Showing papers by "Nabila Aghanim published in 2019"

A Search for Warm/Hot Gas Filaments Between Pairs of SDSS Luminous Red Galaxies

Abstract: We search the Planck data for a thermal Sunyaev-Zel'dovich (tSZ) signal due to gas filaments between pairs of Luminous Red Galaxies (LRG's) taken from the Sloan Digital Sky Survey Data Release 12 (SDSS/DR12). We identify $\sim$260,000 LRG pairs in the DR12 catalog that lie within 6-10 $h^{-1} \mathrm{Mpc}$ of each other in tangential direction and within 6 $h^{-1} \mathrm{Mpc}$ in radial direction. We stack pairs by rotating and scaling the angular positions of each LRG so they lie on a common reference frame, then we subtract a circularly symmetric halo from each member of the pair to search for a residual signal between the pair members. We find a statistically significant (5.3$\sigma$) signal between LRG pairs in the stacked data with a magnitude $\Delta y = (1.31 \pm 0.25) \times 10^{-8}$. The uncertainty is estimated from two Monte Carlo null tests which also establish the reliability of our analysis. Assuming a simple, isothermal, cylindrical filament model of electron over-density with a radial density profile proportional to $r_c/r$ (as determined from simulations), where $r$ is the perpendicular distance from the cylinder axis and $r_c$ is the core radius of the density profile, we constrain the product of over-density and filament temperature to be $\delta_c \times (T_{\rm e}/10^7 \, {\rm K}) \times (r_c/0.5h^{-1} \, {\rm Mpc}) = 2.7 \pm 0.5$. To our knowledge, this is the first detection of filamentary gas at over-densities typical of cosmological large-scale structure. We compare our result to the BAHAMAS suite of cosmological hydrodynamic simulations (McCarthy et al. 2017) and find a slightly lower, but marginally consistent Comptonization excess, $\Delta y = (0.84 \pm 0.24) \times 10^{-8}$.

Mass bias evolution in tSZ cluster cosmology

Abstract: Galaxy clusters observed through the thermal Sunyaev–Zeldovich (tSZ) effect are a recent cosmological probe. The precision on the cosmological constraints is affected mainly by the current knowledge of cluster physics, which enters the analysis through the scaling relations. Here we aim to study one of the most important sources of systematic uncertainties, the mass bias, b . We have analysed the effects of a mass-redshift dependence, adopting a power-law parametrisation. We applied this parametrisation to the combination of tSZ number counts and power spectrum, finding a hint of redshift dependence that leads to a decreasing value of the mass bias for higher redshift. We tested the robustness of our results for different mass bias calibrations and a discrete redshift dependence. We find our results to be dependent on the clusters sample that we are considering, in particular obtaining an inverse (decreasing) redshift dependence when neglecting z ) = 0.62 ± 0.05. The corresponding value of b is too high with respect to weak lensing and numerical simulations estimations. Therefore we conclude that this mass-redshift parametrisation does not help in solving the remaining discrepancy between CMB and tSZ clusters observations.

Detection of intercluster gas in superclusters using the thermal Sunyaev-Zel'dovich effect

Abstract: Using a thermal Sunyaev–Zel’dovich (tSZ) signal, we search for hot gas in superclusters identified using the Sloan Digital Sky Survey Data Release 7 (SDSS/DR7) galaxies. We stack a Comptonization y map produced by the Planck Collaboration around the superclusters and detect the tSZ signal at a significance of 6.4σ . We further search for an intercluster component of gas in the superclusters. For this, we remove the intracluster gas in the superclusters by masking all galaxy groups/clusters detected by the Planck tSZ, ROSAT X-ray, and SDSS optical surveys down to a total mass of 1013 M ⊙ . We report the first detection of intercluster gas in superclusters with y = (3.5 ± 1.4) × 10−8 at a significance of 2.5σ . Assuming a simple isothermal and flat density distribution of intercluster gas over superclusters, the estimated baryon density is (Ωgas /Ωb )×(T e /8 × 106 K) = 0.067 ± 0.006 ± 0.025. This quantity is inversely proportional to the temperature, therefore taking values from simulations and observations, we find that the gas density in superclusters may account for 17–52% of missing baryons at low redshifts. A better understanding of the physical state of gas in the superclusters is required to accurately estimate the contribution of our measurements to missing baryons.

Star formation rates and stellar masses from machine learning

Abstract: Star-formation activity is a key property to probe the structure formation and hence characterise the large-scale structures of the universe. This information can be deduced from the star formation rate (SFR) and the stellar mass (M ⋆ ), both of which, but especially the SFR, are very complex to estimate. Determining these quantities from UV, optical, or IR luminosities relies on complex modeling and on priors on galaxy types. We propose a method based on the machine-learning algorithm Random Forest to estimate the SFR and the M ⋆ of galaxies at redshifts in the range 0.01 ⋆ from the SDSS MPA-JHU DR8 catalogue as outputs. We show that our algorithm can accurately estimate SFR and M ⋆ with scatters of σ SFR = 0.38 dex and σ M ⋆ = 0.16 dex for SFR and stellar mass, respectively, and that it is unbiased with respect to redshift or galaxy type. The full-sky coverage of the WISE satellite allows us to characterise the star-formation activity of all galaxies outside the Galactic mask with spectroscopic redshifts in the range 0.01 SFR = 0.42 dex and σ M ⋆ = 0.24 dex obtained in the redshift range 0.1 < 0.3.

Mass bias evolution in tSZ cluster cosmology.

Abstract: Galaxy clusters observed through the thermal Sunyaev-Zeldovich (tSZ) effect are a recent cosmological probe. The precision on the cosmological constraints is affected mainly by the current knowledge of cluster physics, which enters the analysis through the scaling relations. Here we aim to study one of the most important sources of systematic uncertainties, the mass bias, $b$. We have analysed the effects of a mass-redshift dependence, adopting a power-law parametrisation. We applied this parametrisation to the combination of tSZ number counts and power spectrum, finding a hint of redshift dependence that leads to a decreasing value of the mass bias for higher redshift. We tested the robustness of our results for different mass bias calibrations and a discrete redshift dependence. We find our results to be dependent on the clusters sample that we are considering, in particular obtaining an inverse (decreasing) redshift dependence when neglecting $z<0.2$ clusters. We analysed the effects of this parametrisation on the combination of cosmic microwave background (CMB) primary anisotropies and tSZ galaxy clusters. We find a preferred constant value of mass bias, having $(1-b) =0.62 \pm 0.05$. The corresponding value of $b$ is too high with respect to weak lensing and numerical simulations estimations. Therefore we conclude that this mass-redshift parametrisation does not help in solving the remaining discrepancy between CMB and tSZ clusters observations.

The COSMOS-UltraVISTA stellar-to-halo mass relationship: new insights on galaxy formation efficiency out to z ∼ 5

Abstract: Using precise galaxy stellar mass function measurements in the COSMOS field we determine the stellar-to-halo mass relationship (SHMR) using a parametric abundance matching technique. The unique combination of size and highly complete stellar mass estimates in COSMOS allows us to determine the SHMR over a wide range of halo masses from z ∼ 0.2 to 5. At z ∼ 0.2, the ratio of stellar-to-halo mass content peaks at a characteristic halo mass M_h = 10^(12) M⊙ and declines at higher and lower halo masses. This characteristic halo mass increases with redshift reaching M_h = 10^(12.5)M⊙ at z ∼ 2.3 and remaining flat up to z = 4. We considered the principal sources of uncertainty in our stellar mass measurements and also the variation in halo mass estimates in the literature. We show that our results are robust to these sources of uncertainty and explore likely explanation for differences between our results and those published in the literature. The steady increase in characteristic halo mass with redshift points to a scenario where cold gas inflows become progressively more important in driving star formation at high redshifts, but larger samples of massive galaxies are needed to rigorously test this hypothesis.

PACT I: Combining ACT and Planck data for optimal detection of tSZ signal

Abstract: We present the optimal reconstruction of the thermal Sunyaev-Zel'dovich (tSZ) effect signal based on the combination of a heterogeneous dataset consisting of ACT and Planck data, with different numbers of channels, angular resolutions and noise levels. We combine both datasets using two different approaches, a Matched Multi-Filter (MMF) technique and an optimised Internal Linear Combination (ILC). We show that when applying the MMF to the combination of ACT and Planck data, the size-flux degeneracy is reduced and the signal-to-noise of clusters detected with their SZ signal improves by up to a factor of three. In the case of the optimised ILC method, we show that the tSZ map is reconstructed with a resolution of $\sim 1.5$ arcmin. This is more than a factor two improvement compared with the Planck resolution, and with a very good control of noise, i.e. limited only by the intrinsic noise of the individual experiments. The combination of ACT and Planck data offers a unique opportunity to improve on the study of the pressure profiles and to study substructure in clusters through their tSZ.

T-ReX: a graph-based filament detection method.

Abstract: Numerical simulations and observations show that galaxies are not uniformly distributed in the universe but, rather, they are spread across a filamentary structure. In this large-scale pattern, highly dense regions are linked together by bridges and walls, all of them surrounded by vast, nearly-empty areas. While nodes of the network are widely studied in the literature, simulations indicate that half of the mass budget comes from a more diffuse part of the network, which is made up of filaments. In the context of recent and upcoming large galaxy surveys, it becomes essential that we identify and classify features of the Cosmic Web in an automatic way in order to study their physical properties and the impact of the cosmic environment on galaxies and their evolution. In this work, we propose a new approach for the automatic retrieval of the underlying filamentary structure from a 2D or 3D galaxy distribution using graph theory and the assumption that paths that link galaxies together with the minimum total length highlight the underlying distribution. To obtain a smoothed version of this topological prior, we embedded it in a Gaussian mixtures framework. In addition to a geometrical description of the pattern, a bootstrap-like estimate of these regularised minimum spanning trees allowed us to obtain a map characterising the frequency at which an area of the domain is crossed. Using the distribution of halos derived from numerical simulations, we show that the proposed method is able to recover the filamentary pattern in a 2D or 3D distribution of points with noise and outliers robustness with a few comprehensible parameters.

PACT - I. Combining ACT and Planck data for improved extraction of tSZ signal

Abstract: We present the optimal reconstruction of the thermal Sunyaev–Zel’dovich (tSZ) effect signal based on the combination of a heterogeneous dataset consisting of Atacama Cosmology Telescope (ACT) and Planck data, with different numbers of channels, angular resolutions, and noise levels. We combine both datasets using two different approaches, a matched multifilter (MMF) technique and an optimized internal linear combination (ILC). We show that when applying the MMF to the combination of ACT and Planck data, the size-flux degeneracy is reduced and the signal-to-noise of clusters detected with their Sunyaev–Zel’dovich (SZ) signal improves by up to a factor of three. In the case of the optimized ILC method, we show that the tSZ map is reconstructed with a resolution of ∼1.5 arcmin. This is more than a factor two improvement compared with the Planck resolution, and with a very good control of noise, meaning that it is limited only by the intrinsic noise of the individual experiments. The combination of ACT and Planck data offers a unique opportunity to improve on the study of the pressure profiles and to study substructure in clusters through their tSZ.

Optical Identifications of Galaxy Clusters Among Objects from the Second Planck Catalogue of Sunyaev–Zeldovich Sources

Abstract: We present the results of optical identifications and spectroscopic redshift measurements for galaxy clusters from the second Planck catalogue of Sunyaev-Zeldovich sources. We used the data of observations with the 1.5-m Russian-Turkish telescope (RTT150), the 1.6-m Sayan Observatory AZT-33IK telescope, the 3.5-m Calar Alto telescope, and the 6-m SAO RAS telescope (Bolshoi Teleskop Azimutalnyi, BTA). For the observations we selected Sunyaev-Zeldovich sources unidentified with galaxy clusters with known redshifts. The observations have been carried out for three years, as a result of which we obtained direct images in various filters for a set of galaxy clusters and spectra for the brightest red-sequence galaxies of these clusters. For 38 galaxy clusters we obtained spectroscopic redshift measurements.

Star formation rates and stellar masses from machine learning

Abstract: Star-formation activity is a key property to probe the structure formation and hence characterise the large-scale structures of the universe. This information can be deduced from the star formation rate (SFR) and the stellar mass (Mstar), both of which, but especially the SFR, are very complex to estimate. Determining these quantities from UV, optical, or IR luminosities relies on complex modeling and on priors on galaxy types. We propose a method based on the machine-learning algorithm Random Forest to estimate the SFR and the Mstar of galaxies at redshifts in the range 0.01

Optical validation and characterisation of Planck PSZ1 sources at the Canary Islands observatories: II. Second year of ITP13 observations

Abstract: Context. The second legacy catalog of Planck Sunyaev–Zeldovich (SZ) sources, hereafter PSZ2, provides the largest galaxy cluster sample selected by means of the SZ signature of the clusters in a full sky survey. In order to fully characterize this PSZ2 sample for cosmological studies, all the members should be validated and the physical properties of the clusters, including mass and redshift, should be derived. However, at the time of its publication, roughly 21% of the 1653 PSZ2 members had no known counterpart at other wavelengths.Aims. Here, we present the second and last year of observations of our optical follow-up program 128-MULTIPLE-16/15B (hereafter LP15), which has been developed with the aim of validating all the unidentified PSZ2 sources in the northern sky with declinations higher than −15° that have no correspondence in the first Planck catalog PSZ1. The description of the program and the first year of observations have been presented previously.Methods. The LP15 program was awarded 44 observing nights that were spread over two years with the Isaac Newton Telescope (INT), the Telescopio Nazionale Galileo (TNG), and the Gran Telescopio Canarias (GTC), all at Roque de los Muchachos Observatory (La Palma). Following the same method as described previously, we performed deep optical imaging for more than 200 sources with the INT and spectroscopy for almost 100 sources with the TNG and GTC at the end of the LP15 program. We adopted robust confirmation criteria based on velocity dispersion and richness estimates for the final classification of the new galaxy clusters as the optical counterparts of the PSZ2 detections.Results. Here, we present the observations of the second year of LP15, as well as the final results of the program. The full LP15 sample comprises 190 previously unidentified PSZ2 sources. Of these, 106 objects were studied before, while the remaining sample (except for 6 candidates) has been completed in the second year and is discussed here. In addition to the LP15 sample, we here study 42 additional PSZ2 objects that were originally validated as real clusters because they matched a WISE or PSZ1 counterpart, but they had no measured spectroscopic redshift. In total, we confirm the optical counterparts for 81 PSZ2 sources after the full LP15 program, 55 of them with new spectroscopic information. Forty of these 81 clusters are presented in this paper. After the LP15 observational program the purity of the PSZ2 catalog has increased from 76.7% originally to 86.2%. In addition, we study the possible reasons for false detection, and we report a clear correlation between the number of unconfirmed sources and galactic thermal dust emission.