Hydrodynamic Simulation of Non-Thermal Pressure Profiles of Galaxy Clusters

Nelson, Keith E.; Lau, Erwin T.; Nagai, Daisuke

doi:10.1088/0004-637x/792/1/25

Cited by 194 publications

(253 citation statements)

References 45 publications

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“…Finally, by discarding Abell383 from the nonthermal pressure analysis, we further restricted our attention to clusters whose X-ray and SZ data do not show evidence of line-of-sight elongation. Although hydrodynamical simulations do find lower levels of nonthermal pressure support in relaxed systems, the levels they observe are still higher than what we have constrained with this sample, which suggests that selection effects alone cannot explain our result (Rasia et al 2012;Nelson et al 2014). …”

Section: Nonthermal Pressure: Caveatscontrasting

confidence: 70%

Constraints on the Mass, Concentration, and Nonthermal Pressure Support of Six CLASH Clusters from a Joint Analysis of X-Ray, SZ, and Lensing Data

Siegel

Sayers

Mahdavi

et al. 2018

ApJ

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We present a joint analysis of Chandra X-ray observations, Bolocam thermal Sunyaev-Zel'dovich (SZ) effect observations, Hubble Space Telescope (HST) strong-lensing data, and HST and Subaru Suprime-Cam weak-lensing data. The multiwavelength data set is used to constrain parametric models for the distribution of dark and baryonic matter in a sample of six massive galaxy clusters selected from the Cluster Lensing And Supernova survey with Hubble (CLASH). For five of the six clusters, the multiwavelength data set is well described by a relatively simple model that assumes spherical symmetry, hydrostatic equilibrium, and entirely thermal pressure support. The joint analysis yields considerably better constraints on the total mass and concentration of the clusters compared to analysis of any one data set individually. The resulting constraints are consistent with simulation-based predictions for the concentration-mass relation. The subsample of five galaxy clusters is used to place an upper limit on the fraction of pressure support in the intracluster medium (ICM) due to nonthermal processes, such as turbulence and bulk flow of the gas. We constrain the nonthermal pressure fraction at r 500c to be <0.11 at 95% confidence. This is in tension with state-of-the-art hydrodynamical simulations, which predict a nonthermal pressure fraction of ≈0.25 at r 500c for clusters of similar mass and redshift. This tension may be explained by the sample selection and/or our assumption of spherical symmetry.

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Section: Nonthermal Pressure: Caveatscontrasting

confidence: 70%

Constraints on the Mass, Concentration, and Nonthermal Pressure Support of Six CLASH Clusters from a Joint Analysis of X-Ray, SZ, and Lensing Data

Siegel

Sayers

Mahdavi

et al. 2018

ApJ

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“…An enhancement of the nonthermal pressure (random gas motions) with redshift is also shown by recent hydrodynamical simulations (Lau et al 2009;Nelson et al 2014), who in addition find that there is practically no mass dependence for this effect. Our treatment of a non-selfsimilar pressure shape, therefore, only consists of an evolution with redshift and no scaling with cluster mass.…”

Section: F Gas Evolution Vs X-ray Data and Simulationssupporting

confidence: 61%

Constraining the intracluster pressure profile from the thermal SZ power spectrum

Ramos-Ceja

Basu

Pacaud

et al. 2015

A&A

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The angular power spectrum of the thermal Sunyaev-Zel'dovich (tSZ) effect is highly sensitive to cosmological parameters such as σ 8 and Ω m , but its use as a precision cosmological probe is hindered by the astrophysical uncertainties in modeling the gas pressure profile in galaxy groups and clusters. In this paper we assume that the relevant cosmological parameters are accurately known and explore the ability of current and future tSZ power spectrum measurements to constrain the intracluster gas pressure or the evolution of the gas mass fraction, f gas . We use the CMB bandpower measurements from the South Pole Telescope and a Bayesian Markov chain Monte Carlo (MCMC) method to quantify deviations from the standard, universal gas pressure model. We explore analytical model extensions that bring the predictions for the tSZ power into agreement with experimental data. We find that a steeper pressure profile in the cluster outskirts or an evolving f gas have mild-to-severe conflicts with experimental data or simulations. Varying more than one parameter in the pressure model leads to strong degeneracies that cannot be broken with current observational constraints. We use simulated bandpowers from future tSZ survey experiments, in particular a possible 2000 deg 2 CCAT survey, to show that future observations can provide almost an order of magnitude better precision on the same model parameters. This will allow us to break the current parameter degeneracies and place simultaneous constraints on the gas pressure profile and its redshift evolution, for example.

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“…Several numerical simulations show that the fractional contribution from non-thermal pressure increases with radius (Shaw et al 2010;Battaglia et al 2012;Nelson et al 2014). For all three studies, non-thermal pressure fractions between 15% and 30% are found at (R R 500 ) for redshifts z 0 1 < < .…”

Section: Introductionmentioning

confidence: 77%

Galaxy Cluster Pressure Profiles as Determined by Sunyaev Zel’dovich Effect Observations with MUSTANG and Bolocam. II. Joint Analysis of 14 Clusters

Romero

Mason

Sayers

et al. 2017

ApJ

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We present pressure profiles of galaxy clusters determined from high-resolution Sunyaev-Zel'dovich (SZ) effect observations of 14 clusters, which span the redshift range of z 0.25 0.89 < <. The procedure simultaneously fits spherical cluster models to MUSTANG and Bolocam data. In this analysis, we adopt the generalized NFW parameterization of pressure profiles to produce our models. Our constraints on ensemble-average pressure profile parameters, in this study γ, C 500 , and P 0 , are consistent with those in previous studies, but for individual clusters we find discrepancies with the X-ray derived pressure profiles from the ACCEPT2 database. We investigate potential sources of these discrepancies, especially cluster geometry, electron temperature of the intracluster medium, and substructure. We find that the ensemble mean profile for all clusters in our sample is described by the parameters C P , , 0.3 , 1.3 , 8.6 500 0 0

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Hydrodynamic Simulation of Non-Thermal Pressure Profiles of Galaxy Clusters

Cited by 194 publications

References 45 publications

Constraints on the Mass, Concentration, and Nonthermal Pressure Support of Six CLASH Clusters from a Joint Analysis of X-Ray, SZ, and Lensing Data

Constraints on the Mass, Concentration, and Nonthermal Pressure Support of Six CLASH Clusters from a Joint Analysis of X-Ray, SZ, and Lensing Data

Constraining the intracluster pressure profile from the thermal SZ power spectrum

Galaxy Cluster Pressure Profiles as Determined by Sunyaev Zel’dovich Effect Observations with MUSTANG and Bolocam. II. Joint Analysis of 14 Clusters

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