The search for the charged Higgs boson and a tau veto in the event selection

After the finding of a Higgs boson at the Large Hadron Collider of CERN, the next milestone in experimental particle physics is the detection of a new particle beyond the Standard Model. Many of the popular extensions of the Standard Model are so called Two-Higgs-doublet models, that include five physical Higgs bosons in total. Two of the bosons are neutral scalars, two are charged scalars and one is a pseudoscalar. The first part of this thesis presents the Standard Model of particle physics as a gauge field theory where the gauge principle is used to introduce interactions between the particles. Quantum electrodynamics, weak interactions and quantum chromodynamics with their properties are discussed. The electroweak symmetry breaking through the Higgs mechanism and its implications for the masses of the particles are shown. The considerations on the Standard Model are concluded by discussing some of the problems in the Standard Model. Supersymmetric extensions to the Standard Model are introduced, motivated by their potential to solve some of the problems and by the framework for new physics the supersymmetry provides. The Higgs sector in the more constrained minimal supersymmetry scenario is discussed and some of the properties for these new Higgs bosons are given. The latter part of the thesis focuses on the experimental aspects of high energy particle physics. The search for the charged Higgs boson in the H+ → τ+ ντ decay channel, with the tau lepton decaying into hadronic decay products is presented in detail. Vetoing collision events with more than one tau particle is shown to enhance the transverse mass resolution of the analysis, improving the signal detection. Methods for performing a tau veto are discussed and the problems in performing the tau veto are studied using 13 TeV collision event simulations and data from 2015 from the CMS detector at the LHC. No viable way of performing the tau veto in such a way that it improves the overall analysis is found

Deep Neural Network Classifiers in CMS Track Reconstruction and in the Search for the Charged Higgs Boson

The LHC particle accelerator at CERN is probing the elementary building blocks of matter at energies never seen in laboratory conditions before. In the process of providing new insights in to the Standard Model describing the current understanding of physics governing the behaviour of particles, the accelerator is challenging the algorithms and techniques used in storing the collected data, rebuilding the collected collision events from the detector signal and analysing the data. For this end many state of the art methods are being developed by the scientist working in the LHC experiments in order to gain as much knowledge from the unique data collected from these particle collisions. The decade starting from 2010 can be in many respects considered as the deep learning revolution where a family of machine learning algorithms collectively called deep neural networks had significant breakthroughs driven by advances in hardware used to train these algorithms. During this period many achievements previously only seen in the realm of science fiction became reality as the deep neural networks began driving cars, images and videos could be enhanced with super resolution in real time and improvements in automated translation tools lowered the barriers in communication between people. These results have given the field of deep learning a significant momentum and lead to the methods spreading across academic disciplines as well as different industries. In this thesis the recent advances of deep learning are applied into the realm of particle physics using the data collected by the CMS experiment at the LHC at CERN. First topic presented considers the task of rebuilding the flight paths of charged particles called tracks inside the detector using the measurements made by the Tracker sub-detector in the heart of the CMS. The conditions present inside the detector during particle collisions demand for advanced algorithms able to be both fast and precise. The project in this thesis looks at estimating the quality of the reconstructed tracks and reject tracks that look like they are a result of mistakes made by the reconstruction algorithms, purifying the reconstructed dataset from false signals. Previously the task has been done initially by cut based selections determined by physicists and later by another machine learning algorithm known as the boosted decision tree. Here the first application of deep neural networks to the task is presented with the goal of both simplifying the upkeep of the classifier as well as improving the performance. In the second topic the application of deep neural network classifiers in the context of a search for a new particle, the charged Higgs boson, is presented. Here the main focus is in producing a classifier that has been decorrelated from a variable of interest that will be used in making the final discovery or exclusion of the hypothetical particle. The classifier can then be used just like any other selection step in the analysis aiming to separate known Standard Model background events from the expected signal without distorting the distribution for the variable of interest. Both research topics present first time use cases at the CMS for deep neural networks in their respective contexts and the work done includes the full stack of solving a machine learning problem, starting from data collection strategy to cleaning the data and working out the meaningful input variables for the problem all the way to training, optimizing and deploying the model to get the final results for their performance.Sveitsin ja Ranskan rajalle rakennettu Large Hadron Collider hiukkaskiihdytin törmäyttää atomien ytimistä löytyviä protoneita toisiinsa ennennäkemättömän suurilla energioilla. Nämä törmäyksissä syntyy uusia lyhytikäisiä hiukkasia, joita ei havaita tavanomaisissa olosuhteissa maapallolla. Havainnoimalla erilaisten hiukkasten tuottomääriä törmäyksissä, pystytään tekemään tarkkoja mittauksia fysiikan perusvuorovaikutuksista ja sitä kautta tutkimaan vastaako luonto kaikkein pienimmillä kokoluokilla ymmärrystämme. Hiukkastörmäykset tarjoavat ikkunan maailmankaikkeuden perusrakenneosasiin, alkeishiukkasiin, sekä niiden välisiin vuorovaikutuksiin, joiden teoreettinen kuvaus on kiteytetty hiukkasfysiikan standardimalliin. Hiukkastörmäysten tutkimus vaatii kehittyneiden mittalaitteiden lisäksi hienostuneita analyysimenetelmiä. Pohjimmiltaan hiukkaset ja niiden vuorovaikutukset tottelevat kvanttimekaniikan lainalaisuuksia, minkä takia tutkimus vaatii tilastollisten menetelmien soveltamista: suuresta määrästä dataa voidaan saada luotettavia tuloksia, kun taas yksittäisestä törmäyksestä ei voida vielä varmuudella sanoa mitä on tarkalleen tapahtunut. Perinteisten analyysimenetelmien lisäksi niin kutsutut koneoppimismenetelmät, joissa kerättyä dataa käytetään kouluttamaan algoritmi tekemään päätöksiä, ovat osoittautuneet hyödyllisiksi monenlaisissa käyttötarkoituksissa hiukkastörmäyksiä tutkiessa. Nämä samat koneoppimisalgoritmit ovat tulleet useille tutuiksi mediassa teköälyn nimikkeellä ja niitä voidaan käyttää monenlaisiin käyttökohteisiin kuten itseäänajavien autojen ohjaamiseen tai katsojaa mahdollisesti kiinnostavien elokuvien suositteluun videopalvelussa. Tässä väitöskirjassa tutkitaan kahta uutta käyttökohdetta syviä neuroverkkoja hyödyntäville koneoppimismenetelmille, joista ensimmäinen auttaa määrittämään törmäyksessä syntyneiden hiukkasten lentoratoja ja jälkimmäinen etsii törmäysdatasta merkkejä uudesta toistaiseksi havaitsemattomasta hiukkasesta. Molemmat tutkimukset liittyvät Compact Muon Solenoid mittalaitteen tuottamien havaintojen analysointiin ja kattavat koneoppimisongelman ratkaisemisen koko kaaren datan keräämisestä ja alustavasta siivoamisesta mielekkäiden muuttujien etsimiseen sekä lopulta algoritmin kouluttamiseen ja tuotantoon viemiseen

Search for supersymmetry using Higgs boson to diphoton decays at s√ = 13 TeV

A search for supersymmetry (SUSY) is presented where at least one Higgs boson is produced and decays to two photons in the decay chains of pair-produced SUSY particles. Two analysis strategies are pursued: one focused on strong SUSY production and the other focused on electroweak SUSY production. The presence of charged leptons, additional Higgs boson candidates, and various kinematic variables are used to categorize events into search regions that are sensitive to different SUSY scenarios. The results are based on data from proton-proton collisions at the Large Hadron Collider at a center-of-mass energy of 13 TeV collected by the CMS experiment, corresponding to an integrated luminosity of 77.5 fb−1. No statistically significant excess of events is observed relative to the standard model expectations. We exclude bottom squark pair production for bottom squark masses below 530 GeV and a lightest neutralino mass of 1 GeV; wino-like chargino-neutralino production in gauge-mediated SUSY breaking (GMSB) for chargino and neutralino masses below 235 GeV with a gravitino mass of 1 GeV; and higgsino-like chargino-neutralino production in GMSB, where the neutralino decays exclusively to a Higgs boson and a gravitino for neutralino masses below 290 GeV.Peer reviewe

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| < 0.03 at 95% confidence level. [Figure not available: see fulltext.

An embedding technique to determine ττ backgrounds in proton-proton collision data

An embedding technique is presented to estimate standard model tau tau backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed mu mu events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique described in this paper was developed for CMS. Its validation and the inherent uncertainties are also discussed. The demonstration of the performance of the technique is based on a sample of proton-proton collisions collected by CMS in 2017 at root s = 13 TeV corresponding to an integrated luminosity of 41.5 fb(-1).Peer reviewe

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe

Measurement of prompt open-charm production cross sections in proton-proton collisions at root s=13 TeV

The production cross sections for prompt open-charm mesons in proton-proton collisions at a center-of-mass energy of 13TeV are reported. The measurement is performed using a data sample collected by the CMS experiment corresponding to an integrated luminosity of 29 nb(-1). The differential production cross sections of the D*(+/-), D-+/-, and D-0 ((D) over bar (0)) mesons are presented in ranges of transverse momentum and pseudorapidity 4 < p(T) < 100 GeV and vertical bar eta vertical bar < 2.1, respectively. The results are compared to several theoretical calculations and to previous measurements.Peer reviewe

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV