Magnetic fields in the Shapley Supercluster core with POSSUM: Challenging model predictions
Bibliographic record
Abstract
Context. Faraday rotation measure (RM) grids provide a sensitive means to trace magnetized plasma across a wide range of cosmic environments. Aims. We study the RM signal from the Shapley Supercluster core (SSC) in order to constrain the magnetic field properties of its gas. The SSC region consists of two galaxy clusters, A3558 and A3562, and two galaxy groups between them, at z ≃ 0.048. Methods. We combined RM Grid data with thermal Sunyaev-Zeldovich effect data, obtained from the POlarisation Sky Survey of the Universe’s Magnetism (POSSUM) pilot survey, and Planck, respectively. To robustly determine the gas density, its magnetic field properties, and their correlation | B | ∝ n e η , we studied the RM scatter in the SSC region (𝔖 RM ) and its behavior as a function of distance to the nearest cluster and/or group ( d nrst ). We compared observational results with semi-analytic Gaussian random field models and more realistic cosmological magnetohydrodynamical (MHD) simulations. Results. With a sky-density of 36 RMs/deg 2 , we detect an excess RM scatter of 30.5 ± 4.6 rad/m 2 in the SSC region. When we compare with models, we find an average magnetic field strength of ∼1−3 μG (in the groups and clusters). The 𝔖 RM ( d nrst ) profile, derived from data ranging from ∼0.3−1.8 r 500 for all objects, is systematically flatter than expected compared to the models, with η < 0.5 being favored. Despite this discrepancy, we find that cosmological MHD simulations matched to the SSC structure most closely align with scenarios where the magnetic field is amplified by the turbulent velocity ( v turb ) in the intercluster regions B ℱ ∝ n e 1/2 v turb on scales d nrst ≲ 0.8. Conclusions. The dense RM grid and precision provided by POSSUM allows us to probe magnetized gas in the SSC clusters and groups on scales within and beyond their r 500 . Flatter-than-expected RM scatter profiles reveal a significant challenge in reconciling observations with even the most realistic predictions from cosmological MHD simulations in the outskirts of interacting 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".