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Record W2963437138 · doi:10.3847/1538-4357/ab1f83

Differences in Faraday Rotation between Adjacent Extragalactic Radio Sources as a Probe of Cosmic Magnetic Fields

2019· article· en· W2963437138 on OpenAlexafffund
Tessa Vernstrom, B. M. Gaensler, L. Rudnick, H. Andernach

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsFaraday effectCOSMIC cancer databaseAstronomyMagnetic fieldAstrophysicsRotation (mathematics)Faraday cage

Abstract

fetched live from OpenAlex

Abstract Faraday rotation measures (RMs) of extragalactic radio sources provide information on line-of-sight magnetic fields, including contributions from our Galaxy, source environments, and the intergalactic medium (IGM). Looking at differences in RMs, ΔRM, between adjacent sources on the sky can help isolate these different components. In this work, we classify adjacent polarized sources in the NRAO VLA Sky Survey (NVSS) as random or physical pairs. We recompute and correct the uncertainties in the NVSS RM catalog, since these were significantly overestimated. Our sample contains 317 physical and 5111 random pairs, all with Galactic latitudes , polarization fractions ≥2%, and angular separations between 1.′5 and 20′. We find an rms ΔRM of 14.9 ± 0.4 and 4.6 ± 1.1 rad m −2 for the random and physical pairs, respectively. This means that polarized extragalactic sources that are close on the sky but at different redshifts have larger differences in RM than two components of one source. This difference of ∼10 rad m −2 is significant at 5 σ and persists in different data subsamples. While there have been other statistical studies of ΔRM between adjacent polarized sources, this is the first unambiguous demonstration that some of this RM difference must be extragalactic, thereby providing a firm upper limit on the RM contribution of the IGM. If the ΔRMs originate local to the sources, then the local magnetic field difference between random sources is a factor of 2 larger than that between components of one source. Alternatively, attributing the difference in ΔRMs to the intervening IGM yields an upper limit on the IGM magnetic field strength of 40 nG.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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 teacher head, 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

Citations71
Published2019
Admission routes2
Has abstractyes

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