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Yang Gao

Bio: Yang Gao is an academic researcher from University of Surrey. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 168, co-authored 2047 publications receiving 146301 citations. Previous affiliations of Yang Gao include China Agricultural University & University of Kassel.


Papers
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Journal ArticleDOI
Morad Aaboud1, Alexander Kupco2, Samuel Webb, Timo Dreyer3  +2992 moreInstitutions (214)
TL;DR: In this paper, a search for charged Higgs bosons heavier than the top quark and decaying via H$ √ tb → tb is presented, where multivariate techniques are used to discriminate between signal and background events.
Abstract: A search for charged Higgs bosons heavier than the top quark and decaying via H$^{±}$ → tb is presented. The data analysed corresponds to 36.1 fb$^{−1}$ of pp collisions at $ \sqrt{s}=13 $ TeV and was recorded with the ATLAS detector at the LHC in 2015 and 2016. The production of a charged Higgs boson in association with a top quark and a bottom quark, pp → tbH$^{±}$, is explored in the mass range from m$_{H}$± = 200 to 2000 GeV using multi-jet final states with one or two electrons or muons. Events are categorised according to the multiplicity of jets and how likely these are to have originated from hadronisation of a bottom quark. Multivariate techniques are used to discriminate between signal and background events. No significant excess above the background-only hypothesis is observed and exclusion limits are derived for the production cross-section times branching ratio of a charged Higgs boson as a function of its mass, which range from 2.9 pb at m$_{H}$± = 200 GeV to 0.070 pb at m$_{H}$± = 2000 GeV. The results are interpreted in two benchmark scenarios of the Minimal Supersymmetric Standard Model.

91 citations

Journal ArticleDOI
Morad Aaboud, Georges Aad1, Brad Abbott2, Ovsat Abdinov3  +2984 moreInstitutions (220)
TL;DR: In this article, a search for charged Higgs bosons heavier than the top quark and decaying via H± → tb is presented, which corresponds to 36.1 fb−1 of pp collisions at s=13 TeV.
Abstract: A search for charged Higgs bosons heavier than the top quark and decaying via H± → tb is presented. The data analysed corresponds to 36.1 fb−1 of pp collisions at s=13 TeV and was recorded with the ATLAS detector at the LHC in 2015 and 2016. The production of a charged Higgs boson in association with a top quark and a bottom quark, pp → tbH±, is explored in the mass range from mH± = 200 to 2000 GeV using multi-jet final states with one or two electrons or muons. Events are categorised according to the multiplicity of jets and how likely these are to have originated from hadronisation of a bottom quark. Multivariate techniques are used to discriminate between signal and background events. No significant excess above the background-only hypothesis is observed and exclusion limits are derived for the production cross-section times branching ratio of a charged Higgs boson as a function of its mass, which range from 2.9 pb at mH± = 200 GeV to 0.070 pb at mH± = 2000 GeV. The results are interpreted in two benchmark scenarios of the Minimal Supersymmetric Standard Model.[Figure not available: see fulltext.].

91 citations

Journal ArticleDOI
Morad Aaboud1, Alexander Kupco2, Samuel Webb3, Timo Dreyer4  +2960 moreInstitutions (195)
TL;DR: In this article, the electron and photon energy calibration obtained with the ATLAS detector using about 36 fb−1 of LHC proton-proton collision data recorded at √s=13 TeV in 2015 and 2016 is discussed.
Abstract: This paper presents the electron and photon energy calibration obtained with the ATLAS detector using about 36 fb−1 of LHC proton-proton collision data recorded at √s=13 TeV in 2015 and 2016. The different calibration steps applied to the data and the optimization of the reconstruction of electron and photon energies are discussed. The absolute energy scale is set using a large sample of Z boson decays into electron-positron pairs. The systematic uncertainty in the energy scale calibration varies between 0.03% to 0.2% in most of the detector acceptance for electrons with transverse momentum close to 45 GeV . For electrons with transverse momentum of 10 GeV the typical uncertainty is 0.3% to 0.8% and it varies between 0.25% and 1% for photons with transverse momentum around 60 GeV . Validations of the energy calibration with J/ψ → e+e− decays and radiative Z boson decays are also presented.

91 citations

Journal ArticleDOI
TL;DR: In this paper, the charged particle transverse momentum (pT) spectra are presented for pp collisions at 0.9 and 7 TeV, respectively, and compared with both leading-order QCD and with an empirical scaling of measurements at different collision energies using the scaling variable xT = 2 pT/sqrt(s) over the pT range up to 200 GeV/c.
Abstract: The charged particle transverse momentum (pT) spectra are presented for pp collisions at sqrt(s)=0.9 and 7 TeV. The data samples were collected with the CMS detector at the LHC and correspond to integrated luminosities of 231 inverse microbarns and 2.96 inverse picobarns, respectively. Calorimeter-based high-transverse-energy triggers are employed to enhance the statistical reach of the high-pT measurements. The results are compared with both leading-order QCD and with an empirical scaling of measurements at different collision energies using the scaling variable xT = 2 pT/sqrt(s) over the pT range up to 200 GeV/c. Using a combination of xT scaling and direct interpolation at fixed pT, a reference transverse momentum spectrum at sqrt(s)=2.76 TeV is constructed, which can be used for studying high-pT particle suppression in the dense QCD medium produced in heavy-ion collisions at that centre-of-mass energy.

91 citations

Journal ArticleDOI
TL;DR: The 2011 data set of the CMS experiment, consisting of an integrated luminosity of 4.98 inverse femtobarns of pp collisions at sqrt(s) = 7 TeV, enables expanded searches for direct electroweak pair production of charginos and neutralinos in supersymmetric models as well as their analogs in other models of new physics.
Abstract: The 2011 dataset of the CMS experiment, consisting of an integrated luminosity of 4.98 inverse femtobarns of pp collisions at sqrt(s) = 7 TeV, enables expanded searches for direct electroweak pair production of charginos and neutralinos in supersymmetric models as well as their analogs in other models of new physics. Searches sensitive to such processes, with decays to final states that contain two or more leptons, are presented. Final states with three leptons, with a same-sign lepton pair, and with an opposite-sign lepton pair in conjunction with two jets, are examined. No excesses above the standard model expectations are observed. The results are used in conjunction with previous results on four-lepton final states to exclude a range of chargino and neutralino masses from approximately 200 to 500 GeV in the context of models that assume large branching fractions of charginos and neutralinos to leptons and vector bosons.

91 citations


Cited by
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Journal ArticleDOI

[...]

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 Article
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

13,333 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