We report the first statistical detection of X-ray emission from cosmic web filaments in ROSAT data. We selected 15 165 filaments at 0.2 <
z
< 0.6 ranging from 30 Mpc to 100 Mpc in length, ...identified in the Sloan Digital Sky Survey survey. We stacked the X-ray count-rate maps from ROSAT around the filaments, excluding resolved galaxy groups and clusters above the mass of ∼3 × 10
13
M
⊙
as well as the detected X-ray point sources from the ROSAT,
Chandra
, and
XMM-Newton
observations. The stacked signal results in the detection of the X-ray emission from the cosmic filaments at a significance of 4.2
σ
in the energy band of 0.56−1.21 keV. The signal is interpreted, assuming the Astrophysical Plasma Emission Code model, as an emission from the hot gas in the filament-core regions with an average gas temperature of 0.9
−0.6
+1.0
keV and a gas overdensity of
δ
∼ 30 at the center of the filaments. Furthermore, we show that stacking the SRG/eROSITA data for ∼2000 filaments only would lead to a ≳5
σ
detection of their X-ray signal, even with an average gas temperature as low as ∼0.3 keV.
We studied physical properties of matter in 24 544 filaments ranging from 30 to 100 Mpc in length, identified in the Sloan Digital Sky Survey. We stacked the Comptonization
y
map produced by the ...Planck Collaboration around the filaments, excluding the resolved galaxy groups and clusters above a mass of ∼3 × 10
13
M
⊙
. We detected the thermal Sunyaev-Zel’dovich signal for the first time at a significance of 4.4
σ
in filamentary structures on such a large scale. We also stacked the
Planck
cosmic microwave background lensing convergence map in the same manner and detected the lensing signal at a significance of 8.1
σ
. To estimate physical properties of the matter, we considered an isothermal cylindrical filament model with a density distribution following a
β
-model (
β
= 2/3). Assuming that the gas distribution follows the dark matter distribution, we estimate that the central gas and matter overdensity
δ
and gas temperature
T
e
are
δ
= 19.0
−12.1
+27.3
and
T
e
= 1.4
−0.4
+0.4
× 10
6
K, which results in a measured baryon fraction of 0.080
−0.051
+0.116
× Ω
b
.
The gas mass fraction in galaxy clusters is a convenient probe to use in cosmological studies, as it can help derive constraints on a range of cosmological parameters. This quantity is, however, ...subject to various effects from the baryonic physics inside galaxy clusters, which may bias the obtained cosmological constraints. Among different aspects of the baryonic physics at work, in this paper we focus on the impact of the hydrostatic equilibrium assumption. We analyzed the hydrostatic mass bias
B
, constraining a possible mass and redshift evolution for this quantity and its impact on the cosmological constraints. To that end, we considered cluster observations of the
Planck
-ESZ sample and evaluated the gas mass fraction using X-ray counterpart observations. We show a degeneracy between the redshift dependence of the bias and cosmological parameters. In particular we find evidence at 3.8
σ
for a redshift dependence of the bias when assuming a
Planck
prior on Ω
m
. On the other hand, assuming a constant mass bias would lead to the extremely large value of Ω
m
> 0.860. We show, however, that our results are entirely dependent on the cluster sample under consideration. In particular, the mass and redshift trends that we find for the lowest mass-redshift and highest mass-redshift clusters of our sample are not compatible. In addition, we show that assuming self-similarity in our study can impact the results on the evolution of the bias, especially with regard to the mass evolution. Nevertheless, in all the analyses, we find a value for the amplitude of the bias that is consistent with
B
∼ 0.8, as expected from hydrodynamical simulations and local measurements. However, this result is still in tension with the low value of
B
∼ 0.6 derived from the combination of cosmic microwave background primary anisotropies with cluster number counts.
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 < z < 0.3, independent of their type. The machine-learning algorithm takes as inputs the redshift, WISE luminosities, and WISE colours in near-IR, and is trained on spectra-extracted SFR and M⋆ from the SDSS MPA-JHU DR8 catalogue as outputs. We show that our algorithm can accurately estimate SFR and M⋆ with scatters of σSFR = 0.38 dex and σM⋆ = 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 < z < 0.3. The method can also be applied to photometric-redshift catalogues, with best scatters of σSFR = 0.42 dex and σM⋆ = 0.24 dex obtained in the redshift range 0.1 < z < 0.3.
Galaxy cluster number counts are an important probe with which to constrain cosmological parameters. One of the main ingredients of the analysis, along with accurate estimates of cluster masses, is ...the selection function, and in particular the completeness associated with the cluster sample under consideration. Incorrectly characterising this function can lead to biases in cosmological constraints. In this work, we want to study the completeness of the Planck cluster catalogue, estimating the probability of cluster detection in a realistic setting using hydrodynamical simulations. In particular, we probe the case in which the cluster model assumed in the detection method differs from the shapes and profiles of true galaxy clusters. We created around 9000 images of the Sunyaev–Zel’dovich effect from galaxy clusters from the IllustrisTNG simulation, and used a Monte Carlo injection method to estimate the completeness function. We studied the impact of having different cluster pressure profiles and complex cluster morphologies on the detection process. We find that the cluster profile has a significant effect on completeness, with clusters with steeper profiles producing a higher completeness than ones with flatter profiles. We also show that cluster morphology has a small impact on completeness, finding that elliptical clusters have a slightly lower probability of detection with respect to spherically symmetric ones. Finally, we investigate the impact of a different completeness function on a cosmological analysis with cluster number counts, showing a shift in the constraints on Ω m and σ 8 that lies in the same direction as the shift driven by the mass bias.
The role played by large-scale structures in galaxy evolution is not very well understood yet. In this study, we investigated properties of galaxies in the range 0.1 <
z
< 0.3 from a value-added ...version of the WISExSCOS catalogue around cosmic filaments detected with DisPerSE. We fitted a profile of galaxy over-density around cosmic filaments and found a typical radius of
r
m
= 7.5 ± 0.2 Mpc. We measured an excess of passive galaxies near to the spine of the filament that was higher than the excess of transitioning and active galaxies. We also detected star formation rates (SFR) and stellar mass (
M
⋆
) gradients pointing towards the spine of the filament. We investigated this result and found an
M
⋆
gradient for each type of galaxy, that is active, transitioning, and passive; we found a positive SFR gradient for passive galaxies. We also linked the galaxy properties and gas content in the cosmic web. To do so, we investigated the quiescent fraction
f
Q
profile of galaxies around the cosmic filaments. Based on recent studies about the effect of the gas and the cosmic web on galaxy properties, we modelled
f
Q
with a
β
model of gas pressure. The slope obtained in this work,
β
= 0.54 ± 0.18, is compatible with the scenario of projected isothermal gas in hydrostatic equilibrium (
β
= 2/3) and with the profiles of gas fitted in Sunyaev-Zel’dovich data from the
Planck
satellite.
We discuss constraints on cosmic reionisation and their implications on a cosmic star formation rate (SFR) density ρSFR model; we study the influence of key-parameters such as the clumping factor of ...ionised hydrogen in the intergalactic medium (IGM) CH II and the fraction of ionising photons escaping star-forming galaxies to reionise the IGM fesc. Our analysis has used SFR history data from luminosity functions, assuming that star-forming galaxies were sufficient to lead the reionisation process at high redshift. We have added two other sets of constraints: measurements of the IGM ionised fraction and the most recent result from Planck Satellite about the integrated Thomson optical depth of the cosmic microwave background τPlanck. Our analysis shows that a reionisation beginning as early as z ≥ 14 and persisting until z ~ 6 is a likely scenario. We also considered various possibilities for the evolution of fesc and CH II with redshift, and confront them with observational data cited above. We conclude that, if the model of a constant clumping factor is chosen, the fiducial value of three is consistent with observations; even if a redshift-dependent model is considered, the resulting optical depth is strongly correlated with CH II mean value at z > 7, an additional argument in favour of the use of a constant clumping factor. Similarly, a constant value of the escape fraction is favoured over a redshift-dependent model. When added as a fit parameter, we find fesc = 0.19 ± 0.04. However, this result strongly depends on the choice of magnitude limit in the derivation of ρSFR. Our fiducial analysis considers faint galaxies (Mlim = −13) and the result is a well constrained escape fraction of about 0.2, but when Mlim = −17, the number of galaxies available to reionise the IGM is not sufficient to match the observations, so that much higher values of fesc, approaching 70%, are needed.
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 Mh = 1012M⊙ and declines at higher and lower halo masses. This characteristic halo mass increases with redshift reaching Mh = 1012.5M⊙ 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.
We use a new approach based on self-supervised deep learning networks originally applied to transparency separation in order to simultaneously extract the components of the extragalactic ...submillimeter sky, namely the cosmic microwave background (CMB), the cosmic infrared background (CIB), and the Sunyaev–Zeldovich (SZ) effect. In this proof-of-concept paper, we test our approach on the WebSky extragalactic simulation maps in a range of frequencies from 93 to 545 GHz, and compare with one of the state-of-the-art traditional methods, MILCA, for the case of SZ. We first visually compare the images, and then statistically analyse the full-sky reconstructed high-resolution maps with power spectra. We study the contamination from other components with cross spectra, and particularly emphasise the correlation between the CIB and the SZ effect and compute SZ fluxes around positions of galaxy clusters. The independent networks learn how to reconstruct the different components with less contamination than MILCA. Although this is tested here in an ideal case (without noise, beams, or foregrounds), this method shows significant potential for application in future experiments such as the Simons Observatory (SO) in combination with the Planck satellite.
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)×(Te/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.
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