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We have observed exclusive? production in proton-antiproton collisions at √s = 1.96 TeV, using data from 1.11 ± 0.07 fb−1 integrated luminosity taken by the Run II Collider Detector at Fermilab. We selected events with two electromagnetic showers, each with transverse energy E{sub T}> 2.5 GeV and pseudorapidity.
The authors present a study of [mu][mu][mu][mu], eeee, and [mu][mu]ee events using 1 fb−1 of data collected with the D0 detector at the Fermilab Tevatron p{bar p} Collider at √s = 1.96 TeV. Requiring the lepton pair masses to be greater than 30 GeV, they observe one event, consistent with the expected background of 0.13 ± 0.03 events and with the predicted standard model ZZ and Z[gamma]* production of 1.71 ± 0.15 events. They set an upper limit on the ZZ and Z[gamma]* cross section of 4.4 pb at the 95% C.L. They also derive limits on anomalous neutral trilinear ZZZ and ZZ[gamma]* gauge couplings. The one-parameter 95% C.L. coupling limits with a form factor scale [Lambda] = 1.2 TeV are -0.28
A measurement of W-gamma and Z-gamma production in proton-proton collisions at sqrt(s) = 7 TeV is presented. Results are based on a data sample recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 36 inverse picobarns. The electron and muon decay channels of the W and Z are used. The total cross sections are measured for photon transverse energy>10 GeV and spatial separation from charged leptons in the plane of pseudorapidity and azimuthal angle>0.7, and with an additional dilepton invariant mass requirement of> 50 GeV for the Z-gamma process. The following cross section times branching fraction values are found: sigma(pp to W-gamma+X) B(W to lepton neutrino) = 56.3 +/- 5.0 (stat.) +/- 5.0 (syst.) +/- 2.3 (lumi.) pb and sigma(pp to Z-gamma+X) B}(Z to lepton lepton) = 9.4 +/- 1.0 (stat.) +/- 0.6 (syst.) +/- 0.4 (lumi.) pb. These measurements are in agreement with standard model predictions. The first limits on anomalous WW gamma, ZZ gamma, and Z gamma gamma trilinear gauge couplings at sqrt(s) = 7 TeV are set.
"...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.
Written by authors working at the forefront of research, this accessible treatment presents the current status of the field of collider-based particle physics at the highest energies available, as well as recent results and experimental techniques. It is clearly divided into three sections; The first covers the physics -- discussing the various aspects of the Standard Model as well as its extensions, explaining important experimental results and highlighting the expectations from the Large Hadron Collider (LHC). The second is dedicated to the involved technologies and detector concepts, and the third covers the important - but often neglected - topics of the organisation and financing of high-energy physics research. A useful resource for students and researchers from high-energy physics.
Beyond the world of atoms, at scales smaller than the smallest nuclei, a new world comes into view, populated by an array of colorful elementary particles: strange and charmed quarks, muons and neutrinos, gluons and photons, and many others, all interacting in beautifully intricate patterns. Beyond the Nanoworld tells the story of how this new real
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This successful textbook undergoes a change of character in the third edition. Where earlier editions covered organic polymer chemistry, the third edition covers both physical and organic chemistry. Thus kinetics and thermodynamics of polymerization reactions are discussed. This edition is also distinct from all other polymer textbooks because of its coverage of such currently hot topics as photonic polymers, electricity conducting polymers, polymeric materials for immobilization of reagents and drug release, organic solar cells, organic light emitting diodes. This textbook contains review questions at the end of every chapter, references for further reading, and numerous examples of commercially important processes.