105,157 research outputs found

    Building an Optimal Census of the Solar Neighborhood with Pan-STARRS Data

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    We estimate the fidelity of solar neighborhood (D < 100 pc) catalogs soon to be derived from Pan-STARRS astrometric data. We explore two quantities used to measure catalog quality: completeness, the fraction of desired sources included in a catalog; and reliability, the fraction of entries corresponding to desired sources. We show that the main challenge in identifying nearby objects with Pan-STARRS will be reliably distinguishing these objects from distant stars, which are vastly more numerous. We explore how joint cuts on proper motion and parallax will impact catalog reliability and completeness. Using synthesized astrometry catalogs, we derive optimum parallax and proper motion cuts to build a census of the solar neighborhood with the Pan-STARRS 3 Pi Survey. Depending on the Galactic latitude, a parallax cut pi / sigma pi > 5 combined with a proper motion cut ranging from mu / sigma mu > 1-8 achieves 99% reliability and 60% completeness.Comment: 7 Pages, 4 Figures, 3 Tables. PASP in pres

    Review of the mathematical foundations of data fusion techniques in surface metrology

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    The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed

    ADAM: a general method for using various data types in asteroid reconstruction

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    We introduce ADAM, the All-Data Asteroid Modelling algorithm. ADAM is simple and universal since it handles all disk-resolved data types (adaptive optics or other images, interferometry, and range-Doppler radar data) in a uniform manner via the 2D Fourier transform, enabling fast convergence in model optimization. The resolved data can be combined with disk-integrated data (photometry). In the reconstruction process, the difference between each data type is only a few code lines defining the particular generalized projection from 3D onto a 2D image plane. Occultation timings can be included as sparse silhouettes, and thermal infrared data are efficiently handled with an approximate algorithm that is sufficient in practice due to the dominance of the high-contrast (boundary) pixels over the low-contrast (interior) ones. This is of particular importance to the raw ALMA data that can be directly handled by ADAM without having to construct the standard image. We study the reliability of the inversion by using the independent shape supports of function series and control-point surfaces. When other data are lacking, one can carry out fast nonconvex lightcurve-only inversion, but any shape models resulting from it should only be taken as illustrative global-scale ones.Comment: 11 pages, submitted to A&

    The HIPASS Catalogue - II. Completeness, Reliability, and Parameter Accuracy

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    The HI Parkes All Sky Survey (HIPASS) is a blind extragalactic HI 21-cm emission line survey covering the whole southern sky from declination -90 to +25. The HIPASS catalogue (HICAT), containing 4315 HI-selected galaxies from the region south of declination +2, is presented in Meyer et al. (2004a, Paper I). This paper describes in detail the completeness and reliability of HICAT, which are calculated from the recovery rate of synthetic sources and follow-up observations, respectively. HICAT is found to be 99 per cent complete at a peak flux of 84 mJy and an integrated flux of 9.4 Jy km/s. The overall reliability is 95 per cent, but rises to 99 per cent for sources with peak fluxes >58 mJy or integrated flux > 8.2 Jy km/s. Expressions are derived for the uncertainties on the most important HICAT parameters: peak flux, integrated flux, velocity width, and recessional velocity. The errors on HICAT parameters are dominated by the noise in the HIPASS data, rather than by the parametrization procedure.Comment: Accepted for publication in MNRAS. 12 pages, 11 figures. Paper with higher resolution figures can be downloaded from http://hipass.aus-vo.or

    The metallicity properties of zCOSMOS galaxies at 0.2<z<0.8

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    We study the metallicity properties of galaxies in the zCOSMOS sample between 0.2<z<0.8. At z<0.46, where Ha and [NII] are detected, we find the same dependence of metallicity on stellar mass and Star Formation Rate (SFR), the Fundamental Metallicity Relation, found by Mannucci et al. (2010) in SDSS galaxies on a similar redshift range. We extend this relation to higher redshift, 0.49<z<0.8 where the R23 metallicity index can be measured in our data, finding no evidence for evolution, and a metallicity scatter around the relation of about 0.16 dex. This result confirms, with a much higher level of significance with respect to previous works, the absence of evolution of the FMR during the last half of cosmic history.Comment: 9 pages, 7 figures, accepted for publication in MNRA

    A Nonparametric Approach for Assessing Precision in Georeferenced Point Clouds Best Fit Planes: Toward More Reliable Thresholds

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    The fitting of a plane to data points is essential to the geosciences. However, it is recognized that the reliability of these best fit planes depends upon the point set distribution and geometry, evaluated in terms of the eigen-based parameters derived from the moment of inertia analysis. Despite its significance, few studies have addressed the uncertainties of the analysis, which can adversely affect the reproduction of results one of the cornerstones of scientific endeavor. Aiming to contribute toward the neglected issue of the moment of inertia precision, we have developed a bootstrap resampling scheme to empirically discover the distribution of uncertainties in the orientation of best fit planes. Dispersion of the bootstrapped normal vectors to the best fit plane is regarded as a measure of precision, evaluated with the maximum angular distance from the optimal solution. This rationale was tested using Monte Carlo-generated samples covering a comprehensive range of shape parameters to assess the dependence between eigen parameters and their inherent bias. Our results show that the oblateness of the point cloud is a robust parameter to assess the reliability of the best fit plane. Given this, the method was then applied to a publicly available lidar data set. We argue that georeferenced point clouds with an oblateness parameter greater than 3 and 1.5 may be placed at 95% confidence levels of 5° and 10°, respectively. We propose using these values as thresholds to obtain robust best fit planes, guaranteeing reproducible results for scientific research.Fil: Gallo, Leandro César. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Geociencias Básicas, Aplicadas y Ambientales de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Geociencias Básicas, Aplicadas y Ambientales de Buenos Aires; ArgentinaFil: Cristallini, Ernesto Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Svarc, Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentin
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