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Record W3098488525

X-Ray Observations Of High-B Radio Pulsars

2013· article· en· W3098488525 on OpenAlexaff
S. A. Olausen, Weiwei Zhu, Julia K. Vogel, V. M. Kaspi, A. G. Lyne, C. M. Espinoza, B. W. Stappers, R. N. Manchester, M. A. McLaughlin

Bibliographic record

VenueThe Research Repository @ WVU (West Virginia University) · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsUniversity of British ColumbiaMcGill University
Fundersnot available
KeywordsPulsarPhysicsMagnetarAstrophysicsNeutron starBlack-body radiationLuminosityX-ray pulsarMagnetic fieldAstronomyRadiationGalaxyNuclear physics
DOInot available

Abstract

fetched live from OpenAlex

The study of high-magnetic-field pulsars is important for examining the relationships between radio pulsars, magnetars, and X-ray-isolated neutron stars (XINSs). Here we report on X-ray observations of three such high-magnetic-field radio pulsars. We first present the results of a deep XMM-Newton observation of PSR J1734-3333, taken to follow up on its initial detection in 2009. The pulsar's spectrum is well fit by a blackbody with a temperature of 300 +/- 60 eV, with bolometric luminosity L_bb = 2.0(+2.2 -0.7)e+32 erg/s = 0.0036E_dot for a distance of 6.1 kpc. We detect no X-ray pulsations from the source, setting a 1 sigma upper limit on the pulsed fraction of 60% in the 0.5-3 keV band. We compare PSR J1734-3333 to other rotation-powered pulsars of similar age and find that it is significantly hotter, supporting the hypothesis that the magnetic field affects the observed thermal properties of pulsars. We also report on XMM-Newton and Chandra observations of PSRs B1845-19 and J1001-5939. We do not detect either pulsar, setting 3 sigma upper limits on their blackbody temperatures of 48 and 56 eV, respectively. Despite the similarities in rotational properties, these sources are significantly cooler than all but one of the XINSs, which we attribute to the two groups having been born with different magnetic fields and hence evolving differently.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.034
GPT teacher head0.302
Teacher spread0.268 · 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 designObservational
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

Citations27
Published2013
Admission routes1
Has abstractyes

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