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Showing papers by "Nabila Aghanim published in 2021"


Journal ArticleDOI
Nabila Aghanim1, Yashar Akrami2, Yashar Akrami3, Yashar Akrami4  +229 moreInstitutions (70)
TL;DR: Aghanim et al. as mentioned in this paper used the same data set to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.
Abstract: Author(s): Aghanim, N; Akrami, Y; Ashdown, M; Aumont, J; Baccigalupi, C; Ballardini, M; Banday, AJ; Barreiro, RB; Bartolo, N; Basak, S; Battye, R; Benabed, K; Bernard, JP; Bersanelli, M; Bielewicz, P; Bock, JJ; Bond, JR; Borrill, J; Bouchet, FR; Boulanger, F; Bucher, M; Burigana, C; Butler, RC; Calabrese, E; Cardoso, JF; Carron, J; Challinor, A; Chiang, HC; Chluba, J; Colombo, LPL; Combet, C; Contreras, D; Crill, BP; Cuttaia, F; De Bernardis, P; De Zotti, G; Delabrouille, J; Delouis, JM; DI Valentino, E; DIego, JM; Dore, O; Douspis, M; Ducout, A; Dupac, X; Dusini, S; Efstathiou, G; Elsner, F; Enslin, TA; Eriksen, HK; Fantaye, Y; Farhang, M; Fergusson, J; Fernandez-Cobos, R; Finelli, F; Forastieri, F; Frailis, M; Fraisse, AA; Franceschi, E; Frolov, A; Galeotta, S; Galli, S; Ganga, K; Genova-Santos, RT; Gerbino, M; Ghosh, T; Gonzalez-Nuevo, J; Gorski, KM; Gratton, S; Gruppuso, A; Gudmundsson, JE; Hamann, J; Handley, W; Hansen, FK; Herranz, D; Hildebrandt, SR; Hivon, E; Huang, Z; Jaffe, AH; Jones, WC; Karakci, A; Keihanen, E; Keskitalo, R; Kiiveri, K; Kim, J; Kisner, TS | Abstract: In the original version, the bounds given in Eqs. (87a) and (87b) on the contribution to the early-time optical depth, (15,30), contained a numerical error in deriving the 95th percentile from the Monte Carlo samples. The corrected 95% upper bounds are: τ(15,30) l 0:018 (lowE, flat τ(15, 30), FlexKnot), (1) τ(15, 30) l 0:023 (lowE, flat knot, FlexKnot): (2) These bounds are a factor of 3 larger than the originally reported results. Consequently, the new bounds do not significantly improve upon previous results from Planck data presented in Millea a Bouchet (2018) as was stated, but are instead comparable. Equations (1) and (2) give results that are now similar to those of Heinrich a Hu (2021), who used the same Planck 2018 data to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.

344 citations


Journal ArticleDOI
TL;DR: In this paper, the authors present forecasts for the joint analysis of $Euclid$ and CMB data on the cosmological parameters of the standard cosmology model and some of its extensions.
Abstract: The combination and cross-correlation of the upcoming $Euclid$ data with cosmic microwave background (CMB) measurements is a source of great expectation, since it will provide the largest lever arm of epochs ranging from recombination to structure formation across the entire past light cone. In this work, we present forecasts for the joint analysis of $Euclid$ and CMB data on the cosmological parameters of the standard cosmological model and some of its extensions. This work expands and complements the recently published forecasts based on $Euclid$-specific probes, i.e. galaxy clustering, weak lensing, and their cross-correlation. With some assumptions on the specifications of current and future CMB experiments, the predicted constraints are obtained both from a standard Fisher formalism and a posterior-fitting approach based on actual CMB data. Compared to a $Euclid$-only analysis, the addition of CMB data leads to a substantial impact on constraints for all cosmological parameters of the standard $\Lambda$-cold-dark-matter model, with improvements reaching up to a factor of 10. For the parameters of extended models, which include a redshift-dependent dark energy equation of state, non-zero curvature, and a phenomenological modification of gravity, improvements can be of order of 2$-$3, reaching higher than 10 in some cases. The results highlight the crucial importance for cosmological constraints of the combination and cross-correlation of $Euclid$ probes with CMB data.

32 citations


Journal ArticleDOI
TL;DR: In this paper, the authors show that filaments are essentially dominated by gas in the warm-hot intergalactic medium (WHIM), which accounts for more than 80% of the baryon budget at r ǫ∼∼ǫ 1.5 Mpc.
Abstract: We present the study of gas phases around cosmic-web filaments detected in the TNG300-1 hydro-dynamical simulation at redshift z = 0. We separate the gas into five different phases according to temperature and density. We show that filaments are essentially dominated by gas in the warm-hot intergalactic medium (WHIM), which accounts for more than 80% of the baryon budget at r ∼ 1 Mpc. Apart from WHIM gas, cores of filaments (r ≤ 1 Mpc) also host large contributions from other hotter and denser gas phases, whose fractions depend on the filament population. By building temperature and pressure profiles, we find that gas in filaments is isothermal up to r ∼ 1.5 Mpc, with average temperatures of T core = 4−13 × 105 K, depending on the large-scale environment. Pressure at cores of filaments is on average P core = 4−12 × 10−7 keV.cm−3 , which is ∼1000 times lower than pressure measured in observed clusters. We also estimate that the observed Sunyaev-Zel’dovich signal from cores of filaments should range between 0.5 , and these results are compared with recent observations. Our findings show that the state of the gas in filaments depends on the presence of haloes and on the large-scale environment.

25 citations


Journal ArticleDOI
TL;DR: In this paper, the authors investigate the effect of the dynamical state and the formation history on both the morphology and local connectivity of about 2400 groups and clusters of galaxies from the large hydrodynamical simulation IllustrisTNG at z = 0.
Abstract: Matter distribution around clusters is highly anisotropic because clusters are the nodes of the cosmic web. The shape of the clusters and the number of filaments to which they are connected, that is, their connectivity, is thought to reflect their level of anisotropic matter distribution and must in principle be related to their physical properties. We investigate the effect of the dynamical state and the formation history on both the morphology and local connectivity of about 2400 groups and clusters of galaxies from the large hydrodynamical simulation IllustrisTNG at z = 0. We find that the mass of groups and clusters mainly affects the geometry of the matter distribution: Massive halos are significantly more elliptical and are more strongly connected to the cosmic web than low-mass halos. Beyond the mass-driven effect, ellipticity and connectivity are correlated and are imprints of the growth rate of groups and clusters. Both anisotropy measures appear to trace different dynamical states, such that unrelaxed groups and clusters are more elliptical and more connected than relaxed ones. This relation between matter anisotropies and dynamical state is the sign of different accretion histories. Relaxed groups and clusters have mostly been formed a long time ago and are slowly accreting matter at the present time. They are highly spherical and weakly connected to their environment, mostly because they had enough time to relax and thus lost the connection with their preferential directions of accretion and merging. In contrast, late-formed unrelaxed objects are highly anisotropic with strong connectivities and ellipticities. These groups and clusters are in their formation phase and must be strongly affected by the infalling of materials from filaments.

18 citations


Journal ArticleDOI
TL;DR: In this paper, the influence of the dynamical state and the formation history on both the morphology and local connectivity of about 2400 groups and clusters of galaxies from the large hydrodynamical simulation IllustrisTNG at z = 0.
Abstract: Matter distribution around clusters is highly anisotropic from their being the nodes of the cosmic web. Clusters' shape and the number of filaments they are connected to, i.e., their connectivity, should reflect their level of anisotropic matter distribution and must be, in principle, related to their physical properties. We investigate the influence of the dynamical state and the formation history on both the morphology and local connectivity of about 2400 groups and clusters of galaxies from the large hydrodynamical simulation IllustrisTNG at z=0. We find that the mass of groups and clusters mainly influences the geometry of the matter distribution: massive halos are significantly more elliptical, and more connected to the cosmic web than low-mass ones. Beyond the mass-driven effect, ellipticity and connectivity are correlated and are imprints of the growth rate of groups and clusters. Both anisotropy measures appear to trace different dynamical states, such that unrelaxed groups and clusters are more elliptical and more connected than relaxed ones. This relation between matter anisotropies and dynamical state is the sign of different accretion histories. Relaxed groups and clusters are mostly formed long time ago, and slowly accreting matter at the present time. They are rather spherical and weakly connected to their environment, mostly because they had enough time to relax and, hence, lost the connection with their preferential directions of accretion and merging. In contrast, late-formed unrelaxed objects are highly anisotropic with large connectivities and ellipticities. These groups and clusters are in formation phase and must be strongly affected by the infalling of materials from filaments.

15 citations


Posted Content
TL;DR: In this article, the authors present a comprehensive study of the distribution of matter around different populations of filaments, using the IllustrisTNG simulation at z = 0.68 and find that baryons exactly follow the underlying DM distribution up to r~7 Mpc to the filament spines.
Abstract: We present a comprehensive study of the distribution of matter around different populations of filaments, using the IllustrisTNG simulation at z=0. We compute the dark matter (DM), gas, and stellar radial density profiles of filaments, and we characterise the distribution of the baryon fraction in these structures. We find that baryons exactly follow the underlying DM distribution only down to r~7 Mpc to the filament spines. At shorter distances (r<7 Mpc) the baryon fraction profile of filaments departs from the cosmic value Omega_b/Omega_m. While in the r~0.7 - 7 Mpc radial domain this departure is due to the radial accretion of WHIM gas towards the filament cores (creating an excess of baryons with respect to the cosmic fraction), the cores of filaments (r<0.7 Mpc) show instead a clear baryon depletion, quantified by a depletion factor of Y_b = 0.63-0.68. The analysis of the efficiency of AGN feedback events in filaments reveals that they are potentially powerful enough to eject gas outside of the gravitational potential wells of filaments. We show that the large-scale environment (i.e. denser vs less-dense, hotter vs colder regions) has a non-negligible effect on the absolute values of the DM, gas, and stellar densities around filaments. Nevertheless, the relative distribution of baryons with respect to the underlying DM density field is found to be independent from the filament population. Finally, we provide scaling relations between gas density, temperature, and pressure for the different populations of cosmic filaments. We compare these relations to those pertaining to clusters of galaxies, and find that these cosmic structures occupy separate regions of the density-temperature and density-pressure planes.

8 citations


Journal ArticleDOI
S. A. Stanford1, D. Masters2, Behnam Darvish2, Daniel Stern  +183 moreInstitutions (5)
TL;DR: The Complete Calibration of the Color-Redshift Relation (C3R2) survey as mentioned in this paper is obtaining spectroscopic redshifts in order to map the relation between galaxy color and redshift to a depth of i ∼ 24.5 (AB).
Abstract: The Complete Calibration of the Color–Redshift Relation (C3R2) survey is obtaining spectroscopic redshifts in order to map the relation between galaxy color and redshift to a depth of i ∼ 24.5 (AB). The primary goal is to enable sufficiently accurate photometric redshifts for Stage iv dark energy projects, particularly Euclid and the Nancy Grace Roman Space Telescope (Roman), which are designed to constrain cosmological parameters through weak lensing. We present 676 new high-confidence spectroscopic redshifts obtained by the C3R2 survey in the 2017B–2019B semesters using the DEIMOS, LRIS, and MOSFIRE multiobject spectrographs on the Keck telescopes. Combined with the 4454 redshifts previously published by this project, the C3R2 survey has now obtained and published 5130 high-quality galaxy spectra and redshifts. If we restrict consideration to only the 0.2 < zp < 2.6 range of interest for the Euclid cosmological goals, then with the current data release, C3R2 has increased the spectroscopic redshift coverage of the Euclid color space from 51% (as reported by Masters et al.) to the current 91%. Once completed and combined with extensive data collected by other spectroscopic surveys, C3R2 should provide the spectroscopic calibration set needed to enable photometric redshifts to meet the cosmology requirements for Euclid, and make significant headway toward solving the problem for Roman.

7 citations


Journal ArticleDOI
TL;DR: A framework exploiting the cascade of phase transitions occurring during a simulated annealing of the expectation-maximization algorithm to cluster datasets with multiscale structures to learn a principal graph from spatially structured datasets that can also exhibit many scales is presented.
Abstract: We present a framework exploiting the cascade of phase transitions occurring during a simulated annealing of the expectation-maximization algorithm to cluster datasets with multiscale structures. Using the weighted local covariance, we can extract, a posteriori and without any prior knowledge, information on the number of clusters at different scales together with their size. We also study the linear stability of the iterative scheme to derive the threshold at which the first transition occurs and show how to approximate the next ones. Finally, we combine simulated annealing together with recent developments of regularized Gaussian mixture models to learn a principal graph from spatially structured datasets that can also exhibit many scales.

7 citations


Journal ArticleDOI
TL;DR: In this article, the authors investigate the angular redshift fluctuations (ARF), which probe the information contained in the projected redshift distribution of galaxies, and show how ARF will provide complementary cosmological information compared to traditional angular galaxy clustering.
Abstract: In the context of next generation spectroscopic galaxy surveys, new observables of the distribution of matter are currently being developed. Among these we investigate the angular redshift fluctuations (ARF), which probe the information contained in the projected redshift distribution of galaxies. Relying on the Fisher formalism, we show how ARF will provide complementary cosmological information compared to traditional angular galaxy clustering. We test both the standard $\Lambda$CDM model and the wCDM extension. We find that the cosmological and galaxy bias parameters express different degeneracies when inferred from ARF or from angular galaxy clustering. As such, combining both observables breaks these degeneracies and greatly decreases the marginalised uncertainties, by a factor of at least two on most parameters for the $\Lambda$CDM and wCDM model. We find that the ARF combined with angular galaxy clustering are a great probe of dark energy by increasing the figure of merit of the $w_0$-$w_{\rm a}$ parameter set by a factor of more than 10 compared to angular galaxy clustering alone. Finally we compare ARF to the CMB lensing constraints on the galaxy bias parameters. We show that a joint analysis of ARF and angular galaxy clustering improves constraints by $\sim 40\%$ on galaxy bias compared to a joint analysis of angular galaxy clustering and CMB lensing.

6 citations


Journal ArticleDOI
TL;DR: In this paper, a new all-sky Compton parameter map (y-map) of the thermal Sunyaev-Zel'dovich (tSZ) effect from the 100 to 857 GHz frequency channel maps delivered within the Planck data release 4.
Abstract: We constructed a new all-sky Compton parameter map (y-map) of the thermal Sunyaev-Zel'dovich (tSZ) effect from the 100 to 857 GHz frequency channel maps delivered within the Planck data release 4. The improvements in terms of noise and systematic effects translated into a y-map with a noise level smaller by ~7% compared to the maps released in 2015, and with significantly reduced survey stripes. The produced 2020 y-map is also characterized by residual foreground contamination, mainly due to thermal dust emission at large angular scales and to CIB and extragalactic point sources at small angular scales. Using the new Planck data, we computed the tSZ angular power spectrum and found that the tSZ signal dominates the y-map in the multipole range, 60 < l < 600. We performed the cosmological analysis with the tSZ angular power spectrum and found S8=0.764+0.015-0.018(stat)+0.031-0.016(sys), including systematic uncertainties from a hydrostatic mass bias and pressure profile model. The S8 value may differ by +-0.016 depending on the hydrostatic mass bias model and by +0.021 depending on the pressure profile model used for the analysis. The obtained value is fully consistent with recent KiDS and DES weak-lensing observations. While our result is slightly lower than the Planck CMB one, it is consistent with the latter within 2 sigma.

6 citations


Journal ArticleDOI
TL;DR: This work builds and train a GAN and uses a trained GAN to construct a simple autoencoder (AE) as a first step towards building a predictive model, and shows that the AE manages to efficiently extract information from simulation images.
Abstract: Recently a type of neural networks called Generative Adversarial Networks (GANs) has been proposed as a solution for fast generation of simulation-like datasets, in an attempt to bypass heavy computations and expensive cosmological simulations to run in terms of time and computing power. In the present work, we build and train a GAN to look further into the strengths and limitations of such an approach. We then propose a novel method in which we make use of a trained GAN to construct a simple autoencoder (AE) as a first step towards building a predictive model. Both the GAN and AE are trained on images issued from two types of N-body simulations, namely 2D and 3D simulations. We find that the GAN successfully generates new images that are statistically consistent with the images it was trained on. We then show that the AE manages to efficiently extract information from simulation images, satisfyingly inferring the latent encoding of the GAN to generate an image with similar large scale structures.

Posted Content
S. A. Stanford1, D. Masters2, Behnam Darvish2, Daniel Stern  +183 moreInstitutions (5)
TL;DR: The Complete Calibration of the Color-Redshift Relation (C3R2) survey as discussed by the authors is obtaining spectroscopic redshifts in order to map the relation between galaxy color and redshift to a depth of i ~ 24.5.
Abstract: The Complete Calibration of the Color-Redshift Relation (C3R2) survey is obtaining spectroscopic redshifts in order to map the relation between galaxy color and redshift to a depth of i ~ 24.5 (AB). The primary goal is to enable sufficiently accurate photometric redshifts for Stage IV dark energy projects, particularly Euclid and the Roman Space Telescope, which are designed to constrain cosmological parameters through weak lensing. We present 676 new high-confidence spectroscopic redshifts obtained by the C3R2 survey in the 2017B-2019B semesters using the DEIMOS, LRIS, and MOSFIRE multi-object spectrographs on the Keck telescopes. Combined with the 4454 redshifts previously published by this project, the C3R2 survey has now obtained and published 5130 high-quality galaxy spectra and redshifts. If we restrict consideration to only the 0.2 < z(phot) < 2.6 range of interest for the Euclid cosmological goals, then with the current data release C3R2 has increased the spectroscopic redshift coverage of the Euclid color space from 51% (as reported by Masters et al. 2015) to the current 91%. Once completed and combined with extensive data collected by other spectroscopic surveys, C3R2 should provide the spectroscopic calibration set needed to enable photometric redshifts to meet the cosmology requirements for Euclid, and make significant headway toward solving the problem for Roman.

Journal ArticleDOI
TL;DR: In this paper, a thermal Sunyaev-Zel'dovich (tSZ) map was combined with a multi-frequency quality assessment of the sky pixels based on artificial neural networks with the aim being to detect tSZ sources from sub-millimeter observations by Planck.
Abstract: We present the first combination of a thermal Sunyaev-Zel’dovich (tSZ) map with a multi-frequency quality assessment of the sky pixels based on artificial neural networks with the aim being to detect tSZ sources from submillimeter observations of the sky by Planck . We present the construction of the resulting filtered and cleaned tSZ map, MILCANN. We show that this combination leads to a significant reduction of noise fluctuations and foreground residuals compared to standard reconstructions of tSZ maps. From the MILCANN map, we constructed a tSZ source catalog of about 4000 sources with a purity of 90%. Finally, we compare this catalog with ancillary catalogs and show that the galaxy-cluster candidates in our catalog are essentially low-mass (down to M 500 = 1014 M ⊙ ) high-redshift (up to z ≤ 1) galaxy cluster candidates.

Posted Content
TL;DR: In this paper, a new analysis of small scale CMB data by introducing the cosmological dependency of the foreground signals, focusing first on the thermal Sunyaev-Zel'dovich (tSZ) power spectrum, derived from the halo model, was proposed.
Abstract: We propose a new analysis of small scale CMB data by introducing the cosmological dependency of the foreground signals, focusing first on the thermal Sunyaev-Zel'dovich (tSZ) power spectrum, derived from the halo model. We analyse the latest observations by the South Pole Telescope (SPT) of the high-$\ell$ power (cross) spectra at 90, 150 and 220 GHz, as the sum of CMB and tSZ signals, both depending on cosmological parameters, and remaining contaminants. In order to perform faster analyses, we propose a new tSZ modelling based on machine learning algorithms (namely Random Forest). We show that the additional information contained in the tSZ power spectrum tightens constraints on cosmological and tSZ scaling relation parameters. We combine for the first time the Planck tSZ data with SPT high-$\ell$ to derive even stronger constraints. Finally, we show how the amplitude of the remaining kSZ power spectrum varies depending on the assumptions made on both tSZ and cosmological parameters.

Posted Content
TL;DR: In this paper, the authors present a preliminary concept based on previous space mission proposals, together with some sensitivity calculation results for the observation goals, showing that a 5-sigma measurement of the y-distortions is achievable.
Abstract: The BISOU (Balloon Interferometer for Spectral Observations of the Universe) project aims to study the viability and prospects of a balloon-borne spectrometer, pathfinder of a future space mission dedicated to the measurements of the CMB spectral distortions. We present here a preliminary concept based on previous space mission proposals, together with some sensitivity calculation results for the observation goals, showing that a 5-sigma measurement of the y-distortions is achievable.

Posted Content
TL;DR: In this article, a regularized version of Mixture Models is proposed to learn a principal graph from a distribution of $D$-dimensional data points, where the underlying manifold can be modeled as a graph structure acting like a topological prior for the Gaussian clusters turning the problem into a maximum a posteriori estimation.
Abstract: A regularized version of Mixture Models is proposed to learn a principal graph from a distribution of $D$-dimensional data points. In the particular case of manifold learning for ridge detection, we assume that the underlying manifold can be modeled as a graph structure acting like a topological prior for the Gaussian clusters turning the problem into a maximum a posteriori estimation. Parameters of the model are iteratively estimated through an Expectation-Maximization procedure making the learning of the structure computationally efficient with guaranteed convergence for any graph prior in a polynomial time. We also embed in the formalism a natural way to make the algorithm robust to outliers of the pattern and heteroscedasticity of the manifold sampling coherently with the graph structure. The method uses a graph prior given by the minimum spanning tree that we extend using random sub-samplings of the dataset to take into account cycles that can be observed in the spatial distribution.