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Record W2961671295 · doi:10.4236/jhepgc.2019.53046

Multipole Analysis of Radio Continuum Images of Supernova Remnants: Comparison of Type Ia and Core Collapse

2019· article· en· W2961671295 on OpenAlexafffund
S. Ranasinghe, D. A. Leahy

Bibliographic record

VenueJournal of High Energy Physics Gravitation and Cosmology · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsQuadrupoleMultipole expansionAstrophysicsSupernovaAsymmetryEjectaSupernova remnantRADIUSMolecular cloudAtomic physics

Abstract

fetched live from OpenAlex

A multipole expansion analysis is applied to 1420 MHz radio continuum images of supernova remnants (SNRs) in order to compare Type Ia and core collapse (CC) SNRs. Because the radio synchrotron emission is produced at the outer shock between the SNR and the ISM, we are investigating whether the ISM interaction of SNRs is different between Type Ia and CC SNRs. This is in contrast to previous investigations, which have shown that Type Ia and CC SNRs have different asymmetries in the X-ray emission from their ejecta. The sample consists of 19 SNRs which have been classified as either Type Ia or CC. The quadrupole and octupole moments normalized to their monopole moments (total emission) are used as a measure of asymmetry of the emission. A broad range (by a factor of ~1000) is found for both quadrupole and octupole normalized moments. The strongest correlation we find is that large quadrupole moments are associated with large octupole moments, indicating that both serve as similar indicators of asymmetry. The other correlation we find is that both moments increase with SNR age or radius. This indicates that interstellar medium structure is a strong contributor to asymmetries in the radio emission from SNRs. This does not seem to apply to molecular clouds, because we find that association of a SNR with a molecular cloud is not correlated with larger quadrupole or octupole moments.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.263
Teacher spread0.253 · 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 designTheoretical or conceptual
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

Citations6
Published2019
Admission routes2
Has abstractyes

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