Georges Aad

Bio: Georges Aad is an academic researcher from Aix-Marseille University. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 135, co-authored 1121 publications receiving 88811 citations. Previous affiliations of Georges Aad include Centre national de la recherche scientifique & University of Udine.

Measurement of the $t\bar{t}$ production cross-section using $e\mu$ events with $b$-tagged jets in $pp$ collisions at $\sqrt{s}=7$ and 8 TeV with the ATLAS detector

Abstract: The inclusive top quark pair production cross-section has been measured in proton-proton collisions at sqrt(s)=7 TeV and sqrt(s)=8 TeV with the ATLAS experiment at the LHC, using ttbar events with an opposite-charge e-mu pair in the final state. The measurement was performed with the 2011 7 TeV dataset corresponding to an integrated luminosity of 4.6 fb-1 and the 2012 8 TeV dataset of 20.3 fb-1. The numbers of events with exactly one and exactly two b-tagged jets were counted and used to simultaneously determine sigma(ttbar) and the efficiency to reconstruct and b-tag a b-jet from a top quark decay, thereby minimising the associated systematic uncertainties. The cross-section was measured to be: sigma(ttbar)=$182.9\pm3.1\pm4.2\pm3.6\pm3.3$ pb (7 TeV) and sigma(ttbar)=$242.4\pm1.7\pm5.5\pm7.5\pm4.2$ pb (8 TeV), where the four uncertainties arise from data statistics, experimental and theoretical systematic effects, the knowledge of the integrated luminosity and of the LHC beam energy. The results are consistent with recent theoretical QCD calculations at NNLO. Fiducial measurements corresponding to the experimental acceptance of the leptons are also reported, together with the ratio of cross-sections measured at the two centre-of-mass energies. The inclusive cross-section results were used to determine the top quark pole mass via the dependence of the theoretically-predicted cross-section on $m_t^{pole}$, giving a result of $m_t^{pole}=172.9^{+2.5}_{-2.6}$ GeV. By looking for an excess of ttbar production with respect to the QCD prediction, the results were also used to place limits on the pair-production of supersymmetric top squarks with masses close to the top quark mass decaying to predominantly right-handed top quarks and a light neutralino, the lightest supersymmetric particle. Top squarks with masses between the top quark mass and 177 GeV are excluded at the 95% confidence level.

Search for resonances decaying into top-quark pairs using fully hadronic decays in pp collisions with ATLAS at √s=7 TeV

Abstract: A search for resonances produced in 7 TeV proton-proton collisions and decaying into top-quark pairs is described. In this Letter events where the top-quark decay produces two massive jets with large transverse momenta recorded with the ATLAS detector at the Large Hadron Collider are considered. Two techniques that rely on jet substructure are used to separate top-quark jets from those arising from light quarks and gluons. In addition, each massive jet is required to have evidence of an associated bottom-quark decay. The data are consistent with the Standard Model, and limits can be set on the production cross section times branching fraction of a Z′ boson and a Kaluza-Klein gluon resonance. These limits exclude, at the 95% credibility level, Z′ bosons with masses 0.70-1.00 TeV as well as 1.28-1.32 TeV and Kaluza-Klein gluons with masses 0.70-1.62 TeV.

Search for supersymmetry in events with four or more leptons in √s = 8 TeV pp collisions with the ATLAS detector

Abstract: Results from a search for supersymmetry in events with four or more leptons including electrons, muons and taus are presented. The analysis uses a data sample corresponding to 20.3 fb(-1) of proton proton collisions delivered by the Large Hadron Collider at root s = 8 TeV and recorded by the ATLAS detector. Signal regions are designed to target supersymmetric scenarios that can be either enriched in or depleted of events involving the production of a Z boson. No significant deviations are observed in data from standard model predictions and results are used to set upper limits on the event yields from processes beyond the standard model. Exclusion limits at the 95% confidence level on the masses of relevant supersymmetric particles are obtained. In R-parity-violating simplified models with decays of the lightest supersymmetric particle to electrons and muons, limits of 1350 and 750 GeV are placed on gluino and chargino masses, respectively. In R-parity-conserving simplified models with heavy neutralinos decaying to a massless lightest supersymmetric particle, heavy neutralino masses up to 620 GeV are excluded. Limits are also placed on other supersymmetric scenarios.

Search for dark matter in events with heavy quarks and missing transverse momentum in $pp$ collisions with the ATLAS detector

Abstract: This article reports on a search for dark matter pair production in association with bottom or top quarks in 20.3 fb−1 of pp collisions collected at s√=8 TeV by the ATLAS detector at the LHC. Events with large missing transverse momentum are selected when produced in association with high-momentum jets of which one or more are identified as jets containing b-quarks. Final states with top quarks are selected by requiring a high jet multiplicity and in some cases a single lepton. The data are found to be consistent with the Standard Model expectations and limits are set on the mass scale of effective field theories that describe scalar and tensor interactions between dark matter and Standard Model particles. Limits on the dark-matter--nucleon cross-section for spin-independent and spin-dependent interactions are also provided. These limits are particularly strong for low-mass dark matter. Using a simplified model, constraints are set on the mass of dark matter and of a coloured mediator suitable to explain a possible signal of annihilating dark matter.

Search for dark matter produced in association with bottom or top quarks in s=13 TeV pp collisions with the ATLAS detector.

Abstract: A search for weakly interacting massive dark matter particles produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and missing transverse ...

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Phd by thesis

Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These