859 research outputs found
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 proton-proton collisions at the Large Hadron Collider 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, 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
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