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Brad Abbott

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.


Papers
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Journal ArticleDOI
Morad Aaboud, Georges Aad1, Brad Abbott2, Ovsat Abdinov3  +3004 moreInstitutions (220)
TL;DR: In this paper, a search for events with one top-quark and large missing transverse momentum in the final state was described, and 95% confidence-level upper limits on the corresponding production cross-sections were obtained and these limits were translated into constraints on the parameter space of the models considered.
Abstract: This paper describes a search for events with one top-quark and large missing transverse momentum in the final state. Data collected during 2015 and 2016 by the ATLAS experiment from 13 TeV proton–proton collisions at the LHC corresponding to an integrated luminosity of 36.1 fb−1 are used. Two channels are considered, depending on the leptonic or the hadronic decays of the W boson from the top quark. The obtained results are interpreted in the context of simplified models for dark-matter production and for the single production of a vector-like T quark. In the absence of significant deviations from the Standard Model background expectation, 95% confidence-level upper limits on the corresponding production cross-sections are obtained and these limits are translated into constraints on the parameter space of the models considered.

40 citations

Journal ArticleDOI
TL;DR: This Letter presents the first strong evidence for the resolution of the excited B mesons B(1) and B(2)* as two separate states in fully reconstructed decays to B(+)(*)pi(-).

40 citations

Journal ArticleDOI
Georges Aad1, Brad Abbott2, Jalal Abdallah3, S. Abdel Khalek4  +2908 moreInstitutions (209)
TL;DR: In this article, the prompt and non-prompt production crosssections for psi(2S) mesons are measured using 2.1 fb(-1) of pp collision data at a centre-of-mass energy of 7TeV recorded by the ATLAS experiment at the LHC.
Abstract: The prompt and non-prompt production cross-sections for psi(2S) mesons are measured using 2.1 fb(-1) of pp collision data at a centre-of-mass energy of 7TeV recorded by the ATLAS experiment at the LHC. The measurement exploits the psi(2S) --> J/psi(--> mu(+)mu(-)) pi(+)pi(-) decay mode, and probes psi(2S) mesons with transverse momenta in the range 10 <= p(T) < 100 GeV and rapidity |y| < 2.0. The results are compared to other measurements of psi(2S) production at the LHC and to various theoretical models for prompt and non-prompt quarkonium production.

40 citations

Journal ArticleDOI
Georges Aad1, T. Abajyan2, Brad Abbott3, J. Abdallah  +2921 moreInstitutions (200)
TL;DR: In this article, the CP-violating weak phase phi(s) and the decay width difference were measured using 4.9 fb(-1) of integrated luminosity collected in 2011 by the ATLAS detector from LHC pp collisions at a centre-of-mass energy root s = 7 TeV.
Abstract: A measurement of B-s(0) -> J/psi phi decay parameters, including the CP-violating weak phase phi(s) and the decay width difference Delta Gamma(s) is reported, using 4.9 fb(-1) of integrated luminosity collected in 2011 by the ATLAS detector from LHC pp collisions at a centre-of-mass energy root s = 7 TeV. The mean decay width Gamma(s) and the transversity amplitudes vertical bar A(0)(0)vertical bar(2) and vertical bar A(parallel to)(0)vertical bar(2) are also measured. The values reported for these parameters are: phi(s) = 0.22 +/- 0.41 (stat.) +/- 0.10 (syst.) rad Delta Gamma(s) = 0.053 +/- 0.021 (stat.) +/- 0.010 (syst.) ps(-1) Gamma(s) = 0.677 +/- 0.007 (stat.) +/- 0.004 (syst.) ps(-1) vertical bar A(0)(0)vertical bar(2) = 0.528 +/- 0.006 (stat.) +/- 0.009 (syst.) vertical bar A(parallel to)(0)vertical bar(2) = 0.220 +/- 0.008 (stat.) +/- 0.007 (syst.) where the values quoted for phi(s) and Delta Gamma(s) correspond to the solution compatible with the external measurements to which the strong phase delta(perpendicular to) is constrained and where is Delta Gamma(s) constrained to be positive. The fraction of S-wave KK or f(0) contamination through the decays B-s(0) -> J/psi K+K- (f(0)) is measured as well and is found to be consistent with zero. Results for phi(s) and Delta Gamma(s) are also presented as 68%, 90% and 95% likelihood contours, which show agreement with Standard Model expectations.

40 citations

Journal ArticleDOI
Brad Abbott1, M. Abolins2, V.V. Abramov, Bobby Samir Acharya3  +362 moreInstitutions (47)
TL;DR: A measurement of the transverse momentum distribution of Z bosons produced in p&pmacr; collisions at sqrt[s] = 1.8 TeV from data collected by the DO experiment at the Fermilab Tevatron Collider is presented.
Abstract: We present a measurement of the transverse momentum distribution of Z bosons produced in ppbar collisions at sqrt{s}=1.8 TeV using data collected by the D0 experiment at the Fermilab Tevatron Collider during 1994--1996. We find good agreement between our data and a current resummation calculation. We also use our data to extract values of the non-perturbative parameters for a particular version of the resummation formalism, obtaining significantly more precise values than previous determinations.

40 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
Claude Amsler1, Michael Doser2, Mario Antonelli, D. M. Asner3  +173 moreInstitutions (86)
TL;DR: This biennial Review summarizes much of particle physics, using data from previous editions.

12,798 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