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Record W2944067238 · doi:10.1093/mnras/stz1325

A broad-band spectro-polarimetric view of the NVSS rotation measure catalogue – I. Breaking the nπ-ambiguity

2019· article· en· W2944067238 on OpenAlexafffund
Yik Ki, Sui Ann Mao, J. M. Stil, Aritra Basu, Jennifer West, Carl Heiles, Alex S. Hill, Sarah Betti

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of British ColumbiaNational Research Council CanadaCanadian Institute for Theoretical AstrophysicsHerzberg Institute of AstrophysicsUniversity of TorontoUniversity of Calgary
FundersNational Science Foundation of Sri LankaUniversity of TorontoBundesministerium für Bildung und ForschungSpace Telescope Science InstituteJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsPhysicsJanskyAmbiguityAstrophysicsFaraday effectMeasure (data warehouse)PolarimetrySkyGalaxyRadio galaxyOpticsQuantum mechanicsMagnetic field

Abstract

fetched live from OpenAlex

The NRAO VLA Sky Survey (NVSS) Rotation Measure (RM) catalogue is invaluable for the study of cosmic magnetism. However, the RM values reported in it can be affected by n$\pi$-ambiguity, resulting in deviations of the reported RM from the true values by multiples of +-652.9 rad m-2. We therefore set off to observationally constrain the fraction of sources in the RM catalogue affected by this ambiguity. New broadband spectro-polarimetric observations were performed with the Karl G. Jansky Very Large Array (VLA) at 1--2 GHz, with 23 n$\pi$-ambiguity candidates selected by their peculiarly high |RM| values. We identified nine sources with erroneous RM values due to n$\pi$-ambiguity and 11 with reliable RM values. In addition, we found two sources to be unpolarised and one source to be inconsistent with neither n$\pi$-ambiguity nor reliable RM cases. By comparing the statistical distributions of the above two main classes, we devised a measure of how much a source's RM deviates from that of its neighbours: $\Delta/\sigma$, which we found to be a good diagnostic of n$\pi$-ambiguity. With this, we estimate that there are at least 50 sources affected by n$\pi$-ambiguity among the 37,543 sources in the catalogue. Finally, we explored the Faraday complexities of our sources revealed by our broadband observations.

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 score0.406
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.195
Teacher spread0.188 · 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

Citations29
Published2019
Admission routes2
Has abstractyes

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