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Record W2078473962 · doi:10.1086/423310

Theoretical Modeling of Weakly Lensed Polarized Radio Sources

2004· article· en· W2078473962 on OpenAlexaff
C. R. Burns, C. C. Dyer, Philipp P. Kronberg, Hermann-Josef Röser

Bibliographic record

VenueThe Astrophysical Journal · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhysicsRedshiftQuasarPolarization (electrochemistry)AstrophysicsGalaxyRadio galaxy

Abstract

fetched live from OpenAlex

In this paper we present the theoretical basis for the modeling of weakly gravitationally lensed extended sources that are polarized. This technique has been used in the past to constrain the mass profiles of galaxies projected against the jet of the quasar 3C 9. Since then, work has been done to improve both the measurement and theoretical modeling of the lensing signal, which manifests itself as an alignment breaking between the morphology and the polarization, parametrized as η G . To this end, we present the mathematical derivation of the theoretical value of η G as well as numerical simulations of expected signals in polarized radio jets. We use the radio jet sources 3C 9 and QSO 1253+104 as illustrative examples of the measurement and modeling of the η G signal. For 3C 9, we present constraints on the parameters of the two intervening lenses and quantify their confidence intervals. One lens has no measured redshift, and in this case, we show the dependence of mass and mass-to-light ratio on assumed redshift.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.008
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations13
Published2004
Admission routes1
Has abstractyes

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