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Record W2136361263 · doi:10.1051/0004-6361/201322913

The cooling rate of neutron stars after thermonuclear shell flashes

2013· article· en· W2136361263 on OpenAlexafffund
J. J. M. in ’t Zand, A. Cumming, T. L. Triemstra, R. A. D. A. Mateijsen, T. Bagnoli

Bibliographic record

VenueAstronomy and Astrophysics · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsPhysicsAstrophysicsNeutron starThermonuclear fusionPower lawStarsAccretion (finance)OpacityNuclear physicsPlasmaStatisticsQuantum mechanics

Abstract

fetched live from OpenAlex

Thermonuclear shell flashes on neutron stars are detected as bright X-ray bursts. Traditionally, their decay is modeled with an exponential function. However, this is not what theory predicts. The expected functional form for luminosities below the Eddington limit, at times when there is no significant nuclear burning, is a power law. We tested the exponential and power-law functional forms against the best data available: bursts measured with the high-throughput Proportional Counter Array (PCA) onboard the Rossi X-ray Timing Explorer. We selected a sample of 35 “clean” and ordinary (i.e., shorter than a few minutes) bursts from 14 different neutron stars that 1) show a wide dynamic range in luminosity; 2) are the least affected by disturbances by the accretion disk; and 3) lack prolonged nuclear burning through the rp-process. We find indeed that for every burst a power law is a better description than an exponential function. We also find that the decay index is steep, 1.8 on average, and different for every burst. This may be explained by contributions from degenerate electrons and photons to the specific heat capacity of the ignited layer and by deviations from the Stefan-Boltzmann law due to changes in the opacity with density and temperature. Detailed verification of this explanation yields inconclusive results. While the values for the decay index are consistent, the predicted dependency of the decay index with the burst time scale, as a proxy of ignition depth, is not supported by the data.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.157
Teacher spread0.153 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2013
Admission routes2
Has abstractyes

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