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Record W3197578311 · doi:10.3847/1538-4357/ac2576

Discovery of Eight “Main-sequence Radio Pulse Emitters” Using the GMRT: Clues to the Onset of Coherent Radio Emission in Hot Magnetic Stars

2022· preprint· en· W3197578311 on OpenAlexaff
Barnali Das, P. Chandra, M. E. Shultz, G. A. Wade, James Sikora, O. Kochukhov, C. Neiner, M. E. Oksala, E. Alécian

Bibliographic record

VenueThe Astrophysical Journal · 2022
Typepreprint
Languageen
FieldEngineering
TopicAstronomical Observations and Instrumentation
Canadian institutionsBishop's UniversityRoyal Military College of Canada
Fundersnot available
KeywordsAstrophysicsPhysicsStarsGiant Metrewave Radio TelescopeMagnetic fieldMaserAstronomyGalaxyRadio galaxy

Abstract

fetched live from OpenAlex

Abstract Main-sequence radio pulse emitters (MRPs) are magnetic early-type stars from which periodic radio pulses, produced via electron cyclotron maser emission (ECME), are observed. Despite the fact that these stars can naturally offer suitable conditions for triggering ECME, only seven such stars have been reported so far within a span of more than two decades. In this paper, we report the discovery of eight more MRPs, thus more than doubling the sample size of such objects. These discoveries are the result of our sub-GHz observation program using the Giant Metrewave Radio Telescope over the years 2015–2021. Adding these stars to the previously known MRPs, we infer that at least 32% of the magnetic hot stars exhibit this phenomenon, thus suggesting that observation of ECME is not a rare phenomenon. The significantly larger sample of MRPs allows us for the first time to perform a statistical analysis comparing their physical properties. We present an empirical relation that can be used to predict whether a magnetic hot star is likely to produce ECME. Our preliminary analysis suggests that the physical parameters that play the primary role in the efficiency of the phenomenon are the maximum surface magnetic field strength and the surface temperature. In addition, we present strong evidence of the influence of the plasma density distribution on ECME pulse profiles. Results of this kind further motivate the search for MRPs, as a robust characterization of the relation between observed ECME properties and stellar physical parameters can only be achieved with a large sample.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.627

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 science0.0010.000
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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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