Massive Higher Spin Fields Coupled to a Scalar: Aspects of Interaction and Causality

We consider in detail the most general cubic Lagrangian which describes an interaction between two identical higher spin fieldsin a triplet formulation with a scalar field, all fields having the same values of the mass. After performing the gauge fixing procedure we find that for the case of massive fields the gauge invariance does not guarantee the preservation of the correct number of propagating physical degrees of freedom. In order to get the correct number of degrees of freedom for the massive higher spin field one should impose some additional conditions on parameters of the vertex. Further independent constraints are provided by the causality analysis, indicating that the requirement of causality should be imposed in addition to the requirement of gauge invariance in order to have a consistent propagation of massive higher spin fields.Comment: 34 pages, comments, references and one Appendix added. Typos corrected. Published versio

A generalized Fellner-Schall method for smoothing parameter estimation with application to Tweedie location, scale and shape models

We consider the estimation of smoothing parameters and variance components in models with a regular log likelihood subject to quadratic penalization of the model coefficients, via a generalization of the method of Fellner (1986) and Schall (1991). In particular: (i) we generalize the original method to the case of penalties that are linear in several smoothing parameters, thereby covering the important cases of tensor product and adaptive smoothers; (ii) we show why the method's steps increase the restricted marginal likelihood of the model, that it tends to converge faster than the EM algorithm, or obvious accelerations of this, and investigate its relation to Newton optimization; (iii) we generalize the method to any Fisher regular likelihood. The method represents a considerable simplification over existing methods of estimating smoothing parameters in the context of regular likelihoods, without sacrificing generality: for example, it is only necessary to compute with the same first and second derivatives of the log-likelihood required for coefficient estimation, and not with the third or fourth order derivatives required by alternative approaches. Examples are provided which would have been impossible or impractical with pre-existing Fellner-Schall methods, along with an example of a Tweedie location, scale and shape model which would be a challenge for alternative methods

X-ray Lighthouses of the High-Redshift Universe. II. Further Snapshot Observations of the Most Luminous z>4 Quasars with Chandra

We report on Chandra observations of a sample of 11 optically luminous (Mb<-28.5) quasars at z=3.96-4.55 selected from the Palomar Digital Sky Survey and the Automatic Plate Measuring Facility Survey. These are among the most luminous z>4 quasars known and hence represent ideal witnesses of the end of the "dark age ''. Nine quasars are detected by Chandra, with ~2-57 counts in the observed 0.5-8 keV band. These detections increase the number of X-ray detected AGN at z>4 to ~90; overall, Chandra has detected ~85% of the high-redshift quasars observed with snapshot (few kilosecond) observations. PSS 1506+5220, one of the two X-ray undetected quasars, displays a number of notable features in its rest-frame ultraviolet spectrum, the most prominent being broad, deep SiIV and CIV absorption lines. The average optical-to-X-ray spectral index for the present sample (=-1.88+/-0.05) is steeper than that typically found for z>4 quasars but consistent with the expected value from the known dependence of this spectral index on quasar luminosity. We present joint X-ray spectral fitting for a sample of 48 radio-quiet quasars in the redshift range 3.99-6.28 for which Chandra observations are available. The X-ray spectrum (~870 counts) is well parameterized by a power law with Gamma=1.93+0.10/-0.09 in the rest-frame ~2-40 keV band, and a tight upper limit of N_H~5x10^21 cm^-2 is obtained on any average intrinsic X-ray absorption. There is no indication of any significant evolution in the X-ray properties of quasars between redshifts zero and six, suggesting that the physical processes of accretion onto massive black holes have not changed over the bulk of cosmic time.Comment: 15 pages, 7 figures, accepted for publication in A

A Critical Examination of Quartz, Tridymite and Cristobalite: The Estimation of Free Silica

1. The introduction records the various theories on the aetiology of silicosis and pneumokoniosis with reference to the pathological and chemical aspects of the changes brought about in the lungs by small silica particles. A survey is also given of physical and chemical analytical techniques for the estimation of the free silica content of rocks and dusts. 2. Detailed investigation of one chemical method, that of Trostel and Wynne, has shown it to be suitable, after modification, for the analysis of Stirlingshire coal-measure rocks. However, the high experimental losses occurring during the analysis of small particles preclude its use for the determination of the quartz content of airborne dusts. 3. The examination of the physical method of Differential Thermal Analysis has shown it to be influenced by the presence of a layer of non-quartz silica,which is not estimated,on ground quartz particles. The properties of this layer have been investigated and it has been concluded that it is of relatively constant thickness and density independent of the particle size of the quartz. The proportion of layer to quartz in airborne dusts is considerable and prevents the use of this method, as it stands, for their analysis. During rock analysis this method suffers some loss in accuracy due to the presence of the non-quartz layer hut suggestions are made to produce at least a partial recovery of the loss and also to make the method practicable for dust analysis. 4. The presence of this non-quartz layer has been shown to interfere with the X-ray analysis for quartz in dusts

Designing a Belief Function-Based Accessibility Indicator to Improve Web Browsing for Disabled People

The purpose of this study is to provide an accessibility measure of web-pages, in order to draw disabled users to the pages that have been designed to be ac-cessible to them. Our approach is based on the theory of belief functions, using data which are supplied by reports produced by automatic web content assessors that test the validity of criteria defined by the WCAG 2.0 guidelines proposed by the World Wide Web Consortium (W3C) organization. These tools detect errors with gradual degrees of certainty and their results do not always converge. For these reasons, to fuse information coming from the reports, we choose to use an information fusion framework which can take into account the uncertainty and imprecision of infor-mation as well as divergences between sources. Our accessibility indicator covers four categories of deficiencies. To validate the theoretical approach in this context, we propose an evaluation completed on a corpus of 100 most visited French news websites, and 2 evaluation tools. The results obtained illustrate the interest of our accessibility indicator

Evidential-EM Algorithm Applied to Progressively Censored Observations

Evidential-EM (E2M) algorithm is an effective approach for computing maximum likelihood estimations under finite mixture models, especially when there is uncertain information about data. In this paper we present an extension of the E2M method in a particular case of incom-plete data, where the loss of information is due to both mixture models and censored observations. The prior uncertain information is expressed by belief functions, while the pseudo-likelihood function is derived based on imprecise observations and prior knowledge. Then E2M method is evoked to maximize the generalized likelihood function to obtain the optimal estimation of parameters. Numerical examples show that the proposed method could effectively integrate the uncertain prior infor-mation with the current imprecise knowledge conveyed by the observed data

Toward the estimation of background fluctuations under newly-observed signals in particle physics

When the number of events associated with a signal process is estimated in particle physics, it is common practice to extrapolate background distributions from control regions to a predefined signal window. This allows accurate estimation of the expected, or average, number of background events under the signal. However, in general, the actual number of background events can deviate from the average due to fluctuations in the data. Such a difference can be sizable when compared to the number of signal events in the early stages of data analysis following the observation of a new particle, as well as in the analysis of rare decay channels. We report on the development of a data-driven technique that aims to estimate the actual, as opposed to the expected, number of background events in a predefined signal window. We discuss results on toy Monte Carlo data and provide a preliminary estimate of systematic uncertainty

Application of Monte Carlo Algorithms to the Bayesian Analysis of the Cosmic Microwave Background

Power spectrum estimation and evaluation of associated errors in the presence of incomplete sky coverage; non-homogeneous, correlated instrumental noise; and foreground emission is a problem of central importance for the extraction of cosmological information from the cosmic microwave background. We develop a Monte Carlo approach for the maximum likelihood estimation of the power spectrum. The method is based on an identity for the Bayesian posterior as a marginalization over unknowns. Maximization of the posterior involves the computation of expectation values as a sample average from maps of the cosmic microwave background and foregrounds given some current estimate of the power spectrum or cosmological model, and some assumed statistical characterization of the foregrounds. Maps of the CMB are sampled by a linear transform of a Gaussian white noise process, implemented numerically with conjugate gradient descent. For time series data with N_{t} samples, and N pixels on the sphere, the method has a computational expense $KO[N^{2} +- N_{t} +AFw-log N_{t}], where K is a prefactor determined by the convergence rate of conjugate gradient descent. Preconditioners for conjugate gradient descent are given for scans close to great circle paths, and the method allows partial sky coverage for these cases by numerically marginalizing over the unobserved, or removed, region.Comment: submitted to Ap