Filling in CMB map missing data using constrained Gaussian realizations

For analyzing maps of the cosmic microwave background sky, it is necessary to mask out the region around the galactic equator where the parasitic foreground emission is strongest as well as the brightest compact sources. Since many of the analyses of the data, particularly those searching for non-Gaussianity of a primordial origin, are most straightforwardly carried out on full-sky maps, it is of great interest to develop efficient algorithms for filling in the missing information in a plausible way. We explore practical algorithms for filling in based on constrained Gaussian realizations. Although carrying out such realizations is in principle straightforward, for finely pixelized maps as will be required for the Planck analysis a direct brute force method is not numerically tractable. We present some concrete solutions to this problem, both on a spatially flat sky with periodic boundary conditions and on the pixelized sphere. One approach is to solve the linear system with an appropriately preconditioned conjugate gradient method. While this approach was successfully implemented on a rectangular domain with periodic boundary conditions and worked even for very wide masked regions, we found that the method failed on the pixelized sphere for reasons that we explain here. We present an approach that works for full-sky pixelized maps on the sphere involving a kernel-based multi-resolution Laplace solver followed by a series of conjugate gradient corrections near the boundary of the mask.Comment: 22 pages, 14 figures, minor changes, a few missing references adde

A Bayesian Approach to Locating the Red Giant Branch Tip Magnitude (Part I)

We present a new approach for identifying the Tip of the Red Giant Branch (TRGB) which, as we show, works robustly even on sparsely populated targets. Moreover, the approach is highly adaptable to the available data for the stellar population under study, with prior information readily incorporable into the algorithm. The uncertainty in the derived distances is also made tangible and easily calculable from posterior probability distributions. We provide an outline of the development of the algorithm and present the results of tests designed to characterize its capabilities and limitations. We then apply the new algorithm to three M31 satellites: Andromeda I, Andromeda II and the fainter Andromeda XXIII, using data from the Pan-Andromeda Archaeological Survey (PAndAS), and derive their distances as $731^{(+ 5) + 18}_{(- 4) - 17}$ kpc, $634^{(+ 2) + 15}_{(- 2) - 14}$ kpc and $733^{(+ 13)+ 23}_{(- 11) - 22}$ kpc respectively, where the errors appearing in parentheses are the components intrinsic to the method, while the larger values give the errors after accounting for additional sources of error. These results agree well with the best distance determinations in the literature and provide the smallest uncertainties to date. This paper is an introduction to the workings and capabilities of our new approach in its basic form, while a follow-up paper shall make full use of the method's ability to incorporate priors and use the resulting algorithm to systematically obtain distances to all of M31's satellites identifiable in the PAndAS survey area.Comment: 11 pages, 18 figure

The XMM-Newton serendipitous survey. VII. The third XMM-Newton serendipitous source catalogue

Thanks to the large collecting area (3 x ~1500 cm$^2$ at 1.5 keV) and wide field of view (30' across in full field mode) of the X-ray cameras on board the European Space Agency X-ray observatory XMM-Newton, each individual pointing can result in the detection of hundreds of X-ray sources, most of which are newly discovered. Recently, many improvements in the XMM-Newton data reduction algorithms have been made. These include enhanced source characterisation and reduced spurious source detections, refined astrometric precision, greater net sensitivity and the extraction of spectra and time series for fainter sources, with better signal-to-noise. Further, almost 50\% more observations are in the public domain compared to 2XMMi-DR3, allowing the XMM-Newton Survey Science Centre (XMM-SSC) to produce a much larger and better quality X-ray source catalogue. The XMM-SSC has developed a pipeline to reduce the XMM-Newton data automatically and using improved calibration a new catalogue version has been produced from XMM-Newton data made public by 2013 Dec. 31 (13 years of data). Manual screening ensures the highest data quality. This catalogue is known as 3XMM. In the latest release, 3XMM-DR5, there are 565962 X-ray detections comprising 396910 unique X-ray sources. For the 133000 brightest sources, spectra and lightcurves are provided. For all detections, the positions on the sky, a measure of the quality of the detection, and an evaluation of the X-ray variability is provided, along with the fluxes and count rates in 7 X-ray energy bands, the total 0.2-12 keV band counts, and four hardness ratios. To identify the detections, a cross correlation with 228 catalogues is also provided for each X-ray detection. 3XMM-DR5 is the largest X-ray source catalogue ever produced. Thanks to the large array of data products, it is an excellent resource in which to find new and extreme objects.Comment: 23 pages, version accepted for publication in A&

Cosmological weak lensing with the HST GEMS survey

We present our cosmic shear analysis of GEMS, one of the largest wide-field surveys ever undertaken by the Hubble Space Telescope. Imaged with the Advanced Camera for Surveys (ACS), GEMS spans 795 square arcmin in the Chandra Deep Field South. We detect weak lensing by large-scale structure in high resolution F606W GEMS data from ~60 resolved galaxies per square arcminute. We measure the two-point shear correlation function, the top-hat shear variance and the shear power spectrum, performing an E/B mode decomposition for each statistic. We show that we are not limited by systematic errors and use our results to place joint constraints on the matter density parameter Omega_m and the amplitude of the matter power spectrum sigma_8. We find sigma_8(Omega_m/0.3)^{0.65}=0.68 +/- 0.13 where the 1sigma error includes both our uncertainty on the median redshift of the survey and sampling variance. Removing image and point spread function (PSF) distortions are crucial to all weak lensing analyses. We therefore include a thorough discussion on the degree of ACS PSF distortion and anisotropy which we characterise directly from GEMS data. Consecutively imaged over 20 days, GEMS data also allows us to investigate PSF instability over time. We find that, even in the relatively short GEMS observing period, the ACS PSF ellipticity varies at the level of a few percent which we account for with a semi-time dependent PSF model. Our correction for the temporal and spatial variability of the PSF is shown to be successful through a series of diagnostic tests.Comment: 17 pages, 16 figures. Version accepted by MNRA

Detection of X-ray Clusters of Galaxies by Matching RASS Photons and SDSS Galaxies within GAVO

A new method for a simultaneous search for clusters of galaxies in X-ray photon maps and optical galaxy maps is described. The merging of X-ray and optical data improves the source identification so that a large amount of telescope time for spectroscopic follow-up can be saved. The method appears thus ideally suited for the analysis of the recently proposed wide-angle X-ray missions like DUO and ROSITA. As a first application, clusters are extracted from the 3rd version of the ROSAT All-Sky Survey and the Early Date Release of the Sloan Digital Sky Survey (SDSS). The time-consuming computations are performed within the German Astrophysical Virtual Observatory (GAVO). On a test area of 140 square degrees, 75 X-ray clusters are detected down to an X-ray flux limit of $3-5\times 10^{-13} {\rm erg} {\rm s}^{-1} {\rm cm}^{-2}$ in the ROSAT energy band 0.1-2.4 keV. The clusters have redshifts $z\le 0.5$. The survey thus fills the gap between traditional large-area X-ray surveys and serendipitous X-ray cluster searches based on pointed observations, and has the potential to yield about 4,000 X-ray clusters after completion of SDSS.Comment: 19 pages, low-resolution figures, accepted for publication in Astronomy and Astrophysic

Modelling Aspects of Planar Multi-Mode Antennas for Direction-of-Arrival Estimation

Multi-mode antennas are an alternative to classical antenna arrays, and hence a promising emerging sensor technology for a vast variety of applications in the areas of array signal processing and digital communications. An unsolved problem is to describe the radiation pattern of multi-mode antennas in closed analytic form based on calibration measurements or on electromagnetic field (EMF) simulation data. As a solution, we investigate two modeling methods: One is based on the array interpolation technique (AIT), the other one on wavefield modeling (WM). Both methods are able to accurately interpolate quantized EMF data of a given multi-mode antenna, in our case a planar four-port antenna developed for the 6-8.5 GHz range. Since the modeling methods inherently depend on parameter sets, we investigate the influence of the parameter choice on the accuracy of both models. Furthermore, we evaluate the impact of modeling errors for coherent maximum-likelihood direction-of-arrival (DoA) estimation given different model parameters. Numerical results are presented for a single polarization component. Simulations reveal that the estimation bias introduced by model errors is subject to the chosen model parameters. Finally, we provide optimized sets of AIT and WM parameters for the multi-mode antenna under investigation. With these parameter sets, EMF data samples can be reproduced in interpolated form with high angular resolution