 0.13] [0.05, 0.18] 3.28 17.66170 0.23 0.10 [0.08, 0.15] [0.06, 0.20] 2.45 15.14180 0.26 0.15 [0.11, 0.21] [0.08, 0.29] 1.83 11.08190 0.36 0.24 [0.17, 0.33] [0.13, 0.46] 1.23 7.89200 0.37 0.31 [0.22, 0.44] [0.17, 0.62] 0.00 6.31250 0.81 0.57 [0.40, 0.82] [0.30, 1.15] 1.22 3.62300 0.72 0.61 [0.43, 0.88] [0.32, 1.23] 0.40 3.34350 0.47 0.52 [0.37, 0.76] [0.27, 1.07] 0.00 3.99400 0.39 0.52 [0.37, 0.75] [0.27, 1.05] 0.00 3.97450 0.40 0.62 [0.44, 0.89] [0.33, 1.24] 0.00 3.10500 0.74 0.85 [0.60, 1.24] [0.45, 1.75] 0.00 2.23550 1.45 1.08 [0.75, 1.60] [0.55, 2.34] 0.75 1.84600 1.73 1.46 [1.00, 2.25] [0.72, 3.40] 0.34 1.50

162

Table B.2: Expected and observed upper limits for all the 0 and 1 bins combined using of7 TeV data. For eµ channel in 0/1-jet bins the 2D inputs are used, and for the rest of thechannels cut-based inputs are used.


110 9.99 4.55 [3.22, 6.56] [2.39, 9.20] 2.72 0.48115 5.23 2.32 [1.65, 3.37] [1.22, 4.71] 2.72 0.90120 3.10 1.41 [1.00, 2.03] [0.75, 2.84] 2.56 1.47125 1.83 0.88 [0.62, 1.26] [0.47, 1.76] 2.28 2.35130 1.27 0.65 [0.46, 0.93] [0.34, 1.30] 2.01 3.16135 0.97 0.50 [0.36, 0.71] [0.27, 1.00] 1.99 4.05140 0.74 0.41 [0.29, 0.59] [0.22, 0.81] 1.94 4.84150 0.47 0.30 [0.21, 0.42] [0.16, 0.59] 1.49 6.55160 0.28 0.18 [0.13, 0.26] [0.10, 0.36] 1.34 9.99170 0.24 0.20 [0.14, 0.28] [0.11, 0.40] 0.60 9.13180 0.22 0.27 [0.19, 0.39] [0.15, 0.55] 0.00 6.77190 0.33 0.41 [0.29, 0.59] [0.22, 0.82] 0.00 4.65200 0.54 0.59 [0.42, 0.85] [0.31, 1.20] 0.00 3.31250 0.94 0.85 [0.60, 1.23] [0.45, 1.72] 0.37 2.31300 1.75 1.32 [0.93, 1.91] [0.70, 2.68] 0.76 1.50350 1.12 1.04 [0.73, 1.51] [0.54, 2.14] 0.18 1.94400 1.13 1.08 [0.76, 1.57] [0.57, 2.22] 0.12 1.82450 1.39 1.31 [0.92, 1.92] [0.68, 2.72] 0.15 0.00500 1.77 1.71 [1.18, 2.52] [0.87, 3.66] 0.10 0.00550 2.58 2.16 [1.46, 3.29] [1.05, 4.92] 0.43 0.00600 2.72 2.88 [1.91, 4.53] [1.36, 7.04] 0.00 0.00

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Figure B.5: Expected and observed 95% CL upper limits on the cross section times branch-ing fraction, relative to the SM Higgs expectation, for the 2D approach using the 7+8 TeVdata. The expected limits in the presence of the Higgs with mH = 125 GeV and its associateduncertainty are also shown.

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170

Appendix C

WW production cross sectionupdate

The WW production cross section has been calculated using the full luminosityrecorded by CMS during 2012 ( 19.5 fb−1).

C.1 Background estimates

The background estimation methods have already been described in Section 6.3. Thedetails of the predicted yields for top, W+jets and Z+jets backgrounds are listed inTablesC.1, C.2 and C.3 respectively.

Table C.1: Estimation of top backgrounds in the 0-jet bin

ValueNDatacontrol 7006NDatacontrol

tag 1940εData

top−tag (%) 33.0 ± 1.1εtWtop−tag (%) 15.2 ± 0.8f (%) 71.3 ± 9.5

Tagging efficiency 0-jet, ε0−jettop−tag (%) 48.8 ± 2.5

Top-tagged events in Data 821Background events in control region 213.4 ± 20.2Estimated top events in simulation 609.0 ± 11.7Data-driven top background estimate 638.3 ± 36.8Data/MC Ratio 1.0 ± 0.1

171

C. WW PRODUCTION CROSS SECTION UPDATE

Figure C.1: b-tagging discriminator for jets with 10 < pT < 30 GeV in the 1-tagged highpT jet defined to estimate the top tagging efficiency. Events in the denominator (left) and inthe nominator (right).

C.2 WW cross-section measurement with the full

2012 dataset

Table C.4 lists the data-driven background estimates and data yields for the selection.Background distributions have been reweighted to the expected values obtained with19.5 fb−1 of data. The higgs boson MC contribution at mH = 125 GeV/c2 has beenincluded as background.

Table C.2: Estimation of the W+jets background at the final selection level for differentlepton flavour final states.

µµ ee eµ µe Total27.7± 5.0 45.8 ± 1.8 120.5 ± 5.3 42.3 ± 3.1 236.3 ± 8.1

Table C.3: Estimation of the Drell-Yan background at the final selection level for sameflavour final state.

Final state Rout/inMC N control,data

`` N signal,dataDY N signal,MC

DY data/MCsame flavour 0.180 ± 0.008 1909 209.4 ± 14.8 65.0 ± 12.2 3.2

For the WW efficiency the efficiency for qq→WW and gg→WW processes is estimatedseparately, resulting in (3.058 ± 0.01 (stat.)) % and (6.181 ± 0.08 (stat.)) % values

172

C.2 WW cross-section measurement with the full 2012 dataset

Table C.4: Data yields and expected predictions in 19.5 fb−1. The prediction for the WWprocess assumes the SM cross section value.

Sample yield ± stat. ± syst.gg→WW 220.0 ± 2.8 ± 67.3qq→WW 3460.7 ± 15.0 ± 198.2tt+tW 638.3 ± 36.8 ± 64.3W+jets 236.3 ± 7.6 ± 85.1WZ+ZZ 144.9 ± 1.2 ± 10.3

Z/γ∗ 222.4 ± 14.8 ± 66.5Wγ + Wγ∗ 107.0 ± 12.0 ± 33.7

Zgamma 3.9 ± 1.2 ± 0.2HWW125 135.9 ± 2.1 ± 7.8


Data 5581

respectively. Taking into account their corresponding theoretical cross-section expec-tation, the gg process is ∼ 3% of the total value, so once the efficiencies are weightedcorrecty the total efficiency for the WW process is (3.15± 0.01 (stat.+ syst.)%. Fi-nally, considering an integrated luminosity of 19.5 fb−1 collected by CMS during2012, the cross-section estimation is

σWW = 63.53± 1.16 (stat.)± 2.08 (syst.)± 2.80 (lumi.) pb

to be compared with the latest theoretical prediction quoted in Section 8.1.2.

173

C. WW PRODUCTION CROSS SECTION UPDATE

Figure C.2: Distributions of the leading lepton transverse momentum (pTmax), the trailinglepton transverse momentum (pTmin), and the dilepton transverse momentum (pT ll ) andinvariant mass (Mll) at the final selection level, reweighted to the data-driven estimates. Allfour channels (ee, mm, em and me) are combined, and the uncertainty band corresponds tothe statistical and systematic uncertainties on the predicted yield.

174

Appendix D

HWW : additional material

D.1 Shape based analysis

D.1.1 7 TeV analysis

The observed and expected limits are detailed in Tables D.1 and D.2 for the mll shapeanalysis with the 7 TeV dataset for Different Flavour events.

mH [GeV/c2] observed observed median expected expected range expected range(CLs) (Bayesian) (CLs) for 68% for 95%

110 8.1 8.6 7.6 [ 5.2 , 11.2 ] [ 3.7 , 16.8 ]115 4.9 5.4 3.5 [ 2.5 , 5.3 ] [ 2.0 , 7.8 ]120 2.2 2.4 2.2 [ 1.5 , 3.3 ] [ 1.3 , 4.9 ]130 1.0 1.1 1.0 [ 0.7 , 1.5 ] [ 0.6 , 2.1 ]140 0.6 0.7 0.7 [ 0.4 , 1.0 ] [ 0.3 , 1.6 ]150 0.8 0.8 0.5 [ 0.4 , 0.7 ] [ 0.3 , 1.1 ]160 0.5 0.5 0.3 [ 0.2 , 0.4 ] [ 0.2 , 0.7 ]170 0.5 0.5 0.3 [ 0.2 , 0.5 ] [ 0.2 , 0.8 ]180 0.5 0.6 0.5 [ 0.4 , 0.8 ] [ 0.3 , 1.2 ]190 0.6 0.6 0.7 [ 0.5 , 1.1 ] [ 0.3 , 1.7 ]200 1.4 1.5 1.0 [ 0.8 , 1.7 ] [ 0.5 , 2.7 ]250 1.9 2.1 2.1 [ 1.5 , 3.1 ] [ 1.1 , 5.0 ]300 2.1 2.4 2.5 [ 1.7 , 4.0 ] [ 1.1 , 6.7 ]350 2.3 2.6 2.1 [ 1.4 , 3.4 ] [ 1.2 , 5.4 ]400 2.6 2.8 2.3 [ 1.5 , 3.5 ] [ 1.1 , 6.0 ]450 2.2 2.7 2.8 [ 1.8 , 4.3 ] [ 1.3 , 6.8 ]500 2.5 3.1 4.0 [ 2.6 , 6.5 ] [ 1.5 , 10.1 ]550 3.8 4.6 5.4 [ 3.8 , 8.8 ] [ 2.6 , 14.1 ]600 6.3 8.5 8.5 [ 5.4 , 13.7 ] [ 3.8 , 21.6 ]

Table D.1: Expected and observed mll shape upper limits and uncertainty band for oppositeflavour events in the 0 jet bin.

175

D. HWW : ADDITIONAL MATERIAL

mH [GeV/c2] observed observed median expected expected range expected range(CLs) (Bayesian) (CLs) for 68% for 95%

110 31.0 34.7 14.0 [ 10.9 , 23.5 ] [ 8.5 , 37.9 ]115 17.6 20.2 6.5 [ 4.8 , 10.6 ] [ 4.1 , 17.1 ]120 8.1 8.8 3.6 [ 2.7 , 5.5 ] [ 2.2 , 8.7 ]130 3.9 4.1 1.8 [ 1.4 , 2.9 ] [ 1.1 , 4.3 ]140 2.2 2.4 1.3 [ 0.9 , 2.0 ] [ 0.6 , 3.1 ]150 0.9 1.0 0.9 [ 0.6 , 1.3 ] [ 0.4 , 2.1 ]160 0.4 0.5 0.5 [ 0.3 , 0.8 ] [ 0.3 , 1.2 ]170 0.4 0.4 0.5 [ 0.4 , 0.9 ] [ 0.3 , 1.3 ]180 0.4 0.5 0.7 [ 0.5 , 1.2 ] [ 0.3 , 1.9 ]190 0.5 0.6 1.0 [ 0.7 , 1.8 ] [ 0.4 , 2.7 ]200 1.1 1.0 1.6 [ 1.1 , 2.4 ] [ 0.7 , 3.6 ]250 2.7 3.0 2.7 [ 1.9 , 4.3 ] [ 1.4 , 6.8 ]300 2.6 2.8 3.1 [ 2.2 , 5.1 ] [ 1.5 , 7.9 ]350 2.2 2.3 2.9 [ 1.8 , 4.8 ] [ 1.5 , 7.3 ]400 2.4 2.2 3.3 [ 2.2 , 5.1 ] [ 1.6 , 8.6 ]450 2.4 2.5 4.0 [ 2.5 , 6.7 ] [ 1.8 , 10.6 ]500 4.7 5.3 5.1 [ 3.4 , 8.9 ] [ 2.1 , 14.9 ]550 5.8 6.8 6.8 [ 4.7 , 11.5 ] [ 3.5 , 20.0 ]600 8.4 10.2 9.5 [ 6.4 , 16.4 ] [ 4.5 , 26.8 ]

Table D.2: Expected and observed mll shape upper limits and uncertainty band for oppositeflavour events in the 1 jet bin.


The Pre-Post fit normalisation ratio for 0 and 1 jet bins for the mll shape analysisusing the 8 TeV dataset can be seen in Figure D.1.

176

D.1 Shape based analysis

Figure D.1: Pre-Post fit normalisation ratio for 0-jet (top) and 1-jet processes (bottom)from B-only (left) and S+B (right) fit to all channels for 8 TeV data. Shape-based (mll atN-1 selection) for DF (8TeV).

177


D.2 Cut based analysis


The expected and observed limits and significance for the cut based analysis at 7TeV can be seen in Table D.3 and Figure D.2. Table D.4 shows the backgroundcontributions and yields for 4.9 fb−1 of integrated luminosity of 7 TeV data after thefull cut-based selection for 0 jets and 1 jet bins.

Figure D.2: Expected cut-based upper limits for all the lepton flavour channels in 0 and1 jet bins combined using 4.9 fb−1 of 7 TeV data

.

178



110 8.48 6.19 [4.35, 8.93] [3.23, 12.60] 0.82 0.36115 4.01 2.98 [2.10, 4.32] [1.55, 6.07] 0.71 0.73120 2.47 1.84 [1.30, 2.64] [0.98, 3.69] 0.76 1.15125 1.69 1.16 [0.83, 1.65] [0.62, 2.31] 0.99 1.80130 1.33 0.86 [0.61, 1.23] [0.46, 1.70] 1.03 2.41135 1.05 0.66 [0.47, 0.94] [0.35, 1.30] 1.11 3.07140 0.70 0.53 [0.38, 0.76] [0.29, 1.05] 0.59 3.63150 0.53 0.39 [0.28, 0.56] [0.21, 0.78] 0.94 4.76160 0.28 0.21 [0.15, 0.31] [0.12, 0.43] 0.00 7.81170 0.24 0.23 [0.16, 0.33] [0.12, 0.46] 0.00 7.39180 0.27 0.32 [0.23, 0.46] [0.17, 0.64] 0.00 5.39190 0.32 0.48 [0.34, 0.69] [0.26, 0.96] 0.00 3.61200 0.55 0.70 [0.49, 1.00] [0.37, 1.40] 0.00 2.66250 0.70 1.05 [0.74, 1.52] [0.55, 2.13] 0.00 1.79300 1.31 1.70 [1.20, 2.45] [0.89, 3.41] 0.00 1.15350 1.29 1.44 [1.01, 2.09] [0.75, 2.96] 0.00 1.37400 1.30 1.48 [1.04, 2.14] [0.78, 3.00] 0.00 1.31450 1.39 1.68 [1.18, 2.42] [0.88, 3.42] 0.00 1.18500 1.70 2.09 [1.47, 3.06] [1.09, 4.38] 0.00 0.98550 2.46 2.70 [1.86, 4.02] [1.37, 5.93] 0.00 0.81600 3.31 3.48 [2.35, 5.37] [1.71, 8.27] 0.00 0.68

Table D.3: Expected and observed cut-based upper limits and significance for all the leptonflavour channels (0 and 1 jet bins combined) using 4.9 fb−1 of 7 TeV data.

179


cut-based 0-jet (7 TeV)

Z/γ∗ tt+tW W+jets VV Vγ(∗) WW all bkg. mH = 120 GeV/c2 dataee/µµ 2.2± 4.5 1.4± 0.5 3.7± 1.3 1.3± 0.1 1.2± 0.4 37.3± 3.7 47.2± 6.0 4.9± 1.0 49eµ 0.1± 0.1 3.8± 1.3 11.1± 4.0 1.0± 0.1 4.3± 0.9 63.7± 5.8 84.1± 7.3 11.6± 2.5 87

total 2.3± 4.5 5.2± 1.4 14.9± 4.2 2.3± 0.1 5.5± 1.0 101.0± 6.9 131.2± 9.4 16.5± 2.7 136


total 3.3± 4.2 6.8± 1.8 16.1± 4.6 2.7± 0.2 6.3± 1.2 126.7± 8.6 161.9± 10.8 31.3± 4.8 172


total 3.6± 3.9 8.4± 2.2 17.8± 5.0 3.0± 0.2 6.3± 1.2 143.8± 9.7 182.8± 11.8 47.8± 7.4 193


total 2.7± 1.9 8.4± 2.0 3.0± 1.0 1.5± 0.1 1.1± 0.3 85.2± 5.7 101.9± 6.4 130.5± 21.5 111


total 1.0± 1.1 18.4± 4.5 3.3± 0.9 3.2± 0.2 1.1± 0.3 132.8± 8.8 159.9± 10.0 51.7± 10.2 159


total 2.1± 4.2 30.4± 7.4 5.5± 1.4 3.9± 0.3 1.8± 0.7 73.4± 4.9 117.1± 10.0 19.4± 3.9 109


total 0.7± 1.2 9.4± 2.4 2.0± 0.5 1.3± 0.1 0.3± 0.1 19.4± 1.5 33.0± 3.1 3.5± 0.4 33



total 5.7± 1.9 16.3± 2.6 5.4± 1.9 1.9± 0.1 1.8± 0.5 27.5± 3.3 58.6± 5.0 6.7± 1.8 72


total 4.8± 2.5 20.9± 3.3 5.6± 1.9 2.3± 0.1 2.1± 0.5 34.4± 4.1 70.0± 6.2 12.4± 3.0 90


total 4.5± 2.5 24.2± 3.9 6.5± 2.0 2.6± 0.2 2.3± 0.6 39.3± 4.6 79.4± 6.9 18.1± 4.3 105


total 6.0± 2.1 27.0± 4.1 3.1± 0.9 1.6± 0.1 0.8± 0.3 34.7± 3.9 73.2± 6.1 62.7± 16.2 86


total 13.7± 4.2 56.7± 8.6 5.3± 1.3 2.3± 0.1 0.5± 0.2 61.3± 6.9 139.8± 11.8 26.9± 6.7 111


total 5.5± 2.0 58.4± 8.9 6.3± 1.8 2.6± 0.2 1.2± 0.4 55.4± 6.5 129.4± 11.4 13.8± 4.0 128


total 0.3± 0.6 15.0± 2.4 3.5± 1.0 0.9± 0.1 0.5± 0.3 18.9± 2.3 39.2± 3.5 3.4± 0.8 37

Table D.4: Background contributions and yields for 4.9 fb−1 of integrated luminosity of 7 TeVdata after the full cut-based selection. The data-driven corrections are applied and the errorsreported reflect main systematic uncertanties.

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The expected and observed limits and significance for the cut based analysis at 8 TeVcan be seen in Table D.5 and Figure D.3.Table D.6 shows the background contribu-tions and yields for 19.5 fb−1 of integrated luminosity of 8 TeV data after the fullcut-based selection for 0 jets and 1 jet bins.

Figure D.3: Expected cut-based upper limits for all the lepton flavour channels in 0 and1 jet bins combined using 19.5 fb−1 of 8 TeV data.

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110 7.56 3.89 [2.71, 5.64] [2.04, 7.84] 2.09 0.57115 3.67 1.91 [1.34, 2.75] [1.01, 3.81] 2.13 1.14120 1.91 1.14 [0.81, 1.62] [0.60, 2.23] 1.71 1.86125 1.40 0.82 [0.58, 1.15] [0.43, 1.57] 1.79 2.56130 1.10 0.61 [0.43, 0.86] [0.32, 1.18] 1.94 3.37135 0.87 0.46 [0.33, 0.65] [0.25, 0.89] 2.12 4.30140 0.68 0.38 [0.27, 0.53] [0.20, 0.72] 2.03 5.12145 0.57 0.32 [0.23, 0.44] [0.17, 0.61] 2.03 5.90150 0.48 0.25 [0.18, 0.35] [0.14, 0.48] 2.51 7.01155 0.37 0.20 [0.15, 0.28] [0.11, 0.38] 2.34 8.18160 0.24 0.13 [0.09, 0.18] [0.07, 0.24] 2.23 10.31170 0.21 0.13 [0.10, 0.19] [0.08, 0.26] 1.61 9.57180 0.35 0.20 [0.14, 0.28] [0.11, 0.38] 0.00 7.72190 0.57 0.34 [0.25, 0.48] [0.19, 0.66] 1.64 5.27200 0.80 0.47 [0.34, 0.67] [0.25, 0.92] 1.70 4.08250 1.28 0.90 [0.64, 1.29] [0.48, 1.77] 1.19 2.27300 1.09 0.93 [0.66, 1.32] [0.49, 1.83] 0.18 2.15350 0.80 0.76 [0.54, 1.08] [0.40, 1.52] 0.08 2.58400 0.76 0.74 [0.53, 1.06] [0.40, 1.48] 0.09 2.57450 0.66 0.81 [0.58, 1.15] [0.43, 1.60] 0.00 2.28500 0.82 1.07 [0.76, 1.54] [0.57, 2.17] 0.00 1.76550 1.32 1.39 [0.98, 2.04] [0.73, 2.95] 0.00 1.46600 1.70 1.84 [1.27, 2.78] [0.93, 4.13] 0.00 1.16

Table D.5: Expected and observed cut-based upper limits and significance for all the leptonflavour channels (0 and 1 jet bins combined) using 19.5 fb−1 of 8 TeV data.

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total 88.5± 22.4 25.2± 3.0 65.5± 17.5 16.4± 1.0 45.4± 9.4 409.8± 25.1 650.8± 39.2 90.7± 14.0 754


total 107.1± 17.0 31.8± 3.8 80.9± 21.7 20.4± 1.3 49.9± 10.0 520.7± 31.7 810.8± 43.3 151.6± 23.0 928


total 115.5± 16.5 37.4± 4.4 84.4± 22.5 22.5± 1.4 54.0± 10.7 590.7± 35.8 904.5± 46.9 231.6± 35.3 1025


total 15.3± 7.2 38.2± 5.5 12.6± 3.2 12.6± 0.8 8.6± 2.9 371.0± 22.6 458.4± 24.7 716.9± 117.8 544


total 21.2± 4.1 102.5± 12.2 15.6± 4.0 23.5± 1.5 7.9± 2.0 596.8± 36.1 767.4± 38.6 276.1± 54.2 864


total 1.8± 3.2 130.1± 15.5 24.7± 6.3 22.8± 1.6 6.5± 2.0 402.7± 24.3 588.6± 29.8 120.9± 24.5 593


total 2.1± 3.8 39.1± 6.7 9.9± 2.5 7.3± 0.6 4.4± 1.5 130.2± 8.2 193.0± 11.6 19.6± 2.0 191



total 14.7± 1.8 103.9± 5.0 33.2± 10.0 11.3± 0.8 13.4± 3.0 93.0± 10.6 269.4± 15.8 36.6± 8.9 293


total 16.5± 2.2 131.3± 6.2 38.4± 11.7 13.5± 0.9 13.6± 3.0 117.3± 13.2 330.5± 19.1 64.9± 15.7 370


total 16.3± 2.5 149.0± 7.0 41.6± 12.3 14.9± 1.0 13.7± 3.0 131.9± 14.8 367.3± 20.9 93.0± 20.7 429


total 8.3± 2.1 150.6± 7.5 16.3± 4.4 10.2± 0.7 1.6± 0.5 116.9± 12.7 304.0± 15.5 338.2± 85.7 358


total 19.8± 2.8 339.4± 15.6 25.8± 7.0 14.9± 0.9 3.0± 1.5 214.5± 23.0 617.4± 28.9 149.7± 36.9 683


total 7.1± 1.6 323.9± 15.4 31.2± 8.9 15.6± 1.0 2.1± 1.1 206.6± 23.0 586.4± 29.2 81.8± 23.4 582


total 1.6± 0.9 86.5± 5.7 13.7± 4.2 5.1± 0.4 0.0± 0.0 76.3± 8.7 183.4± 11.2 17.6± 3.9 176

Table D.6: Background contributions and yields for 19.5 fb−1 of integrated luminosity of 8 TeVdata after the full cut-based selection. The data-driven corrections are applied and the errorsreported reflect main systematic uncertanties.

183


184

Agradecimientos

El primer agradecimiento de esta tesis es facil. Quiero agradecerle a Javier todo loque ha hecho por mi durante todos estos anos que he trabajado con el. Todas lascosas buenas que podrıa decir de el como director de mi tesis son secundarias. Lamas relevante de todas es que es una de las mejores personas que me he encontradoa lo largo de mi vida. Siempre ha tenido una palabra buena y raro es el dıa que nonos hayamos echado unas risas en el despacho con el. No he oido de ningun directorde tesis de quien sus estudiantes solo puedan decir cosas positivas y puede estar muyorgulloso de ello. De verdad y de corazon, muchas gracias. Tendre otros jefes buenos(espero...) pero no tendre otro jefe igual.

Esto de agradecer es algo muy complicado. Para empezar, es lo primero (y muchasveces lo unico) que suele leer la gente cuando les ensenas la tesis, esperando encontrarsu nombre y una frase simpatica asociada. Eso mete mucha presion porque es evidenteque siempre se quedara alguien importante fuera o que la frase no estara a la altura.

Por eso voy a ser lo mas general posible, porque tengo tanta gente a la que tengotantısimo que agradecer, que dejar a alguno en el tintero serıa un autentico pecado.A lo largo de estos anos de doctorado he conocido a mucha gente excelente, tanto enIFCA/Uniovi como en el CERN. Me llevo un buen punado de amigos y un montonde recuerdos estupendos. Empece el doctorado sin mucho convencimiento y ahora,mirando hacia atras, veo que ha merecido la pena. Ha habido un poco de todo, laverdad...pero el balance de estos anos ha sido muy bueno. Gracias a todos los queme han echado un cable, ya sea activamente o tomandose un cafe (frıo) conmigo yhablando de trivialidades. Hay gente a quien me gustarıa destacar especialmente,pero finalmente he decidido no hacerlo aqui, sino de palabra cuando les regale unacopia de la tesis para que coja polvo en la estanterıa o les invite a un cafe para celebraresta etapa que se acaba.

Por ultimo quiero agradecer a mi familia el no haberme dado nada mas que carinoy apoyo durante toda mi vida. Papi y mami: sois referencia, faro y refugio de todosnosotros. Cada nueva etapa completada es gracias a vosotros. Os quiero mucho.

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