2,081 research outputs found

    Some Good Reasons to Use Matched Filters for the Detection of Point Sources in CMB Maps

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    In this draft we comment on the results concerning the performances of matched filters, scale adaptive filters and Mexican hat wavelet that recently appeared in literature in the context of point source detection in Cosmic Microwave Background maps. In particular, we show that, contrary to what has been claimed, the use of the matched filters still appear to be the most reliable and efficient method to disantangle point sources from the backgrounds, even when using detection criterion that, differently from the classic nσn\sigma thresholding rule, takes into account not only the height of the peaks in the signal corresponding to the candidate sources but also their curvature.Comment: Replacement after submission to A&A and referee's comments. Astronomy and Astrophysics, in press, JNL/2003/473

    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

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    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

    Statistical properties of dust far-infrared emission

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    The description of the statistical properties of dust emission gives important constraints on the physics of the interstellar medium but it is also a useful way to estimate the contamination of diffuse interstellar emission in the cases where it is considered a nuisance. The main goals of this analysis of the power spectrum and non-Gaussian properties of 100 micron dust emission are 1) to estimate the power spectrum of interstellar matter density in three dimensions, 2) to review and extend previous estimates of the cirrus noise due to dust emission and 3) to produce simulated dust emission maps that reproduce the observed statistical properties. The main results are the following. 1) The cirrus noise level as a function of brightness has been previously overestimated. It is found to be proportional to instead of ^1.5, where is the local average brightness at 100 micron. This scaling is in accordance with the fact that the brightness fluctuation level observed at a given angular scale on the sky is the sum of fluctuations of increasing amplitude with distance on the line of sight. 2) The spectral index of dust emission at scales between 5 arcmin and 12.5 degrees is =-2.9 on average but shows significant variations over the sky. Bright regions have systematically steeper power spectra than diffuse regions. 3) The skewness and kurtosis of brightness fluctuations is high, indicative of strong non-Gaussianity. 4) Based on our characterization of the 100 micron power spectrum we provide a prescription of the cirrus confusion noise as a function of wavelength and scale. 5) Finally we present a method based on a modification of Gaussian random fields to produce simulations of dust maps which reproduce the power spectrum and non-Gaussian properties of interstellar dust emission.Comment: 13 pages, 13 figures. Accepted for publication in A&

    Unevenly-sampled signals: a general formalism of the Lomb-Scargle periodogram

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    The periodogram is a popular tool that tests whether a signal consists only of noise or if it also includes other components. The main issue of this method is to define a critical detection threshold that allows identification of a component other than noise, when a peak in the periodogram exceeds it. In the case of signals sampled on a regular time grid, determination of such a threshold is relatively simple. When the sampling is uneven, however, things are more complicated. The most popular solution in this case is to use the "Lomb-Scargle" periodogram, but this method can be used only when the noise is the realization of a zero-mean, white (i.e. flat-spectrum) random process. In this paper, we present a general formalism based on matrix algebra, which permits analysis of the statistical properties of a periodogram independently of the characteristics of noise (e.g. colored and/or non-stationary), as well as the characteristics of sampling.Comment: 10 pages, 11 figures, Astronomy and Astrophysics, in pres

    The correct estimate of the probability of false detection of the matched filter in the detection of weak signals. II. (Further results with application to a set of ALMA and ATCA data)

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    The matched filter (MF) is one of the most popular and reliable techniques to the detect signals of known structure and amplitude smaller than the level of the contaminating noise. Under the assumption of stationary Gaussian noise, MF maximizes the probability of detection subject to a constant probability of false detection or false alarm (PFA). This property relies upon a priori knowledge of the position of the searched signals, which is usually not available. Recently, it has been shown that when applied in its standard form, MF may severely underestimate the PFA. As a consequence the statistical significance of features that belong to noise is overestimated and the resulting detections are actually spurious. For this reason, an alternative method of computing the PFA has been proposed that is based on the probability density function (PDF) of the peaks of an isotropic Gaussian random field. In this paper we further develop this method. In particular, we discuss the statistical meaning of the PFA and show that, although useful as a preliminary step in a detection procedure, it is not able to quantify the actual reliability of a specific detection. For this reason, a new quantity is introduced called the specific probability of false alarm (SPFA), which is able to carry out this computation. We show how this method works in targeted simulations and apply it to a few interferometric maps taken with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Australia Telescope Compact Array (ATCA). We select a few potential new point sources and assign an accurate detection reliability to these sources.Comment: 28 pages, 20 figures, Astronomy & Astrophysics, Minor changes and some typos correcte

    On Optimal Detection of Point Sources in CMB Maps

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    Point-source contamination in high-precision Cosmic Microwave Background (CMB) maps severely affects the precision of cosmological parameter estimates. Among the methods that have been proposed for source detection, wavelet techniques based on ``optimal'' filters have been proposed.In this paper we show that these filters are in fact only restrictive cases of a more general class of matched filters that optimize signal-to-noise ratio and that have, in general, better source detection capabilities, especially for lower amplitude sources. These conclusions are confirmed by some numerical experiments. \keywords{Methods: data analysis -- Methods: statisticalComment: 6 pages, 3 figure
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