No Arabic abstract
Motivated by recent suggestions that a number of observed galaxy clusters have masses which are too high for their given redshift to occur naturally in a standard model cosmology, we use Extreme Value Statistics to construct confidence regions in the mass-redshift plane for the most extreme objects expected in the universe. We show how such a diagram not only provides a way of potentially ruling out the concordance cosmology, but also allows us to differentiate between alternative models of enhanced structure formation. We compare our theoretical prediction with observations, placing currently observed high and low redshift clusters on a mass-redshift diagram and find -- provided we consider the full sky to avoid a posteriori selection effects -- that none are in significant tension with concordance cosmology.
Power-law cosmologies, in which the cosmological scale factor evolves as a power law in the age, $a propto t^{alpha}$ with $alpha ga 1$, regardless of the matter content or cosmological epoch, is comfortably concordant with a host of cosmological observations.} {In this article, we use recent measurements of the X-ray gas mass fractions in clusters of galaxies to constrain the $alpha$ parameter with curvature $k = pm1, 0$. We find that the best fit happens for an open scenario with the power index $alpha = 1.14 pm 0.05$, though the flat and closed model can not be rule out at very high confidence level.} {Our results are in agreement with other recent analyses and show that the X-ray gas mass fraction measurements in clusters of galaxies provide a complementary test to the power law cosmology.
NIKA2 is a dual-band millimetric camera of thousands of Kinetic Inductance Detectors (KID) installed at the IRAM 30-meter telescope in the Spanish Sierra Nevada. The instrument commissioning was completed in September 2017, and NIKA2 is now open to the scientific community and will operate for the next decade. NIKA2 has well-adapted instrumental design and performance to produce high-resolution maps of the thermal Sunyaev-Zeldovich (SZ) effect toward intermediate and high redshift galaxy clusters. Moreover, it benefits from a guaranteed time large program dedicated to mapping a representative sample of galaxy clusters via SZ and that includes X-ray follow-ups. The main expected outputs of the SZ large program are the constraints on the redshift evolution of the pressure profile and the mass-observable relation. The first SZ mapping of a galaxy cluster with NIKA2 was produced, as part of the SZ large program. We found a sizable impact of the intracluster medium dynamics on the integrated SZ observables. This shows NIKA2 capabilities for the precise characterisation of the mass-observable relation that is required for accurate cosmology with galaxy clusters.
According to the cosmological principle, galaxy cluster sizes and cluster densities, when averaged over sufficiently large volumes of space, are expected to be constant everywhere, except for a slow variation with look-back time (redshift). Thus, average cluster sizes or correlation lengths provide a means of testing for homogeneity that is almost free of selection biases. Using ~10^6 galaxies from the SDSS DR7 survey, I show that regions of space separated by ~2 Gpc/h have the same average cluster size and density to 5 - 10 percent. I show that the average cluster size, averaged over many galaxies, remains constant to less than 10 percent from small redshifts out to redshifts of 0.25. The evolution of the cluster sizes with increasing redshift gives fair agreement when the same analysis is applied to the Millennium Simulation. However, the MS does not replicate the increase in cluster amplitudes with redshift seen in the SDSS data. This increase is shown to be caused by the changing composition of the SDSS sample with increasing redshifts. There is no evidence to support a model that attributes the SN Ia dimming to our happening to live in a large, nearly spherical void.
We test the assumption of hydrostatic equilibrium in an X-ray luminosity selected sample of 50 galaxy clusters at $0.15<z<0.3$ from the Local Cluster Substructure Survey (LoCuSS). Our weak-lensing measurements of $M_{500}$ control systematic biases to sub-4 per cent, and our hydrostatic measurements of the same achieve excellent agreement between XMM-Newton and Chandra. The mean ratio of X-ray to lensing mass for these 50 clusters is $beta_{rm X}=0.95pm0.05$, and for the 44 clusters also detected by Planck, the mean ratio of Planck mass estimate to LoCuSS lensing mass is $beta_{rm P}=0.95pm0.04$. Based on a careful like-for-like analysis, we find that LoCuSS, the Canadian Cluster Comparison Project (CCCP), and Weighing the Giants (WtG) agree on $beta_{rm P}simeq0.9-0.95$ at $0.15<z<0.3$. This small level of hydrostatic bias disagrees at $sim5sigma$ with the level required to reconcile Planck cosmology results from the cosmic microwave background and galaxy cluster counts.
We investigate potential systematic effects in constraining the amplitude of primordial fluctuations sigma_8 arising from the choice of halo mass function in the likelihood analysis of current and upcoming galaxy cluster surveys. We study the widely used N-body simulation fit of Tinker et al. (T08) and, as an alternative, the recently proposed analytical model of Excursion Set Peaks (ESP). We first assess the relative bias between these prescriptions when constraining sigma_8 by sampling the ESP mass function to generate mock catalogs and using the T08 fit to analyse them, for various choices of survey selection threshold, mass definition and statistical priors. To assess the level of absolute bias in each prescription, we then repeat the analysis on dark matter halo catalogs in N-body simulations designed to mimic the mass distribution in the current data release of Planck SZ clusters. This N-body analysis shows that using the T08 fit without accounting for the scatter introduced when converting between mass definitions (alternatively, the scatter induced by errors on the parameters of the fit) can systematically over-estimate the value of sigma_8 by as much as 2sigma for current data, while analyses that account for this scatter should be close to unbiased in sigma_8. With an increased number of objects as expected in upcoming data releases, regardless of accounting for scatter, the T08 fit could over-estimate the value of sigma_8 by ~1.5sigma. The ESP mass function leads to systematically more biased but comparable results. A strength of the ESP model is its natural prediction of a weak non-universality in the mass function which closely tracks the one measured in simulations and described by the T08 fit. We suggest that it might now be prudent to build new unbiased ESP-based fitting functions for use with the larger datasets of the near future.