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Reflection spectra from an accretion disc illuminated by a neutron star X-ray burst

2004· preprint· en· W6891918987 on OpenAlexaff

Bibliographic record

VenuearXiv (Cornell University) · 2004
Typepreprint
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsNeutron starSpectral lineEquivalent widthIonizationBlack-body radiationReflection (computer programming)Line (geometry)Amplitude

Abstract

fetched live from OpenAlex

Recent time-resolved X-ray spectra of a neutron star undergoing a superburst revealed an Fe K line and edge consistent with reprocessing from the surrounding accretion disc. Here, we present models of X-ray reflection from a constant density slab illuminated by a blackbody, the spectrum emitted by a neutron star burst. The calculations predict a prominent Fe K line and a rich soft X-ray line spectrum which is superimposed on a strong free-free continuum. The lines slowly vanish as the ionization parameter of the slab is increased, but the free-free continuum remains dominant at energiesless than 1 keV. The reflection spectrum has a quasi-blackbody shape only at energies greater than 3 keV. If the incident blackbody is added to the reflection spectrum, the Fe K equivalent width varies between 100 and 300 eV depending on the ionization parameter and the temperature, kT, of the blackbody. The equivalent width is correlated with kT, and therefore we predict a strong Fe K line when an X-ray burst is at its brightest (if iron is not too ionized or the reflection amplitude too small). Extending the study of reflection features in the spectra of superbursts to lower energies would provide further constraints on the accretion flow. If the Fe K line or other features are relativistically broadened then they can determine the system inclination angle (which leads to the neutron star mass), and, if the mass is known, a lower-limit to the mass/radius ratio of the star.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.036
GPT teacher head0.194
Teacher spread0.158 · 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.

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
Published2004
Admission routes1
Has abstractyes

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