18,118 research outputs found

    Source extraction and photometry for the far-infrared and sub-millimeter continuum in the presence of complex backgrounds

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    (Abridged) We present a new method for detecting and measuring compact sources in conditions of intense, and highly variable, fore/background. While all most commonly used packages carry out the source detection over the signal image, our proposed method builds from the measured image a "curvature" image by double-differentiation in four different directions. In this way point-like as well as resolved, yet relatively compact, objects are easily revealed while the slower varying fore/background is greatly diminished. Candidate sources are then identified by looking for pixels where the curvature exceeds, in absolute terms, a given threshold; the methodology easily allows us to pinpoint breakpoints in the source brightness profile and then derive reliable guesses for the sources extent. Identified peaks are fit with 2D elliptical Gaussians plus an underlying planar inclined plateau, with mild constraints on size and orientation. Mutually contaminating sources are fit with multiple Gaussians simultaneously using flexible constraints. We ran our method on simulated large-scale fields with 1000 sources of different peak flux overlaid on a realistic realization of diffuse background. We find detection rates in excess of 90% for sources with peak fluxes above the 3-sigma signal noise limit; for about 80% of the sources the recovered peak fluxes are within 30% of their input values.Comment: Accepted on A&

    Determinants of Block Tridiagonal Matrices

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    An identity is proven that evaluates the determinant of a block tridiagonal matrix with (or without) corners as the determinant of the associated transfer matrix (or a submatrix of it).Comment: 8 pages, final form. To appear on Linear Algebra and its Application

    Hedin's equations and enumeration of Feynman's diagrams

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    Hedin's equations are solved perturbatively in zero dimension to count Feynman graphs for self-energy, polarization, propagator, effective potential and vertex function in a many-body theory of fermions with two-body interaction. Counting numbers are also obtained in the GW approximation.Comment: Revised published version, 3 pages, no figure

    Notes on Wick's theorem in many-body theory

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    In these pedagogical notes I introduce the operator form of Wick's theorem, i.e. a procedure to bring to normal order a product of 1-particle creation and destruction operators, with respect to some reference many-body state. Both the static and the time- ordered cases are presented.Comment: 6 page

    About arithmetic-geometric multidistances.

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    In a previous paper (see [7] ) we considered the family of multi-argument functions called multidistances, introduced in some recent papers (see [1]-[6]) by J.Martin and G.Mayor , which extend to n-dimensional ordered lists of elements the usual concept of distance between a couple of points in a metric space. In particular Martin and Mayor investigated three classes of multidistances, that is Fermat, sum-based and OWA- based multidistances. In this note we introduce a new family of multidistance functions, which are a generalization of the sum-based multidistances and we call them arithmetic- geometric multidistancesMultidistance, sum-based multidistances, arithmetic-geometric multidistances.

    Multi-argument distances and regular sum-based multidistances.

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    In this paper we consider the family of multi-argument functions called multidistances, introduced in some recent papers by J.Martin and G.Mayor, which extend to n-dimensional ordered lists of elements the usual concept of distance between a couple of points in a metric space. In particular Martin and Mayor investigated three classes of multidistances, that is Fermat, sum-based and OWA- based multidistances.In this note we focus our attention on a specific property of multidistances, i.e. regularity, and we provide an alternative proof about the regularity of the sum-based multidistances.distance, multidistance, regularity, sum-based multidistances;

    A Vision-Based Technique for Lay Length Measurement of Metallic Wire Ropes

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    The lay length of metallic wire ropes is an important dimensional quantity whose analysis is useful to highlight rope deformations due to distributed damages. This paper describes a measurement system that is based on a video camera and on an offline processing algorithm. The camera acquires an image sequence of the running rope; then, an image processing algorithm extracts the rope contour and measures both the distance among rope strands and the whole distance covered by the rope during the test. A mathematical model of the rope contour has been developed and employed to test the proposed algorithm with simulated data. Field tests have been carried out with the proposed system on a working aerial cableway using a general-purpose camer

    Sticky Information and Inflation Persistence: Evidence from U.S. Data

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    This paper provides a novel single equation estimator of the Sticky Information Phillips Curve (SIPC), which permits to estimate the exact model without any approximation or truncation. In detail, information stickiness is estimated by employing a GMM estimator that matches the theoretical with the actual covariances between current inflation and the lagged exogenous shocks that affect firms’ pricing decisions, which are considered the moments that measure inflation persistence. The main result of the paper is to show that the SIPC model can match inflation persistence only at the cost of mispredicting the variance of inflation, which is a novel finding in the empirical literature on the SIPC.Sticky Information, Inflation Persistence, two-stage GMM estimator

    Partial Identification of Probability Distributions with Misclassified Data

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    This paper addresses the problem of data errors in discrete variables. When data errors occur, the observed variable is a misclassified version of the variable of interest, whose distribution is not identified. Inferential problems caused by data errors have been conceptualized through convolution and mixture models. This paper introduces the direct misclassification approach. The approach is based on the observation that in the presence of classification errors, the relation between the distribution of the "true" but unobservable variable and its misclassified representation is given by a linear system of simultaneous equations, in which the coefficient matrix is the matrix of misclassification probabilities. Formalizing the problem in these terms allows one to incorporate any prior information--e.g., validation studies, economic theory, social and cognitive psychology--into the analysis through sets of restrictions on the matrix of misclassification probabilities. Such information can have strong identifying power; the direct misclassification approach fully exploits it to derive identification regions for any real functional of the distribution of interest. A method for estimating the identification regions and construct their confidence sets is given, and illustrated with an empirical analysis of the distribution of pension plan types using data from the Health and Retirement Study.
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