Meso-Scale Turbulence Fractures Black Hole Accretion Bridges, Exposing Gaps in Galaxy Evolution Models
Turbulence-regulated meso-scale accretion controls SMBH spin and jet reorientation at levels conventional models overlook, linking galaxy feedback to observable variability.
The arXiv preprint 'BlackHoleWeather' (Piana et al. 2026) deploys four 3D hydrodynamical runs inside a 100-kpc volume with sub-parsec resolution and the Hybrid SMBH spin model to show how persistent solenoidal turbulence severs the meso-scale bridge that funnels cold clouds and filaments inward. In driven-turbulence cases the radial accretion rate collapses by two to three orders of magnitude while torque coherence fragments, locking jet axes into slow drift; interrupted-turbulence controls preserve connected channels and allow reorientation rates two orders of magnitude higher, occasionally flipping several degrees during coherent retrograde episodes. This split appears directly in power spectra: connected rain boosts low-frequency accretion power and narrows velocity loci, whereas stirring steepens high-frequency damping. The work remains a preprint and therefore lacks peer review; its idealized turbulence driving and absence of magnetic fields or cosmic-ray physics constitute clear limitations. Earlier CCA studies (Gaspari et al. 2013, MNRAS 432, 626) established the multiphase rain paradigm but stopped at kpc scales; spin-evolution papers (e.g., Dubois et al. 2014) tracked horizon-scale torques without resolving the intervening meso-scale continuity that this simulation suite now isolates. The missing link is observational: the simulated variability should imprint on X-ray light curves and jet precession statistics in cool-core clusters, a prediction testable with XRISM and ngVLA but absent from current coverage.
HELIX: Persistent turbulence at 100-pc scales can throttle SMBH feeding enough to decouple spin evolution from large-scale cooling flows, forcing revisions in both semi-analytic galaxy models and feedback prescriptions used in cosmological simulations.
Sources (3)
- [1]Primary Source(https://arxiv.org/abs/2605.27508)
- [2]Related Source(https://ui.adsabs.harvard.edu/abs/2013MNRAS.432..626G)
- [3]Related Source(https://ui.adsabs.harvard.edu/abs/2014MNRAS.444.2444D)