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Record W4402386433 · doi:10.48550/arxiv.2408.05287

Constraining twin stars with cold neutron star cooling data

2024· preprint· en· W4402386433 on OpenAlexfundno aff
Melissa Mendes, Jan-Erik Christian, F. J. Fattoyev, Jürgen Schaffner–Bielich

Bibliographic record

VenueGSI Repository (GSI Helmholtzzentrum für Schwerionenforschung) · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
FundersMitacsEuropean CommissionDeutsche ForschungsgemeinschaftStrongSchlumberger Foundation
KeywordsNeutron starStarsStar (game theory)PhysicsAstrophysicsAstronomy

Abstract

fetched live from OpenAlex

We investigate the influence of a phase transition from hadronic matter to a deconfined quark phase inside a neutron star on its cooling behaviour including the appearance of twin star solutions in the mass-radius diagram. We find that while the inferred neutrino luminosity of cold transiently-accreting star in MXB $1659\text{-}29$ is reproduced in all of the constructed twin star models, the luminosity of a colder source, the neutron star in SAX J$1808.4\text{-}3658$, cannot be described by equations of state with quark-hadron transition densities below $1.7$ saturation density, suggesting that twin stars with such low density transitions to the quark phase are not realized in nature. We also discuss how constraints to the quark-hadron phase transition density are strongly dependent on the cooling effectiveness of neutrino reactions in the quark phase.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.023
GPT teacher head0.329
Teacher spread0.306 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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