Magnetic fields in the intracluster medium with TNG-Cluster: Properties, morphology, and tangential anisotropy
Bibliographic record
Abstract
We characterized the magnetic field properties of 352 massive galaxy clusters from the TNG-Cluster magnetohydrodynamical (MHD) cosmological simulation with a focus on central magnetic field morphology in cool-core (CC) versus non-cool-core (NCC) clusters. We present the central values and radial profiles of magnetic field strength and plasma parameter as a function of mass, cooling status, and redshift. Compared to low-redshift observations, TNG-Cluster produces reasonable magnetic field amplitudes in the central regions of clusters, spanning a range of 1 − 200 μG. In this paper, we discuss the main finding of this work, namely, that z = 0 CC clusters have preferentially tangential magnetic fields at a characteristic scale of ∼0.1 r 500c . These strongly tangential field orientations are specific to CCs. In contrast, across the full cluster population, magnetic fields show isotropic configurations at all radii and redshifts. As individual halos grow, the evolution of their magnetic field topologies is diverse: tangential features can be short-lived, persist over large cosmological time-scales, or periodically appear, vanish, and reappear towards z = 0. We discuss the underlying physics and possible physical scenarios to explain the origin of these structures. We argue that both short-term active galactic nucleus (AGN) feedback-driven outflows and merger-driven sloshing motions, cannot explain the population-wide tangential bias in magnetic field orientation. Instead, we propose that the trapping of internal gravity waves is responsible for the tangentially biased magnetic field topologies that we find in CC TNG-Cluster halos, due to the strong entropy gradient in these clusters.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".