Author
Brad Abbott
Other affiliations: Aix-Marseille University, Purdue University, University of Hong Kong ...read more
Bio: Brad Abbott is an academic researcher from University of Oklahoma. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 137, co-authored 1566 publications receiving 98604 citations. Previous affiliations of Brad Abbott include Aix-Marseille University & Purdue University.
Topics: Large Hadron Collider, Higgs boson, Lepton, Tevatron, Top quark
Papers published on a yearly basis
Papers
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TL;DR: In this article, narrow resonances decaying into WW, WZ or ZZ boson pairs are searched for in 36.7 fb(-1) of proton-proton collision data at a center-of-mass energy of root s = 13 TeV recorded with the ATLAS detect...
70 citations
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TL;DR: In this article, differential cross-sections of highly boosted pair-produced top quarks as a function of top-quark and t (t) over bar system kinematic observables using proton-proton collis...
Abstract: Measurements are made of differential cross-sections of highly boosted pair-produced top quarks as a function of top-quark and t (t) over bar system kinematic observables using proton-proton collis ...
70 citations
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TL;DR: In this article, a search for flavour changing neutral current (FCNC) processes in top-quark decays by the ATLAS Collaboration is presented, with one top quark decaying through the t -> Zq FCNC (q = u, c) channel, and the other through the Standard Model dominant mode t -> Wb.
Abstract: A search for flavour changing neutral current (FCNC) processes in top-quark decays by the ATLAS Collaboration is presented. Data collected from pp collisions at the LHC at a centre-of-mass energy of root s = 7 TeV during 2011, corresponding to an integrated luminosity of 2.1 fb(-1), were used. A search was performed for top-quark pair-production events, with one top quark decaying through the t -> Zq FCNC (q = u, c) channel, and the other through the Standard Model dominant mode t -> Wb. Only the decays of the Z boson to charged leptons and leptonic W-boson decays were considered as signal. Consequently, the final-state topology is characterised by the presence of three isolated charged leptons, at least two jets and missing transverse momentum from the undetected neutrino. No evidence for an FCNC signal was found. An upper limit on the t -> Zq branching ratio of BR(t -> Zq) < 0.73% is set at the 95% confidence level.
69 citations
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TL;DR: In this article, the authors reported a search for Higgs bosons that are produced via vector boson fusion and subsequently decay into invisible particles using 36.1 fb −1 of pp collision data at s = 13TeV recorded by the ATLAS detector at the LHC.
69 citations
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TL;DR: In this paper, measurements of ZZ production in the l(+)l(-)l'l'(+) l'(-) channel in proton-proton collisions at 13 TeV center-of-mass energy at the Large Hadron Collider are presented.
Abstract: Measurements of ZZ production in the l(+)l(-)l'(+)l'(-) channel in proton-proton collisions at 13 TeV center-of-mass energy at the Large Hadron Collider are presented. The data correspond to 36.1 f ...
69 citations
Cited by
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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
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28,685 citations
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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
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TL;DR: This biennial Review summarizes much of particle physics, using data from previous editions.
12,798 citations
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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