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.

Search for long-lived stopped R-hadrons decaying out-of-time with pp collisions using the ATLAS detector

Abstract: An updated search is performed for gluino, top squark, or bottom squark R-hadrons that have come to rest within the ATLAS calorimeter, and decay at some later time to hadronic jets and a neutralino, using 5.0 and 22.9 fb(-1) of pp collisions at 7 and 8 TeV, respectively. Candidate decay events are triggered in selected empty bunch crossings of the LHC in order to remove pp collision backgrounds. Selections based on jet shape and muon system activity are applied to discriminate signal events from cosmic ray and beam-halo muon backgrounds. In the absence of an excess of events, improved limits are set on gluino, stop, and sbottom masses for different decays, lifetimes, and neutralino masses. With a neutralino of mass 100 GeV, the analysis excludes gluinos with mass below 832 GeV (with an expected lower limit of 731 GeV), for a gluino lifetime between 10 mu s and 1000 s in the generic R-hadron model with equal branching ratios for decays to q (q) over bar(chi) over tilde (0) and g (chi) over tilde (0). Under the same assumptions for the neutralino mass and squark lifetime, top squarks and bottom squarks in the Regge R-hadron model are excluded with masses below 379 and 344 GeV, respectively.

Observation of a new χb state in radiative transitions to Y(1S) and Y(2S) at ATLAS

Abstract: The χb(nP) quarkonium states are produced in proton-proton collisions at the Large Hadron Collider at √s=7 TeV and recorded by the ATLAS detector. Using a data sample corresponding to an integrated luminosity of 4.4 fb-1, these states are reconstructed through their radiative decays to Υ(1S,2S) with Υ→μ+μ-. In addition to the mass peaks corresponding to the decay modes χb(1P,2P)→Υ(1S)γ, a new structure centered at a mass of 10.530±0.005(stat)±0.009(syst) GeV is also observed, in both the Υ(1S)γ and Υ(2S)γ decay modes. This structure is interpreted as the χb(3P) system.

Measurement of ZZ production in pp collisions at √ = 7 TeV and limits on anomalous ZZZ and ZZγ couplings with the ATLAS detector

Abstract: A measurement of the ZZ production cross section in proton-proton collisions at root s = 7 TeV using data recorded by the ATLAS experiment at the Large Hadron Collider is presented. In a data sample corresponding to an integrated luminosity of 4.6 fb(-1) collected in 2011, events are selected that are consistent either with two Z bosons decaying to electrons or muons or with one Z boson decaying to electrons or muons and a second Z boson decaying to neutrinos. The ZZ((*)) -> l(+)l(-)l'(+)l'(-) and ZZ -> l(+)l(-) nu(nu) over bar cross sections are measured in restricted phase-space regions. These results are then used to derive the total cross section for ZZ events produced with both Z bosons in the mass range 66 to 116 GeV, sigma(tot)(ZZ) = 6.7 +/- 0.7 (stat.) (+0.4)(-0.3) (syst.) +/- 0.3 (lumi.) pb, which is consistent with the Standard Model prediction of 5.89(-0.18)(+0.22) pb calculated at next-to-leading order in QCD. The normalized differential cross sections in bins of various kinematic variables are presented. Finally, the differential event yield as a function of the transverse momentum of the leading Z boson is used to set limits on anomalous neutral triple gauge boson couplings in ZZ production.

Search for strong production of supersymmetric particles in final states with missing transverse momentum and at least three b-jets at √s = 8 TeV proton-proton collisions with the ATLAS detector

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.

I and i

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 …

Machine learning

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.).

Phd by thesis

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