The Fate of Supermassive Black Holes and the Evolution of the <i>M</i> <sub>BH</sub> -σ Relation in Merging Galaxies: The Effect of Gaseous Dissipation
Bibliographic record
Abstract
We analyze the effect of dissipation on the orbital evolution of supermassive black holes (SMBHs) using high-resolution self-consistent gasdynamical simulations of binary equal- and unequal-mass mergers of disk galaxies. The galaxy models are consistent with the ΛCDM paradigm of structure formation, and the simulations include the effects of radiative cooling and star formation. We find that equal-mass mergers always lead to the formation of a close SMBH pair at the center of the remnant, with separations limited solely by the adopted force resolution of ~100 pc. Instead, the final SMBH separation in unequal-mass mergers depends sensitively on how the central structure of the merging galaxies is modified by dissipation. In the absence of dissipation, the satellite galaxy can be entirely disrupted before the merger is completed, leaving its SMBH wandering at a distance too far from the center of the remnant for the formation of a close pair. In contrast, gas cooling facilitates the pairing process by increasing the resilience of the companion galaxy to tidal disruption. Moreover, we demonstrate that merging disk galaxies constructed to obey the M BH -σ relation move relative to it depending on whether they undergo a dissipational or collisionless merger, regardless of the mass ratio of the merging systems. Collisionless simulations reveal that remnants tend to move away from the mean relation, highlighting the role of gas-poor mergers as a possible source of scatter. In dissipational mergers, the interplay between strong gas inflows associated with the formation of massive nuclear disks and the consumption of gas by star formation provides the necessary fuel to the SMBHs and allows the merger remnants to satisfy the relation
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".