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Record W4212972699 · doi:10.3847/1538-4357/ac4045

The NANOGrav 12.5 yr Data Set: Polarimetry and Faraday Rotation Measures from Observations of Millisecond Pulsars with the Green Bank Telescope

2022· article· en· W4212972699 on OpenAlexaff
Haley M. Wahl, M. A. McLaughlin, Peter A. Gentile, Megan L. Jones, R. Spiewak, Zaven Arzoumanian, Kathryn Crowter, Paul B. Demorest, Megan E. DeCesar, Timothy Dolch, Justin A. Ellis, R. D. Ferdman, E. C. Ferrara, Emmanuel Fonseca, N. Garver-Daniels, G. Jones, Michael T. Lam, L. Levin, N. Lewandowska, D. R. Lorimer, Ryan S. Lynch, Dustin R. Madison, Cherry Ng, David J. Nice, Timothy T. Pennucci, S. M. Ransom, Paul S. Ray, I. H. Stairs, Kevin Stovall, Joseph K. Swiggum, Weiwei Zhu

Bibliographic record

VenueThe Astrophysical Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicGeophysics and Sensor Technology
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of TorontoMcGill UniversityUniversity of British Columbia
FundersOffice of Naval ResearchWest Virginia Space Grant ConsortiumNational Aeronautics and Space AdministrationScience and Technology Facilities CouncilNational Science Foundation
KeywordsPolarimetryFaraday effectGreen Bank TelescopeMillisecond pulsarPhysicsPulsarAstronomyTelescopeRotation (mathematics)PolarimeterAstrophysicsOpticsMagnetic fieldMathematicsGeometry

Abstract

fetched live from OpenAlex

Abstract In this work, we present polarization profiles for 23 millisecond pulsars observed at 820 and 1500 MHz with the Green Bank Telescope as part of the NANOGrav pulsar timing array. We calibrate the data using Mueller matrix solutions calculated from observations of PSRs B1929+10 and J1022+1001. We discuss the polarization profiles, which can be used to constrain pulsar emission geometry, and present both the first published radio polarization profiles for nine pulsars and the discovery of very low-intensity average profile components (“microcomponents”) in four pulsars. We obtain the Faraday rotation measures for each pulsar and use them to calculate the Galactic magnetic field parallel to the line of sight for different lines of sight through the interstellar medium. We fit for linear and sinusoidal trends in time in the dispersion measure and Galactic magnetic field and detect magnetic field variations with a period of 1 yr in some pulsars, but overall find that the variations in these parameters are more consistent with a stochastic origin.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.205
Teacher spread0.182 · 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

Citations29
Published2022
Admission routes1
Has abstractyes

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