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arxiv: 2606.05355 · v1 · pith:WCU4OH5Pnew · submitted 2026-06-03 · 🌌 astro-ph.GA

Bulk vs. turbulent motions at the centres of galaxy clusters: AGN-driven turbulence according to TNG-Cluster

Bipradeep Saha , Annalisa Pillepich , Joey Braspenning , Marine Prunier , Dimitris Chatzigiannakis , Dylan Nelson This is my paper

Pith reviewed 2026-06-28 04:56 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords galaxy clustersintracluster mediumturbulent motionsbulk motionsvelocity dispersionAGN feedbackhydrodynamical simulations
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The pith

Simulations show turbulent motions contribute less than half the total velocity dispersion in galaxy cluster centers.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper separates bulk coherent motions from small-scale turbulent fluctuations in the hot gas of galaxy clusters. It establishes that in central regions turbulence typically supplies only about half the total velocity dispersion, with values around 50 to 75 km per second and negligible contribution to pressure support. Supermassive black hole feedback emerges as the main source of this turbulence, appearing stronger in clusters that are strong cool cores or show signs of recent activity. The work matters because accurate separation of motion types affects how high-resolution X-ray spectra are interpreted for cluster thermodynamics and mass estimates.

Core claim

The central claim is that in the hot X-ray emitting gas at cluster centers turbulence contributes less than half of the total velocity dispersion for most systems, with typical turbulent dispersions of 50-75 km s^{-1} and sub-percent levels of turbulent pressure support. The turbulent velocity dispersion peaks at the center, reaches a minimum at 0.1-0.2 R_500c, then rises again. Clusters with strong cool cores, X-ray cavities, or recent black hole feedback injections show systematically larger turbulent velocities and more prominent high-velocity tails. Black hole feedback is presented as the key driver of turbulence in the cores, generating strong but short-lived motions together with high-

What carries the argument

The multi-scale filtering Reynolds decomposition, which isolates small-scale turbulent fluctuations from coherent bulk motions in the gas velocity field.

If this is right

  • The intracluster medium shows mostly subsonic turbulence but with broad velocity distributions that can reach high Mach numbers in some regions.
  • Turbulent velocity dispersion is enhanced in clusters that are strong cool cores or have experienced recent black hole feedback energy injections.
  • The radial profile of turbulent dispersion exhibits a central peak, a dip at intermediate radii, and a subsequent rise.
  • Black hole feedback produces strong but transient turbulent motions and outflows in cluster cores.
  • Interpreting high spectral resolution X-ray observations requires distinguishing bulk from turbulent components.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The dominance of bulk motions suggests that velocity-based mass estimates in cluster cores may need separate accounting for coherent flows rather than assuming isotropic turbulence.
  • Correlations between turbulence levels and black hole activity could be tested directly with upcoming X-ray line broadening measurements in individual clusters.
  • The short-lived nature of feedback-driven turbulence implies that time-averaged energy injection rates might underpredict instantaneous motion amplitudes.
  • Extending the separation to non-central regions or higher redshifts could clarify how turbulence contributes to overall cluster thermodynamic balance.

Load-bearing premise

The multi-scale filtering correctly isolates turbulent small-scale motions from coherent bulk flows in the simulated hot gas.

What would settle it

High-resolution X-ray spectroscopy of real cluster cores that measures a turbulent velocity dispersion exceeding half the total dispersion in a majority of systems would falsify the central claim.

Figures

Figures reproduced from arXiv: 2606.05355 by Annalisa Pillepich, Bipradeep Saha, Dimitris Chatzigiannakis, Dylan Nelson, Joey Braspenning, Marine Prunier.

Figure 1
Figure 1. Figure 1: Functioning of the multi-scale filtering Reynolds Decomposition (RD) used throughout this work to separate bulk vs. turbulent gas motions [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Distribution of the filtering scale Lfilter that separates bulk vs. turbulent motions within the central regions of TNG-Cluster. Thin lines indicate individual systems, whereas thick curves give the median results in cluster mass bins. Lfilter represents the local spatial scale above which bulk motion dominates over small-scale velocity fluctuations (i.e. turbulence). Based on the outcome of TNG-Cluster an… view at source ↗
Figure 3
Figure 3. Figure 3: Spatially-resolved turbulent and bulk motions in the cluster centres for a subset of representative TNG-Cluster systems. [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Velocity distributions of bulk and turbulent motions of the hot X-ray-emitting gas ( [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Distributions of Mach numbers for the hot gas ( [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Turbulent vs. total velocity dispersion as function of cluster mass and gas temperature in the central regions of TNG-Cluster systems at [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: The dependence of the turbulent velocity dispersion on cluster properties related to SMBH feedback, according to TNG-Cluster. [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Time evolution of the gas kinematics in the central region of the most massive cluster in the TNG300 simulation, for which high temporal [PITH_FULL_IMAGE:figures/full_fig_p013_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Time evolution of the radial profiles of turbulent velocity dispersion ( [PITH_FULL_IMAGE:figures/full_fig_p014_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Radial profiles of gas velocity dispersion and non-thermal pressure support in TNG-Cluster systems. [PITH_FULL_IMAGE:figures/full_fig_p015_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: The apparent lack of dependence of the turbulent velocity dispersion in cluster centres on large-scale external processes. [PITH_FULL_IMAGE:figures/full_fig_p017_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Insights on the physical drivers of ICM turbulence imprinted in the tails of the velocity distributions, according to TNG-Cluster. [PITH_FULL_IMAGE:figures/full_fig_p018_12.png] view at source ↗
read the original abstract

The highly dynamic intracluster medium (ICM) influences cluster thermodynamic evolution and probes key physical processes. Quantifying the non-thermal motions is therefore essential for understanding cluster physics and interpreting high spectral-resolution X-ray observations from telescopes like {\it XRISM}. We quantify bulk and turbulent gas motions in 352 galaxy clusters at $z=0$ (${\rm M_{200c}=10^{14.3-15.4}\, M_\odot}$) from the TNG-Cluster suite of magneto-hydrodynamical galaxy simulations. We use a multi-scale filtering Reynolds decomposition to separate total gas velocities into bulk (coherent) and turbulent (small-scale fluctuations) components. We primarily focus on the hot X-ray emitting gas in the central core regions. According to TNG-Cluster, majority of the ICM has subsonic turbulence but with broad velocity distributions reaching $\mathcal{M}_{\rm Turb}\sim 10$ and large cluster-to-cluster variations. In cluster centres, turbulence contributes less than half of the total velocity dispersion $(\sigma_{v\rm,Turb } \sim 0.5 ~\sigma_{v,\rm Total})$ for most clusters, with typical turbulent velocity dispersions of $50-75$ km s$^{-1}$ across the mass range, and with sub per cent levels of turbulent pressure support. Clusters that are strong cool cores, or have X-ray cavities, or experienced recent SMBH feedback energy injections exhibit systematically larger turbulent velocity dispersions and more prominent turbulent velocity tails. On average, the turbulent velocity dispersion peaks in cluster centres, decreases slightly to a minimum at $0.1-0.2 \, R_{\rm500c}$, then rises again. Our analysis shows that SMBH feedback is a key driver of turbulence in cluster cores, generating strong but short-lived motion alongside high-velocity outflows. It also calls for caution for interpreting {\it XRISM} observations.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper analyzes bulk and turbulent gas motions in the hot ICM of 352 galaxy clusters (M_200c = 10^14.3-15.4 M_⊙) at z=0 from the TNG-Cluster magneto-hydrodynamical simulations. Using a multi-scale filtering Reynolds decomposition on the central core regions, it reports that turbulence contributes less than half the total velocity dispersion (σ_v,Turb ~ 0.5 σ_v,Total) with typical values 50-75 km s^{-1}, sub-percent turbulent pressure support, mostly subsonic but broad Mach number distributions up to ~10, and identifies SMBH feedback as a key driver, with implications for XRISM observations.

Significance. If the decomposition holds, the large statistical sample provides quantitative benchmarks on non-thermal motions and limited turbulent pressure support in cluster cores, directly relevant to interpreting high-resolution X-ray spectroscopy and AGN feedback effects. The scale of the TNG-Cluster suite (352 objects) is a clear strength for assessing cluster-to-cluster variations.

major comments (2)
  1. [Methods (Reynolds decomposition)] The multi-scale filtering Reynolds decomposition (described in the methods) is load-bearing for all quantitative claims, including the headline σ_v,Turb ~ 0.5 σ_v,Total ratio and sub-percent pressure support. No validation against analytic test cases, no resolution convergence tests specific to the core region, and no sensitivity analysis to filter scale choices are described; the separation of coherent bulk flows from small-scale fluctuations could shift with different thresholds or effective Reynolds number.
  2. [Results (SMBH feedback section)] The attribution of turbulence to SMBH feedback (abstract and results) relies on correlations with cool-core status, X-ray cavities, and recent energy injections, but lacks a quantitative decomposition of energy injection rates versus turbulent dissipation or a control comparison to runs without AGN feedback.
minor comments (2)
  1. [Abstract] Abstract: the notation σ_v,Turb and σ_v,Total should be defined on first use for clarity.
  2. [Results (radial profiles)] The radial profile of turbulent velocity dispersion (peaking in center, minimum at 0.1-0.2 R_500c) would benefit from explicit error bars or bootstrap uncertainties given the cluster-to-cluster scatter.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for their constructive comments. We address each major comment below and indicate where revisions will be made.

read point-by-point responses

  1. Referee: The multi-scale filtering Reynolds decomposition (described in the methods) is load-bearing for all quantitative claims, including the headline σ_v,Turb ~ 0.5 σ_v,Total ratio and sub-percent pressure support. No validation against analytic test cases, no resolution convergence tests specific to the core region, and no sensitivity analysis to filter scale choices are described; the separation of coherent bulk flows from small-scale fluctuations could shift with different thresholds or effective Reynolds number.

    Authors: We agree that the manuscript would benefit from explicit validation of the Reynolds decomposition. Although the method follows established techniques from prior simulation studies, we will add a new subsection to the Methods section that includes: validation against analytic test cases with prescribed bulk flows plus fluctuations; resolution convergence tests for core regions using the multiple resolution levels in TNG-Cluster for a representative subsample; and sensitivity tests to filter scale choices. These additions will be incorporated in the revised manuscript. revision: yes

  2. Referee: The attribution of turbulence to SMBH feedback (abstract and results) relies on correlations with cool-core status, X-ray cavities, and recent energy injections, but lacks a quantitative decomposition of energy injection rates versus turbulent dissipation or a control comparison to runs without AGN feedback.

    Authors: The evidence for SMBH feedback as a driver rests on statistically significant correlations between turbulent velocity dispersion and indicators of recent AGN activity (cool-core status, X-ray cavities, recent energy injections) across the 352-cluster sample. We will expand the discussion to include more detail on the timescales of energy injection and turbulent dissipation. However, the TNG-Cluster suite does not contain control runs without AGN feedback, precluding a direct comparison. revision: partial

standing simulated objections not resolved
  • Control comparison to runs without AGN feedback, as such simulations are not available in the TNG-Cluster suite.

Circularity Check

0 steps flagged

No significant circularity: results are direct measurements from simulation data via standard decomposition

full rationale

The paper applies a multi-scale filtering Reynolds decomposition to TNG-Cluster simulation outputs to quantify bulk vs. turbulent velocities in cluster cores, reporting empirical statistics such as σ_v,Turb ~ 0.5 σ_v,Total. No load-bearing step reduces by the paper's own equations to a fitted parameter, self-citation chain, or self-definitional ansatz; the decomposition is presented as an input method whose outputs are measured quantities, not redefined or forced by the target results. The derivation chain is therefore self-contained and externally falsifiable via the simulation data.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claims rest on the fidelity of the TNG-Cluster magneto-hydrodynamical model and the validity of the chosen decomposition technique; no free parameters or new entities are introduced in the abstract.

axioms (1)
  • domain assumption The TNG-Cluster magneto-hydrodynamical simulations accurately model the relevant physics of the ICM and AGN feedback.
    All quantitative conclusions about turbulence levels and drivers are outputs of this specific simulation suite.

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Forward citations

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