Dual Jet Interaction, Magnetically Arrested Flows, and Flares in Accreting Binary Black Holes
Bibliographic record
Abstract
Abstract Supermassive binary black holes in galactic centers are potential multimessenger sources in gravitational waves and electromagnetic radiation. To find such objects, isolating unique electromagnetic signatures of their accretion flow is key. With the aid of three-dimensional general-relativistic magnetohydrodynamic simulations that utilize an approximate, semianalytic, superimposed spacetime metric, we identify two such signatures for merging binaries. Both involve magnetic reconnection and are analogous to plasma processes observed in the solar corona. The first, like colliding flux tubes that can cause solar flares, involves colliding jets that form an extended reconnection layer, dissipating magnetic energy and causing the two jets to merge. The second, akin to coronal mass ejection events, involves the accretion of magnetic field lines onto both black holes; these magnetic fields then twist, inflate, and form a trailing current sheet, ultimately reconnecting and driving a hot outflow. We provide estimates for the associated electromagnetic emission for both processes, showing that they likely accelerate electrons to high energies and are promising candidates for continuous, stochastic, and/or quasi-periodic higher-energy electromagnetic emission. We also show that the accretion flows around each black hole can display features associated with the magnetically arrested state. However, simulations with black hole spins misaligned with the orbital plane and simulations with larger Bondi radii saturate at lower values of horizon-penetrating magnetic flux than standard magnetically arrested disks, leading to weaker, intermittent jets owing to feedback from the weak jets or equatorial flux tubes ejected by reconnecting field lines near the horizon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".