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Register a new userNon-thermal pressure support in X-COP galaxy clusters
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Added by
Dominique Eckert Dr.
Publication date
2018
fields
Physics
and research's language is
English
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Galaxy clusters are the endpoints of structure formation and are continuously growing through the merging and accretion of smaller structures. Numerical simulations predict that a fraction of their energy content is not yet thermalized, mainly in the form of kinetic motions (turbulence, bulk motions). Measuring the level of non-thermal pressure support is necessary to understand the processes leading to the virialization of the gas within the potential well of the main halo and to calibrate the biases in hydrostatic mass estimates. We present high-quality measurements of hydrostatic masses and intracluster gas fraction out to the virial radius for a sample of 12 nearby clusters with available XMM-Newton and Planck data. We compare our hydrostatic gas fractions with the expected universal gas fraction to constrain the level of non-thermal pressure support. We find that hydrostatic masses require little correction and infer a median non-thermal pressure fraction of $sim6%$ and $sim10%$ at $R_{500}$ and $R_{200}$, respectively. Our values are lower than the expectations of hydrodynamical simulations, possibly implying a faster thermalization of the gas. If instead we use the mass calibration adopted by the Planck team, we find that the gas fraction of massive local systems implies a mass bias $1-b=0.85pm0.05$ for SZ-derived masses, with some evidence for a mass-dependent bias. Conversely, the high bias required to match Planck CMB and cluster count cosmology is excluded by the data at high significance, unless the most massive halos are missing a substantial fraction of their baryons.
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Due to their late formation in cosmic history, clusters of galaxies are not fully in hydrostatic equilibrium and the gravitational pull of their mass at a given radius is expected not to be entirely balanced by the thermal gas pressure. Turbulence may supply additional pressure, and recent (X-ray and SZ) hydrostatic mass reconstructions claim a pressure support of $sim 5-15%$ of the total pressure at $R_{rm 200}$. In this work we show that, after carefully disentangling bulk from small-scale turbulent motions in high-resolution simulations of galaxy clusters, we can constrain which fraction of the gas kinetic energy effectively provides pressure support in the clusters gravitational potential. While the ubiquitous presence of radial inflows in the cluster can lead to significant bias in the estimate of the non-thermal pressure support, we report that only a part of this energy effectively acts as a source of pressure, providing a support of the order of $sim 10%$ of the total pressure at $R_{rm 200}$.
We present the reconstruction of hydrostatic mass profiles in 13 X-ray luminous galaxy clusters that have been mapped in their X-ray and SZ signal out to $R_{200}$ for the XMM-Newton Cluster Outskirts Project (X-COP). Using profiles of the gas temperature, density and pressure that have been spatially resolved out to (median value) 0.9 $R_{500}$, 1.8 $R_{500}$, and 2.3 $R_{500}$, respectively, we are able to recover the hydrostatic gravitating mass profile with several methods and using different mass models. The hydrostatic masses are recovered with a relative (statistical) median error of 3% at $R_{500}$ and 6% at $R_{200}$. By using several different methods to solve the equation of the hydrostatic equilibrium, we evaluate some of the systematic uncertainties to be of the order of 5% at both $R_{500}$ and $R_{200}$. A Navarro-Frenk-White profile provides the best-fit in nine cases out of 13, with the remaining four cases that do not show a statistically significant tension with it. The distribution of the mass concentration follows the correlations with the total mass predicted from numerical simulations with a scatter of 0.18 dex, with an intrinsic scatter on the hydrostatic masses of 0.15 dex. We compare them with the estimates of the total gravitational mass obtained through X-ray scaling relations applied to $Y_X$, gas fraction and $Y_{SZ}$, and from weak lensing and galaxy dynamics techniques, and measure a substantial agreement with the results from scaling laws, from WL at both $R_{500}$ and $R_{200}$ (with differences below 15%), from cluster velocity dispersions, but a significant tension with the caustic masses that tend to underestimate the hydrostatic masses by 40% at $R_{200}$. We also compare these measurements with predictions from alternative models to the Cold Dark Matter, like the Emergent Gravity and MOND scenarios.
We present the constraints on the helium abundance in 12 X-ray luminous galaxy clusters that have been mapped in their X-ray and Sunyaev-Zeldovich (SZ) signals out to $R_{200}$ for the XMM-Newton Cluster Outskirts Project (X-COP). The unprecedented precision available for the estimate of $H_0$ allows us to investigate how much the reconstructed X-ray and SZ signals are consistent with the expected ratio $x$ between helium and proton densities of 0.08-0.1. We find that a $H_0$ around 70 km/s/Mpc is preferred from our measurements, with lower values of $H_0$ as requested from the Planck collaboration (67 km/s/Mpc) requiring a 34% higher value of $x$. On the other hand, higher values of $H_0$, as obtained by measurements in the local universe, impose $x$, from the primordial nucleosynthesis calculations and current solar abundances, reduced by 37--44%.
We use three-dimensional MHD simulations with anisotropic thermal conduction to study turbulence due to the magnetothermal instability (MTI) in the intracluster medium (ICM) of galaxy clusters. The MTI grows on timescales of ~1 Gyr and is capable of driving vigorous, sustained turbulence in the outer parts of galaxy clusters if the temperature gradient is maintained in spite of the rapid thermal conduction. If this is the case, turbulence due to the MTI can provide up to 5-30% of the pressure support beyond r_500 in galaxy clusters, an effect that is strongest for hot, massive clusters. The turbulence driven by the MTI is generally additive to other sources of turbulence in the ICM, such as that produced by structure formation. This new source of non-thermal pressure support reduces the observed Sunyaev-Zeldovich (SZ) signal and X-ray pressure gradient for a given cluster mass and introduces a cluster mass and temperature gradient-dependent bias in SZ and X-ray mass estimates of clusters. This additional physics may also need to be taken into account when estimating the matter power spectrum normalization, sigma-8, through simulation templates from the observed amplitude of the SZ power spectrum.
We use a set of 45 simulated clusters with a wide mass range ($8times 10^{13} < M_{500}~[$M$_{odot}]~< 2times 10^{15}$) to investigate the effect of varying hydrodynamics flavours on cluster mass estimates. The cluster zooms were simulated using the same cosmological models as the BAHAMAS and C-EAGLE projects, leading to differences in both the hydrodynamic solvers and the subgrid physics but still producing clusters which broadly match observations. At the same mass resolution as BAHAMAS, for the most massive clusters ($M_{500} > 10^{15}$ M$_{odot}$), we find changes in the SPH method produce the greatest differences in the final halo, while the subgrid models dominate at lower mass. By calculating the mass of all of the clusters using different permutations of the pressure, temperature and density profiles, created with either the true simulated data or mock spectroscopic data, we find that the spectroscopic temperature causes a bias in the hydrostatic mass estimates which increases with the mass of the cluster, regardless of the SPH flavour used. For the most massive clusters, the estimated mass of the cluster using spectroscopic density and temperature profiles is found to be as low as 50 per cent of the true mass compared to $sim$ 90 per cent for low mass clusters. When including a correction for non-thermal pressure, the spectroscopic hydrostatic mass estimates are less biased on average and the mass dependence of the bias is reduced, although the scatter in the measurements does increase.
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