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J. M. Casas

Publications and source records attributed to J. M. Casas.

At least 19 recordsLinked to original sources

Spatial Variations of Polarized Synchrotron Emission in the QUIJOTE MFI Data using Neural Networks

Polarized synchrotron emission from ultra-relativistic electrons spiraling the Galactic magnetic field has become one of the most relevant emissions in the Interstellar medium these last years due to the improvement in the quality of low-frequency observations. One of the recent experiments designed to explore this emission is the QUIJOTE experiment. We aim to study the spatial variations of the synchrotron emission in the QUIJOTE MFI data, by dividing the sky into physically separated regions. For such task, we firstly use a novel component separation method based on artificial neural networks to clean the synchrotron maps. After training the network with simulations, we fit both $EE$ and $BB$ spectra by assuming a power-law model. Then, we give estimations for the index $α_{S}$, the amplitude, and the ratio between $B$ and $E$ amplitudes. When analyzing the real data, we found a clear spatial variation of the synchrotron properties along the sky at 11 GHz, obtaining a steeper index in the Galactic plane of $α_{S}^{EE} = -3.1 \pm 0.3$ and $α_{S}^{BB} = -3.10 \pm 0.28$ and a flatter one at high Galactic latitudes of $α_{S}^{EE} = -3.05 \pm 0.16$ and $α_{S}^{B} = -2.98 \pm 0.23$. We found average values at all sky of $α_{S}^{EE} = -3.04 \pm 0.18$ and $α_{S}^{BB} = -3.00 \pm 0.26$. Furthermore, after obtaining an average value of $A_{S}^{EE} = 3.31 \pm 0.17$ $μK^{2}$ and $A_{S}^{BB} = 0.93 \pm 0.04$ $μK^{2}$, we estimate a ratio between $B$ and $E$ amplitudes of $A_{S}^{BB}/A_{S}^{EE} = 0.28 \pm 0.06$. Based on the results we conclude that, although neural networks seem to be valuable methods to apply on real ISM observations, combined analyses with Planck, WMAP and/or CBASS data are mandatory to reduce the contamination from QUIJOTE maps and then improve the accuracy of the estimations.

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Methodological refinement of the submillimeter galaxy cross-correlation function measurements and their uncertainty estimation

In this study, we aim to develop a new methodology to estimate the cross-correlation function and uncertainties and apply it to the analysis of magnification bias in galaxy surveys. We adopt a new methodological framework that uses a statistically rigorous approach to obtain more robust measurements for constraining cosmological parameters. This strategy involves using the full field area to count the number of different pairs for each field and combine them into a single estimation, reducing statistical uncertainty and accounting for the full information available in the data. The covariance matrix was estimated internally using an oversampled bootstrap method. We divided each field into at least five patches, that were defined automatically using a k-mean clustering algorithm. We investigate the robustness of the new methodology by comparing the results from a spectroscopic lens sample with those from a photometric lens sample, finding them to be compatible. We also analyse the cross-correlation function and auto-correlation function for individual fields in the three GAMA fields, comparing both samples. The G15 field was found to have a stronger signal compared to the other fields, suggesting that the stronger cross-correlation is produced by the rare combination of two excesses of large-scale structure in both the foreground and background samples. Our results demonstrate the robustness of the new methodology and suggest that the differences with respect to the mini-tile previously used approached may be due to physical properties of the samples themselves. The identified G15 anomalous signal warrants further investigation into its impact on cosmological parameters.

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Spectral Properties of Anomalous Microwave Emission in 144 Galactic Clouds

Anomalous Microwave Emission (AME) is a diffuse microwave component thought to arise from spinning dust grains, yet remains poorly understood. We analyze AME in 144 Galactic clouds by combining low-frequency maps from S-PASS (2.3 GHz), C-BASS (4.76 GHz), and QUIJOTE (10-20 GHz) with 21 ancillary maps. Using aperture photometry and parametric SED fitting via MCMC methods without informative priors, we measure AME emissivity, peak frequency, and spectral width. We achieve peak frequency constraints nearly three times tighter than previous work and identify 83 new AME sources. AME spectra are generally broader than predicted by spinning dust models for a single phase of the interstellar medium, suggesting either multiple spinning dust components along the line of sight or incomplete representation of the grain size distribution in current models. However, the narrowest observed widths match theoretical predictions, supporting the spinning dust hypothesis. The AME amplitude correlates most strongly with the thermal dust peak flux and radiance, showing $\sim30$% scatter and sublinear scaling, which suggests reduced AME efficiency in regions with brighter thermal dust emission. AME peak frequency increases with thermal dust temperature in a trend current theoretical models do not reproduce, indicating that spinning dust models must incorporate dust evolution and radiative transfer in a self-consistent framework where environmental parameters and grain properties are interdependent. PAH tracers correlate with AME emissivity, supporting a physical link to small dust grains. Finally, a log-Gaussian function provides a good empirical description of the AME spectrum across the sample, given current data quality and frequency coverage.

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QUIJOTE scientific results XIX. New constraints on the synchrotron spectral index using a semi-blind component separation method

We introduce a novel approach to estimate the spectral index, $β_s$, of polarised synchrotron emission, combining the moment expansion of CMB and the constrained-ILC. We reconstructed the maps of the first two synchrotron moments, combining multi-frequency data, and applied the `T-T plot' technique between two moment maps to estimate the synchrotron spectral index. This approach offers a new technique for mapping the foreground spectral parameters, complementing the model-based parametric component separation methods. Applying this technique, we derived a new constraint on the spectral index of polarised synchrotron emission using QUIJOTE MFI wide-survey 11 and 13 GHz data, Wilkinson Microwave Anisotropy Probe data at K and Ka bands, and Planck LFI 30 GHz data. In the Galactic plane and North Polar Spur regions, we obtained an inverse-variance-weighted mean synchrotron index of $β_s = -3.11$ with a standard deviation of $0.21$ due to intrinsic scatter, consistent with previous results based on parametric methods using the same dataset. We find that the inverse-variance-weighted mean spectral index, including both statistical and systematic uncertainties, is $β_s^{\rm plane} = -3.05 \pm 0.01$ in the Galactic plane and $β_s^{\rm high\text{-}lat} = -3.13 \pm 0.02$ at high latitudes, indicating a moderate steepening of the spectral index from low to high Galactic latitudes. Our analysis indicates that, within the current upper limit on the Anomalous Microwave Emission polarisation fraction, our results are not subject to any appreciable bias. Furthermore, we infer the spectral index over the entire QUIJOTE survey region, partitioning the sky into 21 patches. This technique can be further extended to constrain the synchrotron spectral curvature by reconstructing higher-order moments when better-quality data become available.

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Cosmic magnification on multi-catalogue Herschel submillimetre galaxies

{Submillimetre galaxies (SMGs) are excellent background sources for magnification-bias studies, but the limited sky coverage in the submillimetre (sub-mm) band constrains their statistical power. Beyond H-ATLAS, Herschel produced additional sub-mm catalogues, though not optimised for spatial statistical lensing analyses.} {Our goal is to refine cosmological constraints from SMG magnification bias by exploiting the full sub-mm sky surveyed by Herschel.} {We expanded the SMG sample by incorporating other Herschel catalogues overlapping SDSS spectroscopic lenses. Random catalogues were generated via kernel density estimation to compute cross-correlations, and Markov Chain Monte Carlo methods were applied to infer astrophysical and cosmological parameters for each catalogue and for the combined dataset.} {We report the first detection of magnification bias in SMGs beyond H-ATLAS, reinforcing the robustness of this observable. Individual Herschel catalogues yield reasonable central values for $Ω_m$ and $σ_8$, although with large uncertainties. The combined analysis, dominated by the more powerful H-ATLAS sample, gives results consistent with $Λ$CDM: $Ω_m = 0.30^{+0.05}_{-0.07}$, $σ_8 = 0.80 (+/- 0.07)$, and $h < 0.80$, in better agreement with \textit{Planck} 2018 than previous non-tomographic studies.} {SMGs are promising tracers for magnification bias, but the narrow sub-mm coverage remains a major limitation. Wider surveys optimised for lensing would enable cross-correlations on larger scales, yielding tighter cosmological constraints.}

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Recovering CMB polarization maps with neural networks: Performance in realistic simulations

Recovering the polarized cosmic microwave background (CMB) is essential for shedding light on the exponential expansion of the very early Universe, known as cosmic inflation. Achieving this goal requires not only improved instrumental sensitivity but also the development of robust and diverse data analysis techniques. In this work, we explore a novel component separation approach based on neural networks to reconstruct the Stokes $Q$ and $U$ polarization maps. To validate the method, we first test the network on realistic \textit{Planck} sky simulations, finding a mean absolute error of $0.1 \pm 0.3~μK^{2}$ for the $E$-mode and $-0.1 \pm 0.3~μK^{2}$ for the $B$-mode. We then apply the trained network to public \textit{Planck} observations, with results consistent with those obtained using the Commander method. Based on these findings, we conclude that neural network-based methods show potential as component separation techniques in polarization CMB experiments. However, substantial improvements and more comprehensive analyses are necessary before these methods can provide reliable high-precision cosmological estimates.

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Recovering the CMB signal with neural networks

Component separation is the process of extracting one or more emission sources in astrophysical maps. It is therefore crucial to develop models that can accurately clean the cosmic microwave background (CMB) in current and future experiments. In this work, we present a new methodology based on neural networks which operates on realistic temperature and polarization simulations. We assess its performance by comparing the power spectra of the output maps with those of the input maps and other emissions. For temperature, we obtain residuals of $20 \pm μK^{2}$. For polarization, we analyze the $E$ and $B$ modes, which are related to density (scalar) and primordial gravitational waves (tensorial) perturbations occurring in the first second of the Universe, obtaining residuals of $10^{-2} μK^{2}$ at $l>200$ and $10^{-2}$ and $10^{-3} μK^{2}$ for $E$ and $B$, respectively.

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Toward the measurement of neutrino masses: Performance of cosmic magnification with submillimeter galaxies

The phenomenon of magnification bias can induce a non-negligible angular correlation between two samples of galaxies with nonoverlapping redshift distributions. This signal is particularly clear when background submillimeter galaxies are used, and has been shown to constitute an independent cosmological probe. This work extends prior studies on the submillimeter galaxy magnification bias to the massive neutrino scenario, with the aim being to assess its sensitivity as a cosmological observable to the sum of neutrino masses. The measurements of the angular cross-correlation function between moderate redshift GAMA galaxies and high-redshift submillimeter H-ATLAS galaxies are fit to the weak lensing prediction down to the arcmin scale. The signal is interpreted under the halo model, which is modified to accommodate massive neutrinos. We discuss the impact of the choice of cosmological parametrization on the sensitivity to neutrino masses. The currently available data on the magnification bias affecting submillimeter galaxies are sensitive to neutrino masses when a cosmological parametrization in terms of the primordial amplitude of the power spectrum $(A_s$) is chosen over the local root mean square of smoothed linear density perturbations $(σ_8$). A clear upper limit on the sum of neutrino masses can be derived if the value of $A_s$ is either fixed or assigned a narrow Gaussian prior, a behavior that is robust against changes to the chosen value.

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Methodological refinement of the submillimeter galaxy magnification bias. II. Cosmological analysis with tomography

This paper is the third in a series on submillimeter galaxy magnification bias, focusing on the tomographic scenario. It refines the methodology used to constrain the halo occupation distribution model and cosmological parameters within a flat $Λ$CDM model, using updated data. The study aims to optimize CPU time, explore strategies for analyzing different redshift bins, and assess the impact of excluding the GAMA15 field. The tomographic approach involves dividing the redshift range into bins and analyzing cross-correlation measurements between submillimeter and foreground galaxies. The results show good agreement between the mean-redshift and full model cases, with an increase in the minimum mass of lenses at higher redshifts. The inferred cosmological parameters have narrower posterior distributions, indicating reduced measurement uncertainties compared to previous studies. Excluding the GAMA15 field reduces the cross-correlation signal, suggesting sample variance within the large-scale structure. Extending the redshift range improves robustness against sample variance and produces similar but tighter constraints. The study highlights the importance of sample variance and redshift binning in tomographic analyses, and suggests using additional wide-area fields and updated foreground catalogues for more effective implementation.

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Mass density profiles at kiloparsec scales using the sub-millimetre galaxies magnification bias

Gravitational lensing is a powerful tool for studying the distribution of mass in the Universe. Understanding the magnification bias effect in gravitational lensing and its impact on the flux of sub-millimetre galaxies (SMGs) is crucial for accurate interpretations of observational data. This study aims to investigate the magnification bias effect and analyse the mass density profiles of different types of foreground lenses, including quasi-stellar objects, galaxies, and clusters. The specific goals are to compare the lens types, assess the impact of angular resolution on the analysis, and determine the adequacy of theoretical mass density profiles in explaining the observed data, using four different theoretical mass density profiles. The magnification bias was estimated using the cross-correlation function between the positions of background SMGs and foreground lens samples. Stacking techniques were employed to enhance the signal at smaller angular separations, and the more precise positions from the WISE catalogue were utilised to improve positional accuracy. The cross-correlation measurements revealed distinctive central excess and outer power-law profiles, with a lack of signal in the intermediate region. The analysis of mass density profiles indicated limitations in the selected profiles' ability to explain the observed data, highlighting the need for additional considerations. The results suggest the presence of isolated galactic halos and the importance of considering environmental factors and close satellites in future investigations. The derived masses and best-fit parameters contribute to our understanding of lensing systems and provide constraints on the nature of central galaxies. Notably, the intriguing lack of signal around 10 arcsec challenges current understanding and calls for further quantitative analysis and confirmation of the observed feature.

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Isoclinism of Algebras With Bracket

We introduce the notion of isoclinism between central extensions in the category of algebras with bracket. We provide several equivalent conditions under which algebras with bracket are isoclinic. We also study the connection between isoclinism and the Schur multiplier of algebras with bracket. It is shown that for finite-dimensional central extensions of algebras with bracket with same dimension, the notion of isoclinism and isomorphism are equivalent. Furthermore, we indicate that all stem covers of an algebra with bracket are isoclinic.

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Constraining the polarisation flux density and angle of point sources by training a convolutional neural network

Constraining the polarisation properties of extragalactic point sources is a relevant task not only because they are one of the main contaminants for primordial cosmic microwave background B-mode detection if the tensor-to-scalar ratio is lower than r = 0.001, but also for a better understanding of the properties of radio-loud active galactic nuclei. We develop and train a machine learning model based on a convolutional neural network to learn how to estimate the polarisation flux density and angle of point sources embedded in cosmic microwave background images knowing only their positions. To train the neural network, we use realistic simulations of patches of area 32x32 pixels at the 217 GHz Planck channel with injected point sources at their centres. The patches also contain a realistic background composed by dust, the CMB and instrumental noise. Firstly, we study the comparison between true and estimated polarisation flux densities for P, Q and U. Secondly, we analyse the comparison between true and estimated polarisation angles. Finally, we study the performance of our model with real data and we compare our results against the PCCS2. We obtain that our model is reliable to constrain the polarisation flux above 80 mJy. For this limit, we obtain errors lower than 30%. Training the same network with Q and U, the reliability limit is above +-250 mJy for determining the polarisation angle of both Q and U sources with a 1sigma uncertainty of +-29deg and +-32deg for Q and U sources respectively. We obtain similar results to the PCCS2 for some sources, although we also find discrepancies in the 300-400 mJy flux density range with respect to the Planck catalogue. Based on these results, our model seems to be a promising tool to give estimations of the polarisation flux densities and angles of point sources above 80 mJy in any catalogue with practically null computational time.

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Quasi-stellar objects and galaxy mass density profiles derived using the submillimetre galaxies magnification bias

In this work, we want to exploit the magnification bias of the SMGs using two different foreground samples, quasi-stellar objects (QSOs) and galaxies. Our aim is to study and compare their mass density profiles and estimate their masses and concentrations. The background SMG sample consists of objects observed by \textit{Herschel} with 1.2<z<4.0. The foreground samples are QSOs and massive galaxies with spectroscopic redshifts between 0.2 and 1.0. The cross-correlation measurements are estimated with the Davis-Peebles estimator by stacking the SMG-QSO and SMG-galaxy pairs for the two analysed cases, respectively. This approach allows us to study the mass density profile from $\sim2$ to $\sim250$ arcsec. Moreover, the analysis is carried out by combining two of the most common theoretical mass density profiles in order to fit the cross-correlation measurements. The measurements are correctly fitted after splitting the available angular scales into an inner and an outer part using independent mass density profiles for each region. For the QSOs, we obtain masses and concentrations of $\log_{10}(M/M_{\odot})=13.51\pm0.04; C=6.85\pm0.34$ for the inner part and $\log_{10}(M/M_{\odot})=13.44\pm0.17; C=0.36\pm0.18$ for outer parts. For the galaxy sample are $\log_{10}(M/M_{\odot})=13.32\pm0.08; C=8.23\pm0.77$ and $\log_{10}(M/M_{\odot})=12.78\pm0.21; C=1.21\pm1.01$ for the inner and outer parts, respectively. In both samples, the inner part has an excess in the mass density profile and much higher concentration with respect to the outer part. We obtain similar values for the central mass with both samples, in agreement with those of galaxy clusters results. However, the estimated masses for the outer region and the concentrations of the inner region both vary with lens sample. This could be related to the probability of galactic interactions and/or the different evolutionary stages.

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CENN: A fully convolutional neural network for CMB recovery in realistic microwave sky simulations

Component separation is the process with which emission sources in astrophysical maps are generally extracted by taking multi-frequency information into account. It is crucial to develop more reliable methods for component separation for future CMB experiments. We aim to develop a new method based on fully convolutional neural networks called the Cosmic microwave background Extraction Neural Network (CENN) in order to extract the CMB signal in total intensity. The frequencies used are the Planck channels 143, 217 and 353 GHz. We validate the network at all sky, and at three latitude intervals: lat1=0^{\circ}<b<5^{\circ}, lat2=5^{\circ}<b<30^{\circ} and lat3=30^{\circ}<b<90^{\circ}, without using any Galactic or point source masks. For training, we make realistic simulations in the form of patches of area 256 pixels, which contain the CMB, Dust, CIB and PS emissions, Sunyaev-Zel'dovich effect and the instrumental noise. After validate the network, we compare the power spectrum from input and output maps. We analyse the power spectrum from the residuals at each latitude interval and at all sky and we study the performance of our model dealing with high contamination at small scales. We obtain a power spectrum with an error of 13{\pm}113 μK^2 for multipoles up to above 4000. For residuals, we obtain 700{\pm}60 μK^2 for lat1, 80{\pm}30 μK^2 for lat2 and 30{\pm}20 μK^2 for lat3. For all sky, we obtain 20{\pm}10 μK^2. We validate the network in a patch with strong contamination at small scales, obtaining an error of 50{\pm}120 μK^2 and residuals of 40{\pm}10 μK^2. Therefore, fully convolutional neural networks are promising methods to perform component separation in future CMB experiments. Particularly, CENN is reliable against different levels of contamination from Galactic and point source foregrounds at both large and small scales.

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Tomography-based observational measurements of the halo mass function via the submillimeter magnification bias

Aims. The main goal of this paper is to derive observational constraints on the halo mass fuction (HMF) by performing a tomographic analysis of the magnification bias signal on a sample of background submillimeter galaxies. The results can then be compared with those from a non-tomographic study. Methods. We measure the cross-correlation function between a sample of foreground GAMA galaxies with spectroscopic redshifts in the range $0.1 < z < 0.8$ (and divided up into four bins) and a sample of background submillimeter galaxies from H-ATLAS with photometric redshifts in the range $1.2 < z < 4.0$. We model the weak lensing signal within the halo model formalism and carry out a Markov chain Monte Carlo algorithm to obtain the posterior distribution of all HMF parameters, which we assume to follow the Sheth and Tormen (ST) three-parameter and two-parameter fits. Results. While the observational constraints on the HMF from the non-tomographic analysis are not stringent, there is a remarkable improvement in terms of uncertainty reduction when tomography is adopted. Moreover, with respect to the traditional ST triple of values from numerical simulations, the results from the three-parameter fit predict a higher number density of halos at masses below $10^{12}M_{\odot}/h$ at 95% credibility. The two-parameter fit yields even more restricting results, with a larger number density of halos below $10^{13}M_{\odot}/h$ and a lower one above $10^{14}M_{\odot}/h$, this time at more than 3$σ$ credibility. Our results are therefore in disagreement with the standard N-body values for the ST fit at 2$σ$ and 3$σ$, respectively.

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Multi-frequency point source detection with fully convolutional networks: Performance in realistic microwave sky simulations

Point Source (PS) detection is an important issue for future Cosmic Microwave Background (CMB) experiments since they are one of the main contaminants to the recovery of CMB signal at small scales. Improving its multifrequency detection would allow to take into account valuable information otherwise neglected when extracting PS using a channel-by-channel approach. We develop a method based on Neural Networks (NNs) to detect PS in multifrequency realistic simulations and compare its performance against one of the most popular methods, the matrix filters. The frequencies used are 143, 217 and 353 GHz and we impose a Galactic cut of 30 degrees. We produce simulations by adding contaminating signals to the PS maps as the CMB, the Cosmic Infrared Background, the Galactic thermal emission, the thermal Sunyaev-Zel'dovich effect and the instrumental noise. These simulations are used to train two NNs called Flat and Spectral MultiPoSeIDoN. The first one considers PS with a flat spectrum and the second one is more realistic because it takes into account the spectral behavior of the PS. Using a detection limit of 60 mJy, Flat MultiPoSeIDoN reachs the 90% of completeness level at 58 mJy and at 79, 71 and 60 for the spectral case at 143, 217 and 353 GHz respectively, while the matrix filters reach it at 84, 79 and 123 mJy. Using safer 4σ detection limit does not help to improve these results. In all cases, MultiPoSeIDoN obtain a much lower number of spurious sources than the filter. The NNs recover the flux density of the detections with a relative error of 10% above 100 mJy, while the filter above 150 mJy. Based on the results, NNs are the perfect candidates to substitute filters to detect multifrequency PS in future CMB experiments. Moreover, we have shown that a multifrequency approach can detect sources with higher accuracy than single-frequency approaches also based on NNs.

astro-ph.IM↗

Cosmology with the sub-millimetre galaxies magnification bias: Tomographic Analysis

As in Gonzalez-Nuevo et al. 2017 and Bonavera et al. 2019, the high-z sub-millimetre galaxies can be used as background sample for gravitational lensing studies thanks to their magnification bias. In particular, as in Bonavera et al. 2020 the magnification bias can be exploited in order to constrain the free parameters of a Halo Occupation Distribution (HOD) model and some of the main cosmological parameters. In this work the magnification bias has been evaluated as cosmological tool in a tomographic set up. The cross-correlation function (CCF) data have been used to jointly constrain the astrophysical parameters $M_{min}$, $M_{1}$ and $α$ in each one of the selected redshift bins and the $Ω_{M}$, $σ_{8}$, and $H_0$ cosmological ones ($Λ$CDM). Moreover, we explore the possible time evolution of the dark energy density introducing also the $ω_0, ω_a$ parameters in the joint analysis ($ω_0$CDM and $ω_0ω_a$CDM). The CCF has been measured between a foreground spectroscopic sample of GAMA galaxies that has been divided into four redshift bins (0.1-0.2, 0.2-0.3, 0.3-0.5 and 0.5-0.8) and a sample of H-ATLAS galaxies with photometric redshifts >1.2. The CCF is modelled using a description that depends on HOD and cosmological parameters that are estimated with MCMC in different cases. For the $Λ$CDM model, the analysis yields a maximum posterior value at 0.26 with $[0.17,0.41]$ 68\% C.I. for $Ω_M$ and at 0.87 with $[0.75,1]$ 68\% C.I. for $σ_8$. With our current results $H_0$ is not yet constrained. With the $ω_0$CDM model, the constraints on $Ω_M$ and $σ_8$ are similar, but we found a maximum posterior value for $ω_0$ at -1 with $[-1.56, -0.47]$ 68\% C.I. In the $ω_0ω_a$CDM model, the results are -1.09 with $[-1.72, -0.66]$ 68\% C.I. for $ω_0$ and -0.19 with $[-1.88, 1.48]$ 68\% C.I. for $ω_a$.

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Galaxy cluster mass density profile derived using the submillimetre galaxies magnification bias

In this work we want to study the average mass density profile of tens to hundreds of clusters of galaxies acting as lenses that produce a magnification bias on the SMGs, and to estimate their associated masses and concentrations for different richness ranges. The background sample is composed of SMGs observed by Herschel with 1.2<z<4.0 (mean redshift at ~2.3) while the foreground sample is made up of galaxy clusters extracted from the SDSS III with photometric redshifts of 0.05< z< 0.8 (mean redshift at ~0.38). Measurements are obtained by stacking the SMG--cluster pairs to estimate the cross-correlation function using the Davis-Peebles estimator. This methodology allows us to derive the mass density profile for a wide range of angular scales, ~2-250 arcsec or ~10-1300 kpc for z=0.38, with a high radial resolution. We find that It is impossible to fit the data with a single mass density profile at all scales. As for the outer part, the estimated average masses increase from $M_{200c}=5.8$ to $51.5\times 10^{13} M_\odot$ and the concentration parameter from C=0.74 to 1.74. In the small-scale regions, the obtained average masses fluctuate around $M_{200c}=3-4 \times 10^{13}M_\odot$ with average C~4. The total average masses are in perfect agreement with the M-R relationship estimated from the cluster catalogue. While the estimated average C values of the central galactic halos are in agreement with traditional M-C relationships, we find low concentrations for the outer part. Moreover, C decrease for lower R values, probably indicating that the group of galaxies cannot be considered to be relaxed systems. Finally, we notice a systematic lack of signal at the transition between the dominance of the cluster halo and the central galactic halo (~100 kpc). This feature is also present in previous studies using different catalogues and/or methodologies, but is never discussed.

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