Search for heavy resonances decaying into a ZZ boson and a vector boson in the ννˉ\nu \bar{\nu} qqˉq\bar{q} final state at CMS

This thesis presents a search for potential signals of new heavy resonances decaying into a pair of vector bosons, with masses between 1 TeV and 4 TeV, predicted by beyond standard model theories. The signals probed are spin-1 W', predicted by the Heavy Vector Triplet model, and spin-2 bulk gravitons, predicted by warped extra-dimension models. The scrutinized data are produced by LHC proton-proton collisions at a center-of-mass energy $\sqrt{s}=13$ TeV during the 2016 operations, and collected by the CMS experiment, corresponding to an integrated luminosity of 35.9 fbinv. One of the boson should be a Z, and it is identified through its invisible decay into neutrinos, while the other electroweak boson, consisting either into a W or into a Z boson, is required to decay hadronically into a pair of quarks. The decay products of heavy resonances are produced with large Lorentz boosts; as a consequence, the decay products of the bosons (quarks and neutrinos) are expected to be highly energetic and collimated. The couple of neutrinos, escaping undetected, is reconstructed as missing momentum in the transverse plane of the CMS detector. The couple of quarks is reconstructed as one large-cone jet, with high transverse momentum, recoiling against the couple of neutrinos. Grooming algorithms are adopted in order to improve the jet mass resolution, by removing soft radiation components and spectator events from the particles clustered as the large-cone jet. The groomed jet mass is used to tag the hadronically decaying vector boson, to define the signal region of the search (close to the nominal mass of the W and Z bosons, between 65-105 GeV) and a signal-depleted control region, that is used for the background estimation. An hybrid data-simulation approach predicts the normalization and the shape of the main background, represented by a vector boson produced in association with jets, by taking advantage of the distribution of data in the signal-depleted control regions. Secondary backgrounds are predicted from simulations. Jet substructure techniques are exploited, in order to classify events into two exclusive purity categories, by distinguishing the couple of quarks inside the large-cone jet. This approach improves the background rejection and the discovery reach. The search is performed by scanning the distribution of the reconstructed mass of the resonance, looking for a local excess in data with regards to the prediction. Depending on the mass, upper limits on the cross-section of heavy spin-1 and spin-2 narrow resonances, multiplied by the branching fraction of the resonance decaying into Z and a W boson for a spin-1 signal, and into a pair of Z bosons for spin-2, are set in the range $0.9$ -- $63$ fb and in the range $0.5$ -- $40$ fb respectively. A W' hypothesis is excluded up to 3.11 TeV, in the Heavy Vector Triplet benchmark A scenario, and up to 3.41 TeV, considering the benchmark B scenario. A bulk graviton hypothesis, given the curvature parameter of the extra-dimension $\tilde{k}=1.0$, is excluded up to 1.14 TeV

Ricerca di nuova fisica a CMS in eventi con leptoni nello stato finale

Questa tesi presenta l'analisi mirata alla scoperta di un eventuale bosone Z' di massa elevata (M>2TeV) nei processi di interazione protone-protone, con il fine di ottimizzare la ricerca nei dati che verranno raccolti da CMS a partire dal 2015, quando il funzionamento di LHC porterà l'energia del centro di massa a 13 TeV. Nella tesi si sono rianalizzati i dati ad 8 TeV per riprodurre i risultati pubblicati. La ricerca, effettuata nel canale Z'→μ+μ-, non mostra nessun eccesso di eventi rispetto ai fondi attesi.ope

Shared Data and Algorithms for Deep Learning in Fundamental Physics

We introduce a collection of datasets from fundamental physics research -- including particle physics, astroparticle physics, and hadron- and nuclear physics -- for supervised machine learning studies. These datasets, containing hadronic top quarks, cosmic-ray induced air showers, phase transitions in hadronic matter, and generator-level histories, are made public to simplify future work on cross-disciplinary machine learning and transfer learning in fundamental physics. Based on these data, we present a simple yet flexible graph-based neural network architecture that can easily be applied to a wide range of supervised learning tasks in these domains. We show that our approach reaches performance close to state-of-the-art dedicated methods on all datasets. To simplify adaptation for various problems, we provide easy-to-follow instructions on how graph-based representations of data structures, relevant for fundamental physics, can be constructed and provide code implementations for several of them. Implementations are also provided for our proposed method and all reference algorithms.Comment: 13 pages, 5 figures, 5 table

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

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.

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

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

Measurement of the Splitting Function in &ITpp &ITand Pb-Pb Collisions at root&ITsNN&IT=5.02 TeV

Data from heavy ion collisions suggest that the evolution of a parton shower is modified by interactions with the color charges in the dense partonic medium created in these collisions, but it is not known where in the shower evolution the modifications occur. The momentum ratio of the two leading partons, resolved as subjets, provides information about the parton shower evolution. This substructure observable, known as the splitting function, reflects the process of a parton splitting into two other partons and has been measured for jets with transverse momentum between 140 and 500 GeV, in pp and PbPb collisions at a center-of-mass energy of 5.02 TeV per nucleon pair. In central PbPb collisions, the splitting function indicates a more unbalanced momentum ratio, compared to peripheral PbPb and pp collisions.. The measurements are compared to various predictions from event generators and analytical calculations.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