Top-Quark Mass Measurement in the Dilepton Channel Using {\it in situ} Jet Energy Scale Calibration

We employ a top-quark mass measurement technique in the dilepton channel with {\it in situ} jet energy scale calibration. Three variables having different jet energy scale dependences are used simultaneously to extract not only the top-quark mass but also the energy scale of the jet from a single likelihood fit. Monte Carlo studies with events corresponding to an integrated luminosity of 5 fb$^{-1}$ proton-proton collisions at the Large Hadron Collider $\sqrt{s} = 7$ TeV are performed. Our analysis suggests that the overall jet energy scale uncertainty can be significantly reduced and the top-quark mass can be determined with a precision of less than 1 GeV/c$^2$, including jet energy scale uncertainty, at the Large Hadron Collider.Comment: Submitted to Phys. Rev.

The Effect Of Pitting Corrosion On The Position Of Aircraft Structural Failures

Corrosion has been shown over the last decade to significantly reduce the structural integrity of aircraft as they age. Previous work at DSTO has shown that pitting and exfoliation corrosion are particularly deleterious to aircraft structural integrity. In addition to reducing fatigue endurance, pitting also increases the surface area of the component over which fatigue failures can occur. This paper reports the results of a Monte-Carlo model of this phenomenon, which has been labelled 'corrosion criticality'. This model concentrates on the effect of the pit spatial density and position on the endurance of a fatigue coupon designed to mimic a simple aircraft component. The study's results show that pitting increases the area of the coupon over which failures can occur

Proof Systems for Retracts in Simply Typed Lambda Calculus

Abstract. This paper concerns retracts in simply typed lambda calculus assuming βη-equality. We provide a simple tableau proof system which characterises when a type is a retract of another type and which leads to an exponential decision procedure.

Top Quark Physics at the Tevatron

We review the field of top-quark physics with an emphasis on experimental techniques. The role of the top quark in the Standard Model of particle physics is summarized and the basic phenomenology of top-quark production and decay is introduced. We discuss how contributions from physics beyond the Standard Model could affect top-quark properties or event samples. The many measurements made at the Fermilab Tevatron, which test the Standard Model predictions or probe for direct evidence of new physics using the top-quark event samples, are reviewed here.Comment: 50 pages, 17 figures, 2 tables; version accepted by Review of Modern Physic

A New Technique for Finding Needles in Haystacks: A Geometric Approach to Distinguishing Between a New Source and Random Fluctuations

We propose a new test statistic based on a score process for determining the statistical significance of a putative signal that may be a small perturbation to a noisy experimental background. We derive the reference distribution for this score test statistic; it has an elegant geometrical interpretation as well as broad applicability. We illustrate the technique in the context of a model problem from high-energy particle physics. Monte Carlo experimental results confirm that the score test results in a significantly improved rate of signal detection.Comment: 5 pages, 4 figure

Kernel density estimation on the torus

Kernel density estimation for multivariate, circular data has been formulated only when the sample space is the sphere, but theory for the torus would also be useful. For data lying on a d-dimensional torus (d >= 1), we discuss kernel estimation of a density, its mixed partial derivatives, and their squared functionals. We introduce a specific class of product kernels whose order is suitably defined in such a way to obtain L-2-risk formulas whose structure can be compared to their Euclidean counterparts. Our kernels are based on circular densities; however, we also discuss smaller bias estimation involving negative kernels which are functions of circular densities. Practical rules for selecting the smoothing degree, based on cross-validation, bootstrap and plug-in ideas are derived. Moreover, we provide specific results on the use of kernels based on the von Mises density. Finally, real-data examples and simulation studies illustrate the findings

Mixtures of nonparametric autoregressions

We consider data generating mechanisms which can be represented as mixtures of finitely many regression or autoregression models.We propose nonparametric estimators for the functions characterising the various mixture components based on a local quasi maximum likelihood approach and prove their consistency. We present an EM algorithm for calculating the estimates numerically which is mainly based on iteratively applying common local smoothers and discuss its convergence properties. © American Statistical Association and Taylor & Francis 2011.postprin