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Particle acceleration and radio emission for SGRs/AXPs as white dwarf pulsars

2015· article· en· W2263513496 on OpenAlexfundaboutno aff
Ronaldo V. Lobato, Jaziel G. Coelho, M. Malheiro

Bibliographic record

VenueJournal of Physics Conference Series · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorMcGill University
KeywordsWhite dwarfPulsarPhysicsAstrophysicsAstronomyParticle accelerationAccelerationStarsClassical mechanics

Abstract

fetched live from OpenAlex

Recently, an alternative model based on white dwarfs pulsars has been proposed to explain a class of pulsars known as Soft Gamma Repeaters (SGR) and Anomalus X-Ray Pulsars (AXP) [6][4], usually named as magnetars. In this model the magnetized white dwarfs can have surface magnetic field B ∼ 107 — 1010G and rotate very fast with frequencies ω ∼ 1 rad/s, allowing them to produce large electromagnetic (EM) potentials and generate electron-positron pairs. These EM potentials are comparable with the ones of neutron stars pulsars with strong magnetic fields. In our study we consider two possible processes associated with the particle acceleration: in one we have the pair production near to the star polar caps i.e., inside the light cylinder where magnetic-field lines are closed, on the other the creation of pair is in the Outer Magnetosphere i.e., far away of the star surface where magnetic field are open [1]. This analysis of the possibility of radio emission was done for all the 23 SGRs/AXPs of the McGill Online Magnetar Catalog [7] that contains the current information available on these sources. Our work is a first attempted to find an explanation for the puzzle why for all the SGRs/AXPs was expected radio emission, but it was observed in only four of them.

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 score0.298
Threshold uncertainty score0.334

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 communication0.0000.001
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 head0.051
GPT teacher head0.352
Teacher spread0.301 · 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

Citations11
Published2015
Admission routes2
Has abstractyes

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