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Record W4416652270 · doi:10.1051/0004-6361/202556287

Magnetic fields in the Shapley Supercluster core with POSSUM: Challenging model predictions

2025· article· en· W4416652270 on OpenAlexafffund
D. Alonso-López, S.P. O'Sullivan, A. Bonafede, Ludwig M. Böss, C. Stuardi, E. Osinga, Cameron L. Van Eck, E. Carretti, Jennifer West, Takuya Akahori, S. Giacintucci, A. Khadir, Yik Ki, S. Malik, N. M. McClure‐Griffiths, L. Rudnick, Benjamin Seidel, Sudhanshu Tiwari, T. Venturi

Bibliographic record

VenueAstronomy and Astrophysics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsDominion Astrophysical ObservatoryUniversity of TorontoHerzberg Institute of Astrophysics
FundersOffice of Naval ResearchAgencia Estatal de InvestigaciónNatural Sciences and Engineering Research Council of CanadaGovernment of Western AustraliaNuclear Safety and Security CommissionUniversity of TorontoDeutsche ForschungsgemeinschaftEuropean Regional Development FundEuropean CommissionCommonwealth Scientific and Industrial Research OrganisationAustralian GovernmentBanco SantanderScience and Industry Endowment FundUniversidad Complutense de MadridAgence Nationale de la RechercheComunidad de MadridCanada Research ChairsNational Aeronautics and Space Administration
KeywordsFaraday effectSupercluster (genetic)Galaxy clusterMagnetic fieldGalaxyMeasure (data warehouse)Field (mathematics)RedshiftCluster (spacecraft)Magnetohydrodynamic turbulence

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.008
GPT teacher head0.198
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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