Measurement of the Ratios of the Branching Fractions [Beta](B0[sigma] --> D−[sigma][pi]+ [pi]+[pi]−)/[Beta](B0 --> D−[pi]+ [pi]+[pi]−) and [Beta](B0[sigma] --> D−[sigma][pi]+)/[Beta](B0 --> D−[pi]+ [pi]+[pi]−) with the CDF Detector


Book Description

We present the measurement of the ratios of branching fractions B... to B..., and B... to B... We analyze data taken with the CDF II detector that corresponds to an integrated luminosity of 355 pb - 1 in pp collisions at ... TeV at the Fermilab Tevatron. Using a novel displaced track trigger we reconstruct 494 ± 28 B... decays, 8098 ± 114 B... decays, 159 ± 17 B... decays, and 3288 ± 76 B... decays. Using the world average value of the ... production ratio fs/fd = 0.259 ± 0.038, we determine the ratios of branching fractions ... where the uncertainties labeled BR and PR refer to the uncertainty on the D meson branching fractions and the production ratio fs/fd, respectively.




Measurement of the Ratios of Branching Fractions B(Bs -] Ds Pi Pi Pi)


Book Description

Using 355 pb−1 of data collected by the CDF II detector in p{bar p} collisions at √s = 1.96 TeV at the Fermilab Tevatron, they study the fully reconstructed hadronic decays B{sub (s)}° → D{sub (s)}−? and B{sub (s)}° → D{sub (s)}−?+?+?−. They present the first measurement of the ratio of branching fractions?(B{sub s}° → D{sub s}−?+?+?−)/?(B° → D−?+?+?−) = 1.05 ± 0.10(stat.) ± 0.22(syst.). They also update their measurement of?(B{sub s}° → D{sub s}−?+)/?(B° → D−?+) to 1.13 ± 0.08(stat.) ± 0.23(syst.) improving the statistical uncertainty by more than a factor of two. They find?(B{sub s}° → D{sub s}−?+) = [3.8 ± 0.3(stat.) ± 1.3(syst.)] x 10−3 and?(B{sub s}° → D{sub s}−?+?+?−) = [8.4 ± 0.8(stat.) ± 3.2(syst.)] x 10−3.




Measurement of the Ratio of Branching Fractions Br(B0s̳ [right Arrow] D−s̳[pi])/Br(B0 [right Arrow] D−[pi]+) at CEF-11


Book Description

The measurement of B0s mixing is one of the flagship analyses for the Run II B physics program. The sensitivity of the measurement to the frequency of B0s oscillations strongly depends on the number of reconstructed B0 mesons. We present the measurement of the ratio of branching fractions Br ..., which directly influences the number of B0s events available for the measurement of B0s mixing at CDF-II. We analyze 115 pb-l of data collected with the CDF-II detector in pp collisions at ... TeV using a novel displaced track trigger ...










A Minicourse on Stochastic Partial Differential Equations


Book Description

This title contains lectures that offer an introduction to modern topics in stochastic partial differential equations and bring together experts whose research is centered on the interface between Gaussian analysis, stochastic analysis, and stochastic PDEs.




Particle Physics


Book Description

This book explains the emergence of a profoundly new understanding of the fundamental forces of Nature.




Optimization Methods in Finance


Book Description

Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.




Mathematical Theory of Optimization


Book Description

This book provides an introduction to the mathematical theory of optimization. It emphasizes the convergence theory of nonlinear optimization algorithms and applications of nonlinear optimization to combinatorial optimization. Mathematical Theory of Optimization includes recent developments in global convergence, the Powell conjecture, semidefinite programming, and relaxation techniques for designs of approximation solutions of combinatorial optimization problems.