arXiv subjects

E. Martinez-Gonzalez

Publications and source records attributed to E. Martinez-Gonzalez.

At least 73 records · Page 4Linked to original sources

arXiv2004

Detection of a non-Gaussian Spot in WMAP

An extremely cold and big spot in the WMAP 1-year data is analyzed. Our work is a continuation of a previous paper (Vielva et al. 2004) where non-Gaussianity was detected, with a method based on the Spherical Mexican Hat Wavelet (SMHW) technique. We study the spots at different thresholds on the SMHW coefficient maps, considering six estimators, namely number of maxima, number of minima, number of hot and cold spots, and number of pixels of the spots. At SMHW scales around 4 degrees (10 degrees on the sky), the data deviate from Gaussianity. The analysis is performed on all sky, the northern and southern hemispheres, and on four regions covering all the sky. A cold spot at (b = -57, l = 209) is found to be the source of this non-Gaussian signature. We compare the spots of our data with 10000 Gaussian simulations, and conclude that only around 0.2% of them present such a cold spot. Excluding this spot, the remaining map is compatible with Gaussianity and even the excess of kurtosis in Vielva et al. 2004, is found to be due exclusively to this spot. Finally, we study whether the spot causing the observed deviation from Gaussianity could be generated by systematics or foregrounds. None of them seem to be responsible for the non-Gaussian detection.

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arXiv2004

Detection of non-Gaussianity in the WMAP 1-year data using spherical wavelets

A non-Gaussian detection in the WMAP 1-year data is reported. The detection has been found in the combined Q-V-W map proposed by the WMAP team (Komatsu et al. 2003) after applying a wavelet technique based on the Spherical Mexican Hat Wavelet (SMHW). The skewness and the kurtosis of the SMHW coefficients are calculated at different scales. A non-Gaussian signal is detected at scales of the SMHW around 4 deg (size in the sky of around 10 deg). The right tail probability of the detection is approx. 0.4%. In addition, a study of Gaussianity is performed in each hemisphere. The northern hemisphere is compatible with Gaussianity, whereas the southern one deviates from Gaussianity with a right tail probability of approx. 0.1%. Systematics, foregrounds and uncertainties in the estimation of the cosmological parameters are carefully studied in order to identify the possible source of non-Gaussianity. The detected deviation from Gaussianity is not found to be caused by systematic effects: 1) each one of the Q, V and W receivers shows the same non-Gaussianity pattern, and 2) several combinations of the different receivers at each frequency band do not show this non-Gaussian pattern. Similarly, galactic foregrounds show a negligible contribution to the non-Gaussian detection: non-Gaussianity is detected in all the WMAP maps and no frequency dependence is observed. Moreover, the expected foreground contribution to the combined WMAP map was added to CMB Gaussian simulations showing a behaviour compatible with the Gaussian model. Influence of uncertainties in the CMB power spectrum estimation are also quantified. Hence, possible intrinsic temperature fluctuations (like secondary anisotropies and primordial features) can not be rejected as the source of this non-Gaussian detection.

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arXiv2004

Predictions on high frequency polarization properties of extragalactic radio sources and implications for CMB polarization measurements

We present a method to simulate the polarization properties of extragalactic radio sources at microwave frequencies. Polarization measurements of nearly 2x10^6 sources at 1.4 GHz are provided by the NVSS survey. Using this catalogue and the GB6 survey, we study the distribution of the polarization degree of both steep- and flat-spectrum sources. We find that the polarization degree is anti-correlated with the flux density for the former population, while no correlation is detected for the latter. The available high-frequency data are exploited to determine the frequency dependence of the distribution of polarization degrees. Using such information and the evolutionary model by Toffolatti et al. (1998), we estimate the polarization power spectrum of extragalactic radio sources at \geq 30 GHz and their contamination of CMB polarization maps. Two distinct methods to compute point-source polarization spectra are presented, extending and improving the one generally used in previous analyses. While extragalactic radio sources can significantly contaminate the CMB E-mode power spectrum only at low frequencies (<30 GHz), they can severely constrain the detectability of the CMB B-mode up to ~100 GHz.

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arXiv2003

Tests of Gaussianity

We review two powerful methods to test the Gaussianity of the cosmic microwave background (CMB): one based on the distribution of spherical wavelet coefficients and the other on smooth tests of goodness-of-fit. The spherical wavelet families proposed to analyse the CMB are the Haar and the Mexican Hat ones. The latter is preferred for detecting non-Gaussian homogeneous and isotropic primordial models containing some amount of skewness or kurtosis. Smooth tests of goodness-of-fit have recently been introduced in the field showing some interesting properties. We will discuss the smooth tests of goodness-of-fit developed by Rayner and Best for the univariate as well as for the multivariate analysis.

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arXiv2003

Goodness-of-fit tests of Gaussianity: constraints on the cumulants of the MAXIMA data

In this work, goodness-of-fit tests are adapted and applied to CMB maps to detect possible non-Gaussianity. We use Shapiro-Francia test and two Smooth goodness-of-fit tests: one developed by Rayner and Best and another one developed by Thomas and Pierce. The Smooth tests test small and smooth deviations of a prefixed probability function (in our case this is the univariate Gaussian). Also, the Rayner and Best test informs us of the kind of non-Gaussianity we have: excess of skewness, of kurtosis, and so on. These tests are optimal when the data are independent. We simulate and analyse non-Gaussian signals in order to study the power of these tests. These non-Gaussian simulations are constructed using the Edgeworth expansion, and assuming pixel-to-pixel independence. As an application, we test the Gaussianity of the MAXIMA data. Results indicate that the MAXIMA data are compatible with Gaussianity. Finally, the values of the skewness and kurtosis of MAXIMA data are constrained by |S| \le 0.035 and |K| \le 0.036 at the 99% confidence level.

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arXiv2003

Advanced pseudo-correlation radiometers for the Planck-LFI instrument

The LFI (Low Frequency Instrument) on board the ESA Planck satellite is constituted by an array of radiometric detectors actively cooled at 20 K in the 30-70 GHz frequency range in the focal plane of the Planck telescope. In this paper we present an overview of the LFI instrument, with a particular focus on the radiometer design. The adopted pseudo-correlation scheme uses a software balancing technique (with a tunable parameter called gain modulation factor) which is effective in reducing the radiometer susceptibility to amplifier instabilities also in presence of small non-idealities in the radiometric chain components, provided that the gain modulation factor is estimated with an accuracy of the order of 0.2%. These results have been recently confirmed by experimental laboratory measurements conducted on the LFI prototype radiometers at 30, 70 and 100 GHz.

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arXiv2003

CMB power spectrum estimation and map reconstruction with the Expectation - Maximization algorithm

We apply the iterative Expectation-Maximization algorithm (EM) to estimate the power spectrum of the CMB from multifrequency microwave maps. In addition, we are also able to provide a reconstruction of the CMB map. By assuming that the combined emission of the foregrounds plus the instrumental noise is Gaussian distributed in Fourier space, we have simplified the EM procedure finding an analytical expression for the maximization step. By using the simplified expression the CPU time can be greatly reduced. We test the stability of our power spectrum estimator with realistic simulations of Planck data, including point sources and allowing for spatial variation of the frequency dependence of the Galactic emissions. Without prior information about any of the components, our new estimator can recover the CMB power spectrum up to scales l~1500 with less than 10% error. This result is significantly improved if the brightest point sources are removed before applying our estimator. In this way, the CMB power spectrum can be recovered up to l~1700 with 10% error and up to l~2100 with 50% error. This result is very close to the one that would be obtained in the ideal case of only CMB plus white noise, for which all our assumptions are satisfied. Moreover, the EM algorithm also provides an straightforward mechanism to reconstruct the CMB map. The recovered cosmological signal shows a high degree of correlation (r = 0.98) with the input map and low residuals.

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arXiv2003

Goodness-of-Fit Tests to study the Gaussianity of the MAXIMA data

Goodness-of-Fit tests, including Smooth ones, are introduced and applied to detect non-Gaussianity in Cosmic Microwave Background simulations. We study the power of three different tests: the Shapiro-Francia test (1972), the uncategorised smooth test developed by Rayner and Best(1990) and the Neyman's Smooth Goodness-of-fit test for composite hypotheses (Thomas and Pierce 1979). The Smooth Goodness-of-Fit tests are designed to be sensitive to the presence of ``smooth'' deviations from a given distribution. We study the power of these tests based on the discrimination between Gaussian and non-Gaussian simulations. Non-Gaussian cases are simulated using the Edgeworth expansion and assuming pixel-to-pixel independence. Results show these tests behave similarly and are more powerful than tests directly based on cumulants of order 3, 4, 5 and 6. We have applied these tests to the released MAXIMA data. The applied tests are built to be powerful against detecting deviations from univariate Gaussianity. The Cholesky matrix corresponding to signal (based on an assumed cosmological model) plus noise is used to decorrelate the observations previous to the analysis. Results indicate that the MAXIMA data are compatible with Gaussianity.

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arXiv2003

Point Source Detection using the Spherical Mexican Hat Wavelet on simulated all-sky Planck maps

We present an estimation of the point source (PS) catalogue that could be extracted from the forthcoming ESA Planck mission data. We have applied the Spherical Mexican Hat Wavelet (SMHW) to simulated all-sky maps that include CMB, Galactic emission (thermal dust, free-free and synchrotron), thermal Sunyaev-Zel'dovich effect and PS emission, as well as instrumental white noise. This work is an extension of the one presented in Vielva et al. (2001a). We have developed an algorithm focused on a fast local optimal scale determination, that is crucial to achieve a PS catalogue with a large number of detections and a low flux limit. An important effort has been also done to reduce the CPU time processor for spherical harmonic transformation, in order to perform the PS detection in a reasonable time. The presented algorithm is able to provide a PS catalogue above fluxes: 0.48 Jy (857 GHz), 0.49 Jy (545 GHz), 0.18 Jy (353 GHz), 0.12 Jy (217 GHz), 0.13 Jy (143 GHz), 0.16 Jy (100 GHz HFI), 0.19 Jy (100 GHz LFI), 0.24 Jy (70 GHz), 0.25 Jy (44 GHz) and 0.23 Jy (30 GHz). We detect around 27700 PS at the highest frequency Planck channel and 2900 at the 30 GHz one. The completeness level are: 70% (857 GHz), 75% (545 GHz), 70% (353 GHz), 80% (217 GHz), 90% (143 GHz), 85% (100 GHz HFI), 80% (100 GHz LFI), 80% (70 GHz), 85% (44 GHz) and 80% (30 GHz). In addition, we can find several PS at different channels, allowing the study of the spectral behaviour and the physical processes acting on them. We also present the basic procedure to apply the method in maps convolved with asymmetric beams. The algorithm takes ~ 72 hours for the most CPU time demanding channel (857 GHz) in a Compaq HPC320 (Alpha EV68 1 GHz processor) and requires 4 GB of RAM memory.

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arXiv2003

Comparing filters for the detection of point sources

This paper considers filters (the Mexican hat wavelet, the matched and the scale-adaptive filters) that optimize the detection/separation of point sources on a background. We make a one-dimensional treatment, we assume that the sources have a Gaussian profile, i. e. $τ(x) = e^{- x^2/2R^2}$, and a background modelled by an homogeneous and isotropic Gaussian random field, characterised by a power spectrum $P(q)\propto q^{-γ}, γ\geq 0$. Local peak detection is used after filtering. Then, the Neyman-Pearson criterion is used to define the confidence level for detections and a comparison of filters is done based on the number of spurious and true detections. We have performed numerical simulations to test theoretical ideas and conclude that the results of the simulations agree with the analytical results.

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arXiv2002

COBE-DMR constraints on the nonlinear coupling parameter: a wavelet based method

Nonlinearity introduced in slow-roll inflation will produce weakly non-Gaussian CMB temperature fluctuations. We have simulated non-Gaussian large scale CMB maps (including COBE-DMR constraints) introducing an additional quadratic term in the gravitational potential.The amount of nonlinearity being controlled by the so called nonlinear coupling parameter f_{nl}. An analysis based on the Spherical Mexican Hat wavelet was applied to these and to the COBE-DMR maps. Skewness values obtained at several scales were combined into a Fisher discriminant. Comparison of the Fisher discriminant distributions obtained for different nonlinear coupling parameters with the COBE-DMR values, sets a constraint of abs(f_{nl})<1100 at the 68% confidence level. This new constraint being tighter than the one previously obtained by using the bispectrum by Komatsu et al. (2002).

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arXiv2002

A Bayesian non-parametric method to detect clusters in Planck data

We show how one may expect a significant number of SZ detections in future Planck data without any of the typical assumptions needed in present component separation methods, such as about the power spectrum or the frequency dependence of any of the components, circular symmetry or a typical scale for the clusters. We reduce the background by subtracting an estimate of the point sources, dust and CMB. The final SZE map is estimated in Fourier space. The catalogue of returned clusters is complete above flux 200 mJy (353 GHz) while the lowest flux reached by our method is about 70 mJy (353 GHz). We predict a large number of detections (about 9000) in 4/5 of the sky. This large number of SZ detections will allow a robust and consistent analysis of the evolution of the cluster population with redshift and will have important implications for determining the best cosmological model.

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arXiv2002

The performance of spherical wavelets to detect non-Gaussianity in the CMB sky

We investigate the performance of spherical wavelets in discriminating between standard inflationary models (Gaussian) and non-Gaussian models. For the later we consider small perturbations of the Gaussian model in which an artificially specified skewness or kurtosis is introduced through the Edgeworth expansion. By combining all the information present in all the wavelet scales with the Fisher discriminant, we find that the spherical Mexican Hat wavelets are clearly superior to the spherical Haar wavelets. The former can detect levels of the skewness and kurtosis of ~1% for 33' resolution, an order of magnitude smaller than the later. Also, as expected, both wavelets are better for discriminating between the models than the direct consideration of moments of the temperature maps. The introduction of instrumental white noise in the maps, S/N=1, does not change the main results of this paper.

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arXiv2002

Cosmology with GTC. A combined mm-optical galaxy cluster survey

The CMB Planck satellite (ESA) will provide a catalogue of nearly 30000 galaxy clusters (Sunyaev-Zel'dovich effect) between redshift 0 and approx. 2-3 (depending on the cosmological model). This hughe catalogue of clusters will allow detailed studies of the evolution of the cluster population with redshift which will constrain the cosmological model. The identification of the high redshift clusters should be done with a large telescope (like GTC) since Planck data alone will not provide any clue about the redshift of the clusters. In this work we show that an optical follow up of only 300 clusters (randomly selected from the Planck catalogue) is needed in order to distinguish models with or without a cosmological constant.

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arXiv2002

Filtering techniques for the detection of Sunyaev-Zel'dovich clusters in multifrequency CMB maps

The problem of detecting Sunyaev-Zel'dovich (SZ) clusters in multifrequency CMB observations is investigated using a number of filtering techniques. A multifilter approach is introduced, which optimizes the detection of SZ clusters on microwave maps. An alternative method is also investigated, in which maps at different frequencies are combined in an optimal manner so that existing filtering techniques can be applied to the single combined map. The SZ profiles are approximated by the circularly-symmetric template $τ(x) = [1 +(x/r_c)^2]^{-λ}$, with $λ\simeq \tfrac{1}{2}$ and $x\equiv |\vec{x}|$, where the core radius $r_c$ and the overall amplitude of the effect are not fixed a priori, but are determined from the data. The background emission is modelled by a homogeneous and isotropic random field, characterized by a cross-power spectrum $P_{ν_1 ν_2}(q)$ with $q\equiv |\vec{q}|$. The filtering methods are illustrated by application to simulated Planck observations of a $12.8^\circ \times 12.8^\circ$ patch of sky in 10 frequency channels. Our simulations suggest that the Planck instrument should detect $\approx 10000$ SZ clusters in 2/3 of the sky. Moreover, we find the catalogue to be complete for fluxes $S > 170$ mJy at 300 GHz.

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arXiv2002

Scale-Adaptive filters for the detection/separation of compact sources

This paper presents scale-adaptive filters that optimize the detection/separation of compact sources on a background. We assume that the sources have a multiquadric profile, i. e. $τ(x) = {[1 + {(x/r_c)}^2]}^{-λ}, λ\geq {1/2}, x\equiv |\vec{x}|$, and a background modeled by a homogeneous and isotropic random field, characterized by a power spectrum $P(q)\propto q^{-γ}, γ\geq 0, q\equiv |\vec{q}|$. We make an n-dimensional treatment but consider two interesting astrophysical applications related to clusters of galaxies (Sunyaev-Zel'dovich effect and X-ray emission).

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arXiv2002

Point source detection and extraction from simulated Planck TOD using optimal adaptive filters

Wavelet-related techniques have proven useful in the processing and analysis of one and two dimensional data sets (spectra in the former case, images in the latter). In this work we apply adaptive filters, introduced in a previous work (Sanz et al. 2001), to optimize the detection and extraction of point sources from a one-dimensional array of time-ordered data such as the one that will be produced by the future 30 GHz LFI28 channel of the ESA Planck mission. At a $4σ$ detection level 224 sources over a flux of 0.88 Jy are detected with a mean relative error (in absolute value) of 21% and a systematic bias of -7.7%. The position of the sources in the sky is determined with errors inferior to the size of the pixel. The catalogue of detected sources is complete at fluxes $\geq$ 4.3 Jy. The number of spurious detections is less than a 10% of the true detections. We compared the results with the ones obtained by filtering with a Gaussian filter and a Mexican Hat Wavelet of width equal to the scale of the sources. The adaptive filter outperforms the other filters in all considered cases. We conclude that optimal adaptive filters are well suited to detect and extract sources with a given profile embedded in a background of known statistical properties. In the Planck case, they could be useful to obtain a real-time preliminary catalogue of extragalactic sources, which would have a great scientific interest, e. g. for follow-up observations.

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arXiv2001

Optimal detection of sources on a homogeneous and isotropic background

This paper introduces the use of pseudo-filters that optimize the detection/extraction of sources on a background. We assume as a first approach that such sources are described by a spherical (central) profile and that the background is represented by a homogeneous and isotropic random field. We make an n-dimensional treatment making emphasis in astrophysical applications for spectra, images and volumes, for the cases of exponential and Gaussian source profiles and scale-free power spectra to represent the background.

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