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Record W2073564764 · doi:10.1086/383610

H<scp>i</scp>Absorption of Polarized Emission: A New Technique for Determining Kinematic Distances to Galactic Supernova Remnants

2004· article· en· W2073564764 on OpenAlexaff
R. Kothes, T. L. Landecker, M. Wolleben

Bibliographic record

VenueThe Astrophysical Journal · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of CalgaryHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPhysicsAstrophysicsSupernovaNebulaAbsorption (acoustics)Polarization (electrochemistry)PulsarSupernova remnantAstronomyStarsOptics

Abstract

fetched live from OpenAlex

We present a new method of determining the systemic velocity of Galactic supernova remnants (SNRs) based on H I absorption of their linearly polarized radio continuum emission. Conventional H I observations of total power emission are limited by H I emission and self-absorption along the line of sight, but since H I emission is unpolarized, the only limits on measurements of absorption of the polarized emission are noise and velocity resolution. This leads to lower uncertainties and makes it possible to obtain absorption profiles for virtually all Galactic SNRs with very precise H I column densities. To demonstrate the new technique, we have obtained H I absorption profiles from Tycho's supernova remnant (G120.1+1.4). Absorption profiles of the polarized emission are very similar to those of the total power emission. Optical depths from the polarization profiles are slightly larger because of small-scale emission features. We also observed polarization absorption profiles of the Boomerang pulsar wind nebula (part of G106.3+2.7) and the plerionic SNR DA 495 (G65.7+1.2), remnants that are so faint that absorption profiles cannot be obtained in total power.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.720
Threshold uncertainty score0.684

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 integrity0.0000.000
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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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 designBench or experimental
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

Citations21
Published2004
Admission routes1
Has abstractyes

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