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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.


Papers
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Journal ArticleDOI
Morad Aaboud1, Alexander Kupco, Samuel Webb, Timo Dreyer  +2921 moreInstitutions (59)
TL;DR: In this article, a direct search for lepton flavor violation in decays of the Z boson with the ATLAS detector at the LHC was presented, and the results showed that lepton flavors violated in the decays into an electron or muon and a hadronically decaying r l...
Abstract: Direct searches for lepton flavor violation in decays of the Z boson with the ATLAS detector at the LHC are presented. Decays of the Z boson into an electron or muon and a hadronically decaying r l ...

18 citations

Journal ArticleDOI
Morad Aaboud, Alexander Kupco1, Samuel Webb2, Timo Dreyer3  +2989 moreInstitutions (214)
TL;DR: In this paper, a measurement of ZZ production with the ATLAS detector at the Large Hadron Collider was carried out in the final state with two charged leptons and two neutrinos.
Abstract: This paper presents a measurement of ZZ production with the ATLAS detector at the Large Hadron Collider. The measurement is carried out in the final state with two charged leptons and two neutrinos ...

18 citations

01 Nov 2012
TL;DR: Aad et al. as mentioned in this paper search for direct top squark pair production in final states with one isolated lepton, jets, and missing transverse momentum in √s = 7 TeV pp collisions using 4.7 fb-1 of ATLAS data.
Abstract: Citation for published version (APA): Aad, G., et al., U., Bentvelsen, S., Colijn, A. P., de Jong, P., de Nooij, L., Doxiadis, A. D., Garitaonandia, H., Geerts, D. A. A., Gosselink, M., Kayl, M. S., Koffeman, E., Lee, H., Linde, F., Mechnich, J., Mussche, I., Ottersbach, J. P., Rijpstra, M., Ruckstuhl, N., ... Vreeswijk, M. (2012). Search for direct top squark pair production in final states with one isolated lepton, jets, and missing transverse momentum in √s = 7 TeV pp collisions using 4.7 fb-1 of ATLAS data. Physical Review Letters, 109(21), [211803]. https://doi.org/10.1103/PhysRevLett.109.211803

18 citations

Journal ArticleDOI
Georges Aad1, Brad Abbott2, Dale Charles Abbott3, A. Abed Abud4  +2936 moreInstitutions (202)
TL;DR: The observation of forward proton scattering in association with lepton pairs produced via photon fusion is presented, allowing the background-only hypothesis to be rejected with a significance exceeding 5 standard deviations in each channel.
Abstract: The observation of forward proton scattering in association with lepton pairs (e^{+}e^{-}+p or μ^{+}μ^{-}+p) produced via photon fusion is presented. The scattered proton is detected by the ATLAS Forward Proton spectrometer, while the leptons are reconstructed by the central ATLAS detector. Proton-proton collision data recorded in 2017 at a center-of-mass energy of sqrt[s]=13 TeV are analyzed, corresponding to an integrated luminosity of 14.6 fb^{-1}. A total of 57 (123) candidates in the ee+p (μμ+p) final state are selected, allowing the background-only hypothesis to be rejected with a significance exceeding 5 standard deviations in each channel. Proton-tagging techniques are introduced for cross-section measurements in the fiducial detector acceptance, corresponding to σ_{ee+p}=11.0±2.6(stat)±1.2(syst)±0.3(lumi) and σ_{μμ+p}=7.2±1.6(stat)±0.9(syst)±0.2(lumi) fb in the dielectron and dimuon channel, respectively.

18 citations

Journal ArticleDOI
Georges Aad1, Alexander Kupco2, Peter Davison2, Samuel Webb2  +2930 moreInstitutions (106)
TL;DR: In this article, the authors measured the top-antitop quark pair production charge asymmetry in the dilepton channel using data corresponding to an integrated luminosity of 20.3 fb−1 from pp collisions at a center-of-mass energy of s√=8 TeV collected with the ATLAS detector at the Large Hadron Collider at CERN.
Abstract: Measurements of the top--antitop quark pair production charge asymmetry in the dilepton channel are presented using data corresponding to an integrated luminosity of 20.3 fb−1 from pp collisions at a center-of-mass energy of s√=8 TeV collected with the ATLAS detector at the Large Hadron Collider at CERN. Inclusive and differential measurements as a function of the invariant mass, transverse momentum, and longitudinal boost of the tt¯ system are performed both in the full phase space and in a fiducial phase space closely matching the detector acceptance. Two observables are studied: AllC based on the selected leptons and Att¯C based on the reconstructed tt¯ final state. The inclusive asymmetries are measured in the full phase space to be AllC=0.008±0.006 and Att¯C=0.021±0.016, which are in agreement with the Standard Model predictions of AllC=0.0064±0.0003 and Att¯C=0.0111±0.0004.

18 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
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 …

33,785 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
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.).

13,246 citations

Journal ArticleDOI
01 Apr 1988-Nature
TL;DR: In this paper, a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) is presented.
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

9,929 citations

Journal ArticleDOI
Georges Aad1, T. Abajyan2, Brad Abbott3, Jalal Abdallah4  +2964 moreInstitutions (200)
TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.

9,282 citations