arXiv subjects

E. Salerno

Publications and source records attributed to E. Salerno.

12 recordsLinked to original sources

arXiv2012

Radio spectra and polarisation properties of a bright sample of Radio-Loud Broad Absorption Line Quasars

The origin of broad-absorption-line quasars (BAL QSOs) is still an open issue. Accounting for ~20% of the QSO population, these objects present broad absorption lines in their optical spectra generated from outflows with velocities up to 0.2c. In this work we present the results of a multi-frequency study of a well-defined radio-loud BAL QSO sample, and a comparison sample of radio-loud non-BAL QSOs, both selected from the Sloan Digital Sky Survey (SDSS). We aim to test which of the currently-popular models for the BAL phenomenon - `orientation' or 'evolutionary' - best accounts for the radio properties of BAL quasars. Observations from 1.4 to 43 GHz have been obtained with the VLA and Effelsberg telescopes, and data from 74 to 408 MHz have been compiled from the literature. The fractions of candidate GHz-peaked sources are similar in the two samples (36\pm12% vs 23\pm8%), suggesting that BAL QSOs are not generally younger than non-BAL QSOs. BAL and non-BAL QSOs show a large range of spectral indices, consistent with a broad range of orientations. There is weak evidence (91% confidence) that the spectral indices of the BAL QSOs are steeper than those of non-BAL QSOs, mildly favouring edge-on orientations. At a higher level of significance (\geq97%), the spectra of BAL QSOs are not flatter than those of non-BAL QSOs, which suggests that a polar orientation is not preferred.

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arXiv2011

Adaptive Langevin Sampler for Separation of t-Distribution Modelled Astrophysical Maps

We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC) sampling scheme to unmix the astrophysical sources and describe the derivation details. In this scheme, we use the Langevin stochastic equation for transitions, which enables parallel drawing of random samples from the posterior, and reduces the computation time significantly (by two orders of magnitude). In addition, Student's t-distribution parameters are updated throughout the iterations. The results on astrophysical source separation are assessed with two performance criteria defined in the pixel and the frequency domains.

astro-ph.IM↗

arXiv2011

A Bayesian technique for the detection of point sources in CMB maps

The detection and flux estimation of point sources in cosmic microwave background (CMB) maps is a very important task in order to clean the maps and also to obtain relevant astrophysical information. In this paper we propose a maximum a posteriori (MAP) approach detection method in a Bayesian scheme which incorporates prior information about the source flux distribution, the locations and the number of sources. We apply this method to CMB simulations with the characteristics of the Planck satellite channels at 30, 44, 70 and 100 GHz. With a similar level of spurious sources, our method yields more complete catalogues than the matched filter with a 5 sigma threshold. Besides, the new technique allows us to fix the number of detected sources in a non-arbitrary way.

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arXiv2011

Joint Bayesian separation and restoration of CMB from convolutional mixtures

We propose a Bayesian approach to joint source separation and restoration for astrophysical diffuse sources. We constitute a prior statistical model for the source images by using their gradient maps. We assume a t-distribution for the gradient maps in different directions, because it is able to fit both smooth and sparse data. A Monte Carlo technique, called Langevin sampler, is used to estimate the source images and all the model parameters are estimated by using deterministic techniques.

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arXiv2010

Correlated Component Analysis for diffuse component separation with error estimation on simulated Planck polarization data

We present a data analysis pipeline for CMB polarization experiments, running from multi-frequency maps to the power spectra. We focus mainly on component separation and, for the first time, we work out the covariance matrix accounting for errors associated to the separation itself. This allows us to propagate such errors and evaluate their contributions to the uncertainties on the final products.The pipeline is optimized for intermediate and small scales, but could be easily extended to lower multipoles. We exploit realistic simulations of the sky, tailored for the Planck mission. The component separation is achieved by exploiting the Correlated Component Analysis in the harmonic domain, that we demonstrate to be superior to the real-space application (Bonaldi et al. 2006). We present two techniques to estimate the uncertainties on the spectral parameters of the separated components. The component separation errors are then propagated by means of Monte Carlo simulations to obtain the corresponding contributions to uncertainties on the component maps and on the CMB power spectra. For the Planck polarization case they are found to be subdominant compared to noise.

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arXiv2008

Component separation methods for the Planck mission

The Planck satellite will map the full sky at nine frequencies from 30 to 857 GHz. The CMB intensity and polarization that are its prime targets are contaminated by foreground emission. The goal of this paper is to compare proposed methods for separating CMB from foregrounds based on their different spectral and spatial characteristics, and to separate the foregrounds into components of different physical origin. A component separation challenge has been organized, based on a set of realistically complex simulations of sky emission. Several methods including those based on internal template subtraction, maximum entropy method, parametric method, spatial and harmonic cross correlation methods, and independent component analysis have been tested. Different methods proved to be effective in cleaning the CMB maps from foreground contamination, in reconstructing maps of diffuse Galactic emissions, and in detecting point sources and thermal Sunyaev-Zeldovich signals. The power spectrum of the residuals is, on the largest scales, four orders of magnitude lower than that of the input Galaxy power spectrum at the foreground minimum. The CMB power spectrum was accurately recovered up to the sixth acoustic peak. The point source detection limit reaches 100 mJy, and about 2300 clusters are detected via the thermal SZ effect on two thirds of the sky. We have found that no single method performs best for all scientific objectives. We foresee that the final component separation pipeline for Planck will involve a combination of methods and iterations between processing steps targeted at different objectives such as diffuse component separation, spectral estimation and compact source extraction.

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arXiv2006

Estimating the spectral indices of correlated astrophysical foregrounds by a second-order statistical approach

We present the first tests of a new method, the Correlated Component Analysis (CCA) based on second-order statistics, to estimate the mixing matrix, a key ingredient to separate astrophysical foregrounds superimposed to the Cosmic Microwave Background (CMB). In the present application, the mixing matrix is parameterized in terms of the spectral indices of Galactic synchrotron and thermal dust emissions, while the free-free spectral index is prescribed by basic physics, and is thus assumed to be known. We consider simulated observations of the microwave sky with angular resolution and white stationary noise at the nominal levels for the PLANCK satellite, and realistic foreground emissions, with a position dependent synchrotron spectral index. We work with two sets of PLANCK frequency channels: the low frequency set, from 30 to 143 GHz, complemented with the Haslam 408 MHz map, and the high frequency set, from 217 to 545 GHz. The concentration of intense free-free emission on the Galactic plane introduces a steep dependence of the spectral index of the global Galactic emission with Galactic latitude, close to the Galactic equator. This feature makes difficult for the CCA to recover the synchrotron spectral index in this region, given the limited angular resolution of PLANCK, especially at low frequencies. A cut of a narrow strip around the Galactic equator (|b|<3 deg), however, allows us to overcome this problem. We show that, once this strip is removed, the CCA allows an effective foreground subtraction, with residual uncertainties inducing a minor contribution to errors on the recovered CMB power spectrum.

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arXiv2004

Extracting cosmic microwave background polarisation from satellite astrophysical maps

We present the application of the Fast Independent Component Analysis ({\ica}) technique for blind component separation to polarized astrophysical emission. We study how the Cosmic Microwave Background (CMB) polarized signal, consisting of $E$ and $B$ modes, can be extracted from maps affected by substantial contamination from diffuse Galactic foreground emission and instrumental noise. {We implement Monte Carlo chains varying the CMB and noise realizations in order to asses the average capabilities of the algorithm and their variance.} We perform the analysis of all sky maps simulated according to the {\sc Planck} satellite capabilities, modelling the sky signal as a superposition of the CMB and of the existing simulated polarization templates of Galactic synchrotron. Our results indicate that the angular power spectrum of CMB $E$-mode can be recovered on all scales up to $\ell\simeq 1000$, corresponding to the fourth acoustic oscillation, while the $B$-mode power spectrum can be detected, up to its turnover at $\ell\simeq 100$, if the ratio of tensor to scalar contributions to the temperature quadrupole exceeds 30%. The power spectrum of the cross correlation between total intensity and polarization, $TE$, can be recovered up to $\ell\simeq 1200$, corresponding to the seventh $TE$ acoustic oscillation.

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arXiv2004

Separation of correlated astrophysical sources using multiple-lag data covariance matrices

This paper deals with a source separation strategy based on second-order statistics, namely, on data covariance matrices estimated at several lags. In general, ``blind'' approaches to source separation do not assume any knowledge on the mixing operator; however, any prior information about the possible structure of the mixing operator can improve the solution. Unlike ICA blind separation approaches, where mutual independence between the sources is assumed, our method only needs to constrain second-order statistics, and is effective even if the original sources are significantly correlated. Besides the mixing matrix, our strategy is also capable to evaluate the source covariance functions at several lags. Moreover, once the mixing parameters have been identified, a simple deconvolution can be used to estimate the probability density functions of the source processes. To benchmark our algorithm, we used a database that simulates the one expected from the instruments that will operate onboard ESA's Planck Surveyor Satellite to measure the CMB anisotropies all over the celestial sphere. The assumption was made that the emission spectra of the galactic foregrounds can be parametrised, thus reducing the number of unknowns for system identification to the number of the foreground radiations. We performed separation in several sky patches, featuring different levels of galactic contamination to the CMB, and assuming several noise levels, including the ones derived from the Planck specifications.

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arXiv2001

All-sky astrophysical component separation with Fast Independent Component Analysis (FastICA)

We present a new, fast, algorithm for the separation of astrophysical components superposed in maps of the sky, based on the fast Independent Component Analysis technique (FastICA). It allows to recover both the spatial pattern and the frequency scalings of the emissions from statistically independent astrophysical processes, present along the line-of-sight, from multi-frequency observations. We apply FastICA to simulated observations of the microwave sky with angular resolution and instrumental noise at the mean nominal levels for the Planck satellite, containing the most important known diffuse signals: the Cosmic Microwave Background (CMB), Galactic synchrotron, dust and free-free emissions. A method for calibrating the reconstructed maps of each component at each frequency has been devised. The spatial pattern of all the components have been recovered on all scales probed by the instrument. In particular, the CMB angular power spectra is recovered at the percent level up to $\ell_{max}\simeq 2000$. Frequency scalings and normalization have been recovered with better than percent precision for all the components at frequencies and in sky regions where their signal-to-noise ratio exceeds 1.5; the error increases at ten percent level for signal-to-noise ratios about 1. Runs have been performed on a Pentium III 600 MHz computer; FastICA typically took a time of the order of 10 minutes for all-sky simulations with 3.5 arcminutes pixel size. We conclude that FastICA is an extremly promising technique for analyzing the maps that will be obtained by the forthcoming high resolution CMB experiments.

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arXiv2000

Neural networks and separation of Cosmic Microwave Background and astrophysical signals in sky maps

The Independent Component Analysis (ICA) algorithm is implemented as a neural network for separating signals of different origin in astrophysical sky maps. Due to its self-organizing capability, it works without prior assumptions on the signals, neither on their frequency scaling, nor on the signal maps themselves; instead, it learns directly from the input data how to separate the physical components, making use of their statistical independence. To test the capabilities of this approach, we apply the ICA algorithm on sky patches, taken from simulations and observations, at the microwave frequencies, that are going to be deeply explored in a few years on the whole sky, by the Microwave Anisotropy Probe (MAP) and by the {\sc Planck} Surveyor Satellite. The maps are at the frequencies of the Low Frequency Instrument (LFI) aboard the {\sc Planck} satellite (30, 44, 70 and 100 GHz), and contain simulated astrophysical radio sources, Cosmic Microwave Background (CMB) radiation, and Galactic diffuse emissions from thermal dust and synchrotron. We show that the ICA algorithm is able to recover each signal, with precision going from 10% for the Galactic components to percent for CMB; radio sources are almost completely recovered down to a flux limit corresponding to $0.7σ_{CMB}$, where $σ_{CMB}$ is the rms level of CMB fluctuations. The signal recovering possesses equal quality on all the scales larger then the pixel size. In addition, we show that the frequency scalings of the input signals can be partially inferred from the ICA outputs, at the percent precision for the dominant components, radio sources and CMB.

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arXiv1997

Large bent jets in the inner region of CSSs

The class of Compact Steep-spectrum Sources is dominated by double-lobed objects (70%). The remaining 30% are jet-dominated objects, with the jet brightened either by Doppler boosting or by interaction with the ambient media. We show that there is both observational and statistical evidence in favour of an interaction between jets and dense gas clouds. Such an interaction should happen in the Narrow Line Regions. The images of four CSSs observed by us with VLBI are also presented. These sources do show large bent jets in the first kpc from the nucleus.

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