A fast Bayesian approach to discrete object detection in astronomical datasets - PowellSnakes I

A new fast Bayesian approach is introduced for the detection of discrete objects immersed in a diffuse background. This new method, called PowellSnakes, speeds up traditional Bayesian techniques by: i) replacing the standard form of the likelihood for the parameters characterizing the discrete objects by an alternative exact form that is much quicker to evaluate; ii) using a simultaneous multiple minimization code based on Powell's direction set algorithm to locate rapidly the local maxima in the posterior; and iii) deciding whether each located posterior peak corresponds to a real object by performing a Bayesian model selection using an approximate evidence value based on a local Gaussian approximation to the peak. The construction of this Gaussian approximation also provides the covariance matrix of the uncertainties in the derived parameter values for the object in question. This new approach provides a speed up in performance by a factor of `hundreds' as compared to existing Bayesian source extraction methods that use MCMC to explore the parameter space, such as that presented by Hobson & McLachlan. We illustrate the capabilities of the method by applying to some simplified toy models. Furthermore PowellSnakes has the advantage of consistently defining the threshold for acceptance/rejection based on priors which cannot be said of the frequentist methods. We present here the first implementation of this technique (Version-I). Further improvements to this implementation are currently under investigation and will be published shortly. The application of the method to realistic simulated Planck observations will be presented in a forthcoming publication.Comment: 30 pages, 15 figures, revised version with minor changes, accepted for publication in MNRA

Assessment of fissionable material behaviour in fission chambers

A comprehensive study is performed in order to assess the pertinence of fission chambers coated with different fissile materials for high neutron flux detection. Three neutron scenarios are proposed to study the fast component of a high neutron flux: (i) high neutron flux with a significant thermal contribution such as BR2, (ii) DEMO magnetic fusion reactor, and (iii) IFMIF high flux test module. In this study, the inventory code ACAB is used to analyze the following questions: (i) impact of different deposits in fission chambers; (ii) effect of the irradiation time/burn-up on the concentration; (iii) impact of activation cross-section uncertainties on the composition of the deposit for all the range of burn-up/irradiation neutron fluences of interest. The complete set of nuclear data (decay, fission yield, activation cross-sections, and uncertainties) provided in the EAF2007 data library are used for this evaluation

Cosmic Microwave Background Images

We aim to present a tutorial on the detection, parameter estimation and statistical analysis of compact sources (far galaxies, galaxy clusters and Galactic dense emission regions) in cosmic microwave background observations. The topic is of great relevance for current and future cosmic microwave background missions because the presence of compact sources in the data introduces very significant biases in the determination of the cosmological parameters that determine the energy contain, origin and evolution of the universe and because compact sources themselves provide us with important information about the large scale structure of the universe.Comment: 10 pages, 2 figures. This preprint replaces a previous one posted in arXiv under the title 'An introduction to compact source detection in cosmic microwave background images'. The change of title was forced by the publishing journa

Detection of new point-sources in WMAP Cosmic Microwave Background (CMB) maps at high Galactic latitude. A new technique to extract point sources from CMB maps

In experimental microwave maps, point-sources can strongly affect the estimation of the power-spectrum and/or the test of Gaussianity of the Cosmic Microwave Background (CMB) component. As a consequence, their removal from the sky maps represents a critical step in the analysis of the CMB data. Before removing a source, however, it is necessary to detect it and source extraction consists of a delicate preliminary operation. In the literature, various techniques have been presented to detect point-sources in the sky maps. The most sophisticated ones exploit the multi-frequency nature of the observations that is typical of the CMB experiments. These techniques have "optimal" theoretical properties and, at least in principle, are capable of remarkable performances. Actually, they are rather difficult to use and this deteriorates the quality of the obtainable results. In this paper, we present a new technique, the "weighted matched filter" (WMF), that is quite simple to use and hence more robust in practical applications. Such technique shows particular efficiency in the detection of sources whose spectra have a slope different from zero. We apply this method to three Southern Hemisphere sky regions - each with an area of 400 square degrees - of the seven years Wilkinson Microwave Anisotropy Probe (WMAP) maps and compare the resulting sources with those of the two seven-year WMAP point-sources catalogues. In these selected regions we find seven additional sources not previously listed in WMAP catalogues and discuss their most likely identification and spectral properties.Comment: Astronomy and Astrophysics, 2011, in pres

A Bayesian approach to discrete object detection in astronomical datasets

A Bayesian approach is presented for detecting and characterising the signal from discrete objects embedded in a diffuse background. The approach centres around the evaluation of the posterior distribution for the parameters of the discrete objects, given the observed data, and defines the theoretically-optimal procedure for parametrised object detection. Two alternative strategies are investigated: the simultaneous detection of all the discrete objects in the dataset, and the iterative detection of objects. In both cases, the parameter space characterising the object(s) is explored using Markov-Chain Monte-Carlo sampling. For the iterative detection of objects, another approach is to locate the global maximum of the posterior at each iteration using a simulated annealing downhill simplex algorithm. The techniques are applied to a two-dimensional toy problem consisting of Gaussian objects embedded in uncorrelated pixel noise. A cosmological illustration of the iterative approach is also presented, in which the thermal and kinetic Sunyaev-Zel'dovich effects from clusters of galaxies are detected in microwave maps dominated by emission from primordial cosmic microwave background anisotropies.Comment: 20 pages, 12 figures, accepted by MNRAS; contains some additional material in response to referee's comment

On the regularity of the covariance matrix of a discretized scalar field on the sphere

We present a comprehensive study of the regularity of the covariance matrix of a discretized field on the sphere. In a particular situation, the rank of the matrix depends on the number of pixels, the number of spherical harmonics, the symmetries of the pixelization scheme and the presence of a mask. Taking into account the above mentioned components, we provide analytical expressions that constrain the rank of the matrix. They are obtained by expanding the determinant of the covariance matrix as a sum of determinants of matrices made up of spherical harmonics. We investigate these constraints for five different pixelizations that have been used in the context of Cosmic Microwave Background (CMB) data analysis: Cube, Icosahedron, Igloo, GLESP and HEALPix, finding that, at least in the considered cases, the HEALPix pixelization tends to provide a covariance matrix with a rank closer to the maximum expected theoretical value than the other pixelizations. The effect of the propagation of numerical errors in the regularity of the covariance matrix is also studied for different computational precisions, as well as the effect of adding a certain level of noise in order to regularize the matrix. In addition, we investigate the application of the previous results to a particular example that requires the inversion of the covariance matrix: the estimation of the CMB temperature power spectrum through the Quadratic Maximum Likelihood algorithm. Finally, some general considerations in order to achieve a regular covariance matrix are also presented.Comment: 36 pages, 12 figures; minor changes in the text, matches published versio

SAT based Enforcement of Domotic Effects in Smart Environments

The emergence of economically viable and efficient sensor technology provided impetus to the development of smart devices (or appliances). Modern smart environments are equipped with a multitude of smart devices and sensors, aimed at delivering intelligent services to the users of smart environments. The presence of these diverse smart devices has raised a major problem of managing environments. A rising solution to the problem is the modeling of user goals and intentions, and then interacting with the environments using user defined goals. `Domotic Effects' is a user goal modeling framework, which provides Ambient Intelligence (AmI) designers and integrators with an abstract layer that enables the definition of generic goals in a smart environment, in a declarative way, which can be used to design and develop intelligent applications. The high-level nature of domotic effects also allows the residents to program their personal space as they see fit: they can define different achievement criteria for a particular generic goal, e.g., by defining a combination of devices having some particular states, by using domain-specific custom operators. This paper describes an approach for the automatic enforcement of domotic effects in case of the Boolean application domain, suitable for intelligent monitoring and control in domotic environments. Effect enforcement is the ability to determine device configurations that can achieve a set of generic goals (domotic effects). The paper also presents an architecture to implement the enforcement of Boolean domotic effects, and results obtained from carried out experiments prove the feasibility of the proposed approach and highlight the responsiveness of the implemented effect enforcement architectur