2021
DOI: 10.1093/mnras/stab880
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Troubled cosmic flows: turbulence, enstrophy, and helicity from the assembly history of the intracluster medium

Abstract: Both simulations and observations have shown that turbulence is a pervasive phenomenon in cosmic scenarios, yet it is particularly difficult to model numerically due to its intrinsically multiscale character which demands high resolutions. Additionally, turbulence is tightly connected to the dynamical state and the formation history of galaxies and galaxy clusters, producing a diverse phenomenlogy which requires large samples of such structures to attain robust conclusions. In this work, we use an adaptive mes… Show more

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Cited by 17 publications
(10 citation statements)
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References 103 publications
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“…We attribute the difference to the unavoidable presence of compressive turbulence, consistent with previous work (e.g. Miniati 2015;Vazza et al 2017;Vallés-Pérez et al 2021) . Furthermore, the turbulent anisotropy parameter shows the effects of substantial radial accretion (see Fig.…”
Section: Discussionsupporting
confidence: 89%
See 1 more Smart Citation
“…We attribute the difference to the unavoidable presence of compressive turbulence, consistent with previous work (e.g. Miniati 2015;Vazza et al 2017;Vallés-Pérez et al 2021) . Furthermore, the turbulent anisotropy parameter shows the effects of substantial radial accretion (see Fig.…”
Section: Discussionsupporting
confidence: 89%
“…Alternatively, one can estimate the turbulent motions by interpolating the original 3-D velocity field in order to map the local mean field and to identify turbulent velocity fluctuations on scales smaller than the interpolation scale (Vazza et al 2009(Vazza et al , 2011a. As another alternative, a multi-scale iterative filtering approach has been implemented in, for example, Vazza et al (2012), Angelinelli et al (2020), Vallés-Pérez et al (2021. In the present work, we apply a simpler approach, that is by using a fixed scale filtering method, based on previous results by our group.…”
Section: Introductionmentioning
confidence: 99%
“…Exploring gas azimuthal decomposition on 2-D mock X-ray (and SZ) images will be the next necessary step to accurately evaluate the efficiency of such a technique on data observations by considering observational effects such as finite angular resolution, noise, etc. This approach might require high angular resolution (similarly to Vallés-Pérez et al 2021;Capalbo et al 2021), and could be a powerful tool to highlight patterns in current and future observations of the cosmic gas at the peripheries of galaxy clusters (Tchernin et al 2016;Barcons et al 2017;XRISM Science Team 2020;CHEX-MATE Collaboration et al 2021;Simionescu et al 2021).…”
Section: Discussionmentioning
confidence: 99%
“…Cluster peripheries are thus crucial places to probe the transition between hot and warm gas, and to probe the complex dynamics of infalling WHIM gas. In fact, this is in these regions that gas is expected to flow from filaments into clusters, with turbulent motions (Rost et al 2021;Vallés-Pérez et al 2021), and where accretion shocks might arise (Shi et al 2020;Zhang et al 2020Zhang et al , 2021bZhu et al 2021b). Following these findings on the radial gas properties, we focus in the rest of the paper our exploration of the azimuthal gas distribution in cluster environment concentrating on two main gas phases in two different radial apertures: hot medium up to 1 R 200 and WHIM from 1 to 2R 200 .…”
Section: Radial Gas Properties Summarymentioning
confidence: 99%
“…All the three simulations are performed at magnetic Prandtl number Pm = Rm/Re = 1, where Rm and Re are the magnetic and fluid Reynolds numbers, respectively. Recent cosmological simulations of hierarchical structure formation including the formation of galaxy clusters show that turbulence in the cluster core is dominated by solenoidal modes [33][34][35][36]. Accordingly, and to maximize the efficiency of the fluctuation dynamo, we use only solenoidal modes (i.e., ∇ • F = 0) for the turbulent driving.…”
Section: Summary Of Magnetohydrodynamic (Mhd) Simulationsmentioning
confidence: 99%