Misaligned magnetized accretion flows onto spinning black holes: Magneto-spin alignment, outflow power, and intermittent jets
Bibliographic record
Abstract
Magnetic fields regulate black hole (BH) accretion, governing both inflow and outflow dynamics. When a BH accumulates substantial vertical magnetic flux, it enters the magnetically arrested disk (MAD) state, where dynamically important fields power jets and trigger disk eruptions. We investigate MAD evolution when the BH spin and disk angular momentum are misaligned, a likely scenario in many BH systems. Using numerical simulations, we show that jets from rapidly spinning, prograde BHs realign the inner disk via the magneto-spin alignment mechanism for initial tilts up to $T \lesssim 60^\circ$. Larger tilts lead to intermittent jets that disrupt the disk out to $r\gtrsim100$ gravitational radii, creating hot cavities and magnetized filaments. These episodic jets form a mini$-$feedback loop and may explain quasiperiodic X-ray and radio flares observed in low-luminosity active galaxies. We also find that (i) BH spin and disk tilt influence the amount of magnetic flux accumulated at the horizon, and (ii) large-scale, thick, misaligned accretion flows do not exhibit sustained Lense$-$Thirring (LT) precession. This suggests that slowly accreting BHs ($\dot{M} \ll 10^{-3} \dot{M}_{\rm Edd}$) are unlikely to show lightcurve quasiperiodic oscillations from LT precession, consistent with observations. Instead, magnetic flux eruptions drive jet wobbling and lateral motion, offering an alternative explanation for phenomena such as the M87 jet's apparent precession and rapid swings in blazar jet orientation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".