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Record W2809614080 · doi:10.1142/9789811203770_0006

The Measurement of Polarization in Radio Astronomy

2021· book-chapter· en· W2809614080 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWORLD SCIENTIFIC eBooks · 2021
Typebook-chapter
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsNational Research Council CanadaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPolarimeterStokes parametersPolarization (electrochemistry)TelescopePhysicsRadio telescopeOpticsConfusionPolarimetryAstronomyRemote sensingGeology

Abstract

fetched live from OpenAlex

Modern dual-polarization receivers allow a radio telescope to characterize the full polarization state of incoming insterstellar radio waves. Many astronomers incorrectly consider a polarimeter to be the "backend" of the telescope. We go to lengths to dissuade the reader of this concept: the backend is the least complicated component of the radio telescope when it comes to measuring polarization. The feed, telescope structure, dish surface, coaxial cables, optical fibers, and electronics can each alter the polarization state of the received astronomical signal. We begin with an overview of polarized radiation, introducing Jones and Stokes vectors, and then discuss construction of digitized pseudo-Stokes vectors from the outputs of modern correlators. We describe the measurement and calibration process for polarization observations and illustrate how instrumental polarization can affect a measurement. Finally, we draw attention to the confusion generated by various polarization conventions and highlight the need for observers to state all adopted conventions when reporting polarization results.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.982
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.022
GPT teacher head0.208
Teacher spread0.187 · 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