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Record W2766321643 · doi:10.3847/2041-8213/aa94c4

When Disorder Looks Like Order: A New Model to Explain Radial Magnetic Fields in Young Supernova Remnants

2017· article· en· W2766321643 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of ManitobaCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsMagnetic fieldSupernovaPolarization (electrochemistry)Radial velocityField (mathematics)Acceleration

Abstract

fetched live from OpenAlex

Abstract Radial magnetic fields are observed in all known young, shell-type supernova remnants in our Galaxy, including Cas A, Tycho, Kepler, and SN1006, and yet the nature of these radial fields has not been thoroughly explored. Using a 3D model, we consider the existence and observational implications of an intrinsically radial field. We also present a new explanation of the origin of the radial pattern observed from polarization data as resulting from a selection effect due to the distribution of cosmic-ray electrons (CREs). We show that quasi-parallel acceleration can concentrate CREs at regions where the magnetic field is radial, making a completely turbulent field appear ordered, when it is in fact disordered. We discuss observational properties that may help distinguish between an intrinsically radial magnetic field and the case where it only appears radial due to the CRE distribution. We also show that the case of an intrinsically radial field with a quasi-perpendicular CRE acceleration mechanism has intriguing similarities to the observed polarization properties of SN1006.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.998

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.224
Teacher spread0.213 · 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 designOther design
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

Citations30
Published2017
Admission routes1
Has abstractyes

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