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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
Georges Aad1, Brad Abbott2, Jalal Abdallah3, S. Abdel Khalek4  +2917 moreInstitutions (211)
TL;DR: The results are interpreted in the context of several supersymmetric models involving gluinos and scalar top and bottom quarks, as well as a mSUGRA/CMSSM model, significantly extending the previous ATLAS limits.
Abstract: This paper reports the results of a search for strong production of supersymmetric particles in 20.1 fb(-1) of proton-proton collisions at a centre-of-mass energy of 8 TeV using the ATLAS detector at the LHC. The search is performed separately in events with either zero or at least one high-p (T) lepton (electron or muon), large missing transverse momentum, high jet multiplicity and at least three jets identified as originated from the fragmentation of a b-quark. No excess is observed with respect to the Standard Model predictions. The results are interpreted in the context of several supersymmetric models involving gluinos and scalar top and bottom quarks, as well as a mSUGRA/CMSSM model. Gluino masses up to 1340 GeV are excluded, depending on the model, significantly extending the previous ATLAS limits.

107 citations

Journal ArticleDOI
Morad Aaboud1, Zuzana Barnovska2, Nicolas Berger2, Marco Delmastro2, L. Di Ciaccio2, Sabine Elles2, K. Grevtsov3, Tetiana Hryn'ova2, Stéphane Jézéquel2, Iro Koletsou2, Remi Lafaye2, Jessica Levêque2, P. Mastrandea4, G. Sauvage2, Emmanuel Sauvan2, Olivier Simard2, T. Todorov2, Isabelle Wingerter-Seez2, Elena Yatsenko, Djamel Eddine Boumediene5, Emmanuel Busato5, David Calvet5, Samuel Calvet5, Arthur Rene Chomont1, Julien Donini5, Ph Gris5, R. Madar6, Dominique Pallin5, S. M. Romano Saez1, Claudio Santoni5, D. Simon1, Francois Vazeille5, S. Albrand7, Simon Paul Berlendis1, A. Bethani1, C. Camincher1, Johann Collot7, Sabine Crépé-Renaudin7, Pierre-Antoine Delsart7, Carolina Gabaldon7, Marie-Hélène Genest7, P. O. J. Gradin1, J-Y. Hostachy7, Fabienne Ledroit-Guillon7, Annick Lleres7, Arnaud Lucotte7, Fairouz Malek7, E. Petit, Jan Stark7, Benjamin Trocmé7, Mengqing Wu7, G. Rahal, Georges Aad8, Mahmoud Alstaty1, Marlon Barbero8, Alessandro Calandri1, Thomas Philippe Calvet1, Yann Coadou8, Cristinel Diaconu1, Fares Djama8, V. Ellajosyula1, Lorenzo Feligioni8, Asma Hadef1, Gregory David Hallewell1, Fabrice Hubaut8, S. J. Kahn1, E. B. F. G. Knoops8, E. Le Guirriec8, J. Liu1, Kun Liu9, Kun Liu10, Daniele Madaffari8, Emmanuel Monnier8, Steve Muanza8, Elemer Nagy1, Pascal Pralavorio8, Y. Rodina1, Alexandre Rozanov8, Mossadek Talby8, T. Theveneaux-Pelzer5, R. E. Ticse Torres1, Sylvain Tisserant8, Jozsef Toth8, Francois Touchard8, Laurent Vacavant8, C. Wang1 
TL;DR: In this article, a measurement of the total $pp$ cross section at the LHC at $\sqrt{s}=8$ TeV is presented. But this measurement is performed with the ALFA sub-detector of ATLAS.

106 citations

Journal ArticleDOI
Georges Aad1, Brad Abbott2, Jalal Abdallah, A. A. Abdelalim3  +3049 moreInstitutions (190)
TL;DR: This Letter reports on a search for narrow high-mass resonances decaying into dilepton final states at the Large Hadron Collider, recorded by the ATLAS experiment in pp collisions at √s=7 TeV.
Abstract: This Letter reports on a search for narrow high-mass resonances decaying into dilepton final states. The data were recorded by the ATLAS experiment in pp collisions at root s = 7 TeV at the Large Hadron Collider and correspond to a total integrated luminosity of 1.08 (1.21) fb(-1) in the e(+)e(-) (mu(+)mu(-)) channel. No statistically significant excess above the standard model expectation is observed and upper limits are set at the 95% C. L. on the cross section times branching fraction of Z' resonances and Randall-Sundrum gravitons decaying into dileptons as a function of the resonance mass. A lower mass limit of 1.83 TeV on the sequential standard model Z' boson is set. A Randall-Sundrum graviton with coupling k/(M) over bar Pl = 0.1 is excluded at 95% C. L. for masses below 1.63 TeV.

106 citations

Journal ArticleDOI
Georges Aad, Alexander Kupco1, Bjørn Hallvard Samset2, Paolo Laurelli  +2935 moreInstitutions (197)
TL;DR: The results of a search for direct pair production of heavy top-quark partners in 4.7 fb−1 of integrated luminosity from pp collisions at s√=7 TeV collected by the ATLAS detector at the LHC are reported in this paper.
Abstract: The results of a search for direct pair production of heavy top-quark partners in 4.7 fb−1 of integrated luminosity from pp collisions at s√=7 TeV collected by the ATLAS detector at the LHC are reported. Heavy top-quark partners decaying into a top quark and a neutral non-interacting particle are searched for in events with two leptons in the final state. No excess above the Standard Model expectation is observed. Limits are placed on the mass of a supersymmetric scalar top and of a spin-1/2 top-quark partner. A spin-1/2 top-quark partner with a mass between 300 GeV and 480 GeV, decaying to a top quark and a neutral non-interacting particle lighter than 100 GeV, is excluded at 95% confidence level.

105 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