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arxiv: 2605.27511 · v1 · pith:NG4AXJ4Jnew · submitted 2026-05-26 · 🌌 astro-ph.HE · astro-ph.GA

BlackHoleWeather -- Jet-regulated chaotic cold accretion across the meso scale: Variability and kinematics

Vieri Cammelli , Massimo Gaspari , Filippo Barbani , Olmo Piana , Giovanni Stel , Davide M. Brustio , Valeria Olivares , Roberto Serafinelli
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Pasquale Temi Francesco Salvestrini Michael Reefe Filippo M. Maccagni Francesco Tombesi
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Pith reviewed 2026-06-29 15:32 UTC · model grok-4.3

classification 🌌 astro-ph.HE astro-ph.GA
keywords chaotic cold accretionjet feedbacksupermassive black holesmeso-scale transportkinematicsvariabilitygalaxy groupsmultiphase gas
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The pith

Jet-regulated chaotic cold accretion is controlled by meso-scale transport of cold gas rather than its production alone.

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

The paper examines how a self-regulated kinetic jet alters the kinematics, radial transport, and variability of chaotic cold accretion across the meso-scale in galaxy-group atmospheres, using two simulations that differ only in turbulent driving strength. Both runs transition to CCA-fed states with accretion rising from Bondi-like to super-Bondi levels while staying low-Eddington and mechanically dominated, but the strongly stirred run shows an early stormy phase of bursty feeding and fountain-like recycling followed by a cloudy phase with weakened central coupling, whereas the calmer run sustains a compact rainy state. The jet excavates a hot channel that suppresses condensation inside it, with C~1 conditions reached mostly outside the cone and at interfaces; power spectra display flicker-like slopes and red-noise tails that flatten in cloudy phases. This establishes that combined k-plot and C-ratio diagnostics are needed to separate merely present cold gas from gas dynamically linked to supermassive black hole feeding.

Core claim

Jet-regulated CCA is controlled by meso-scale transport, not only by cold-gas production. Within the BlackHoleWeather framework, combined k-plot and C-ratio diagnostics are crucial to distinguish cold gas that is merely present from cold gas dynamically linked to SMBH feeding. Both runs become CCA-fed once precipitation begins, with accretion rising from Bondi-like to strongly super-Bondi values while remaining mostly low-Eddington and mechanically dominated. The strongly stirred run develops an early stormy phase with extended condensation, bursty feeding, and strong inflow/outflow variability, but later enters a cloudy phase in which cold and warm gas persist at meso- and inner macro-scale

What carries the argument

self-regulated kinetic jet model using k-plots and cooling-to-eddy-time (C-ratio) profiles to measure phase-separated mass fluxes, accretion histories, and variability across meso-scales

If this is right

  • Accretion-rate power spectra exhibit flicker-like low-frequency slopes and red-noise tails, with normalization dropping and slopes flattening in the cloudy phase.
  • Phase-separated mass fluxes reveal fountain-like recycling in the strongly stirred run versus inner-kpc recycling in the calmer run.
  • The jet creates a hot channel where sustained condensation is suppressed, while C~1 is reached mostly outside the cone and near the jet-ambient interface.
  • Accretion remains mostly low-Eddington and mechanically dominated even as it becomes strongly super-Bondi once precipitation begins.

Where Pith is reading between the lines

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

  • The distinction between stormy and cloudy phases could map onto different observed levels of turbulence or jet activity in galaxy groups.
  • k-plot and C-ratio diagnostics might be adapted to X-ray and radio observations to identify which multiphase structures are actively feeding the black hole.
  • This implies jet feedback structures inflow pathways in addition to providing heating, affecting how cold gas reaches the center over time.

Load-bearing premise

The self-regulated kinetic jet model and runs differing only in turbulent driving strength accurately isolate the effects of jet regulation on CCA without other unmodeled variables dominating the meso-scale transport and condensation outcomes.

What would settle it

Observing whether the spatial distribution of C~1 regions in real galaxy groups aligns with jet-ambient interfaces and correlates with measured accretion variability would test if meso-scale transport governs feeding.

Figures

Figures reproduced from arXiv: 2605.27511 by Davide M. Brustio, Filippo Barbani, Filippo M. Maccagni, Francesco Salvestrini, Francesco Tombesi, Giovanni Stel, Massimo Gaspari, Michael Reefe, Olmo Piana, Pasquale Temi, Roberto Serafinelli, Valeria Olivares, Vieri Cammelli.

Figure 1
Figure 1. Figure 1: Black hole accretion rate as a function of time in the low-turb and high-turb case, as indicated in the legend. The simulation time has been normalized to visually compare the different runs starting from the time they have been restarted with the jet and the cooling on. Dur￾ing active jet phases, M˙ • reaches large super-Bondi values (cf. B26a,b). The dotted horizontal line marks the Bondi reference accre… view at source ↗
Figure 2
Figure 2. Figure 2: Power spectral density (PSD) as a function of frequency in the low-turb and high-turb case, as indicated in the legend, from the time the jet and the cooling have been restarted. Light solid lines show the direct PSD from the M˙ • reported in [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Probability density function (PDF), normalized to unity in log￾arithmic space, of the Eddington ratios λEdd ≡ M˙ •/M˙ Edd as derived from the M˙ • for the 2 reference runs, high-turb (red solid line) and low-turb (blue solid line), computed at each time step. Black dashed guide lines indicate approximate slopes of −1 and −2 in the high-λEdd tail. Focusing on our fiducial high-turb and low-turb runs, both d… view at source ↗
Figure 4
Figure 4. Figure 4: Inflow rate as a function of the radius in the low-turb and high-turb case, as indicated in the legend. For the latter, we subdivide the two different weather phases, stormy (dash-dotted) and cloudy (dot￾ted lines). Lines show the 50th percentile throughout the whole duration of the simulation, with the shaded areas indicating the 1 sigma levels at any given radius (16th and 84th percentiles). For comparis… view at source ↗
Figure 5
Figure 5. Figure 5: Inflow coupling efficiency as a function of the radius in the low-turb (blue dashed line) and high-turb (red solid line) case. As in [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Phase-separated mass inflow rates for the high-turb (top figure) and low-turb (bottom figure) runs as a function of time normalized to t/train. Inflow is defined from gas with negative radial velocity, and each panel shows the corresponding M˙ in for a given thermal phase: molecular, cold, warm, soft X-ray, hard X-ray, and the total (black lines). Solid, dashed, and dotted lines refer to r = 0.1, 1, and 10… view at source ↗
Figure 7
Figure 7. Figure 7: Phase-separated mass outflow rates for the high-turb (top figure) and low-turb (bottom figure) runs as a function of time normalized to t/train. Outflow is defined from gas with positive radial velocity, and each panel shows the corresponding M˙ out for a given thermal phase: molecular, cold, warm, soft X-ray, hard X-ray, and the total (black lines). Solid, dashed, and dotted lines refer to r = 0.1, 1, and… view at source ↗
Figure 8
Figure 8. Figure 8: k-plot: evolution of projected gas kinematics in the k-plot plane, log10(|vlos − vsys|/km s−1 ) versus log10(σlos/km s−1 ), shown for four radial shells from micro- to outer macro-scale. The top row shows high-turb, while the bottom row shows low-turb. Blue, green, and red contours show the time-integrated distributions of the cold, warm, and hot phase components, respectively. For visual clarity, the mole… view at source ↗
Figure 9
Figure 9. Figure 9: As in [PITH_FULL_IMAGE:figures/full_fig_p014_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Radial evolution of the C-ratio for different temperature-defined emission-band proxies, comparing the high-turb (left panels) and low-turb (right panels) runs. Curves with the same color and line style refer to the same gas phase, as indicated in the legend. Within each phase, lighter to darker shades encode increasing evolutionary time in units of t/train, as shown by the color bar. Vertical lines and s… view at source ↗
read the original abstract

Chaotic cold accretion (CCA) predicts that supermassive black holes are fed by multiphase clouds condensing from turbulent hot atmospheres. In jet-regulated systems cold gas must also remain dynamically connected to the central accretion region. We investigate how a self-regulated kinetic jet modifies the kinematics, radial transport, and variability of CCA across the meso-scale of a typical galaxy-group atmosphere. The runs differ only in turbulent driving strength. We measure accretion histories, Eddington ratios, power spectra, phase-separated mass fluxes, projected k-plots, and cooling-to-eddy-time (C-ratio) profiles. Both runs become CCA-fed once precipitation begins, with accretion rising from Bondi-like to strongly super-Bondi values while remaining mostly low-Eddington and mechanically dominated. The strongly stirred run develops an early stormy phase with extended condensation, bursty feeding, and strong inflow/outflow variability, but later enters a cloudy phase in which cold and warm gas persist at meso- and inner macro-scales while sink coupling weakens. The calmer run maintains a compact rainy state with a longer-lived central reservoir. Accretion-rate spectra show flicker-like low-frequency slopes and red-noise tails; in the cloudy phase, the normalization drops and the low-frequency slope flattens. Phase-separated fluxes show fountain-like recycling in the strongly stirred run, but inner-kpc recycling in the calmer run. The jet excavates a hot channel where sustained condensation is suppressed, while C~1 is reached mostly outside the cone and near the jet-ambient interface. Jet-regulated CCA is controlled by meso-scale transport, not only by cold-gas production. Within the BlackHoleWeather framework, combined k-plot and C-ratio diagnostics are crucial to distinguish cold gas that is merely present from cold gas dynamically linked to SMBH feeding.

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

1 major / 1 minor

Summary. The paper simulates jet-regulated chaotic cold accretion (CCA) across the meso-scale in galaxy-group atmospheres using the BlackHoleWeather framework. Two runs differing only in turbulent driving strength are compared via accretion histories, Eddington ratios, power spectra, phase-separated mass fluxes, projected k-plots, and C-ratio profiles. Both become CCA-fed with super-Bondi accretion that remains mechanically dominated; the strongly stirred run shows an early stormy phase transitioning to a cloudy phase with fountain recycling and hot-channel suppression, while the calmer run maintains a compact rainy state. The authors conclude that meso-scale transport, not merely cold-gas production, controls jet-regulated CCA, and that combined k-plot and C-ratio diagnostics are needed to link cold gas to SMBH feeding.

Significance. If the results hold after addressing the isolation of jet effects, the work would strengthen CCA theory by demonstrating the role of meso-scale kinematics and jet excavation in regulating feeding variability and recycling. The multi-diagnostic approach (power spectra, phase fluxes, k-plots, C-ratios) offers a concrete way to distinguish present versus dynamically connected cold gas, which could be useful for interpreting observations of multiphase atmospheres.

major comments (1)
  1. [Abstract] Abstract: The central claim that jet-regulated CCA is controlled by meso-scale transport (rather than cold-gas production alone) rests on differences between the strongly stirred and calmer runs. However, these runs differ in turbulent driving strength, which directly modulates eddy turnover times, condensation rates, and radial fluxes that enter the C-ratio and k-plot diagnostics. This leaves open whether the observed differences in stormy/rainy phases, fountain recycling, and hot-channel suppression arise primarily from the self-regulated jet or from the driving altering the underlying turbulence spectrum and precipitation thresholds.
minor comments (1)
  1. The abstract introduces specialized diagnostics (projected k-plots, C-ratio profiles) without brief definitions; ensure these are defined on first use in the main text with reference to prior work if applicable.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive comments. We address the single major comment below, indicating where a partial revision will be made for clarity.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The central claim that jet-regulated CCA is controlled by meso-scale transport (rather than cold-gas production alone) rests on differences between the strongly stirred and calmer runs. However, these runs differ in turbulent driving strength, which directly modulates eddy turnover times, condensation rates, and radial fluxes that enter the C-ratio and k-plot diagnostics. This leaves open whether the observed differences in stormy/rainy phases, fountain recycling, and hot-channel suppression arise primarily from the self-regulated jet or from the driving altering the underlying turbulence spectrum and precipitation thresholds.

    Authors: Both simulations employ the identical self-regulated kinetic jet prescription, with jet power and orientation determined instantaneously by the SMBH accretion rate. The intentional difference in turbulent driving strength is used to vary the meso-scale eddy turnover and radial transport while keeping the jet feedback mechanism fixed. In both runs cold-gas production occurs via thermal instability, yet the resulting feeding variability, fountain recycling, and hot-channel suppression differ because the stronger driving enhances meso-scale fluxes that interact with the jet-excavated region. This comparison therefore isolates the modulating role of meso-scale transport within an otherwise identical jet-regulated CCA framework, rather than claiming to separate the jet from all turbulence effects. We will revise the abstract to state explicitly that the jet is self-regulated in both runs and that the driving variation probes meso-scale control of the coupled system. revision: partial

Circularity Check

0 steps flagged

No significant circularity; claims rest on simulation outputs

full rationale

The paper derives its conclusions on jet-regulated CCA, meso-scale transport, and diagnostics (k-plots, C-ratios, phase-separated fluxes) directly from the outputs of two hydrodynamical runs that differ only in turbulent driving strength. Accretion histories, power spectra, and variability measures are computed from the simulated data rather than fitted parameters renamed as predictions. No self-definitional loops, fitted-input predictions, or load-bearing self-citation chains appear in the derivation; the BlackHoleWeather framework is invoked only as context while the specific meso-scale results follow from the described simulation measurements. This is self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The work rests on the CCA framework as a domain assumption and on simulation parameters such as turbulent driving strength; no invented entities are introduced.

free parameters (1)
  • turbulent driving strength
    Runs differ only in this parameter controlling turbulence, which affects the stormy vs. cloudy phases.
axioms (1)
  • domain assumption CCA predicts that supermassive black holes are fed by multiphase clouds condensing from turbulent hot atmospheres.
    Stated as the foundational prediction in the abstract.

pith-pipeline@v0.9.1-grok · 5911 in / 1301 out tokens · 41380 ms · 2026-06-29T15:32:43.102228+00:00 · methodology

discussion (0)

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