Continued cooling of the accretion-heated neutron star crust in the X-ray transient IGR J17480–2446 located in the globular cluster Terzan 5
Bibliographic record
Abstract
We present a new Chandra observation (performed in 2016 July) of the neutron star X-ray transient IGR J17480–2446, located in the globular cluster Terzan 5. We study the continued cooling of the neutron star crust in this system that was heated during the 2010 outburst of the source. This new observation was performed 2 yr after the last observation of IGR J17480–2446, hence, significantly extending the cooling baseline. We reanalysed all available Chandra observations of the source (but excluding observations during which one of the known transients in Terzan 5 was in outburst) and fitted the obtained cooling curve with our cooling code NSCool, which allows for much improved modelling than what was previously performed for the source. The data and our fit models indicate that the crust was still cooling ∼5.5 yr after the outburst ended. The neutron star crust has likely not reached crust-core thermal equilibrium yet, and further cooling is predicted (which can be confirmed with additional Chandra observations in >5 yr). Intriguingly, we find indications that the thermal conductivity might be relatively low in part of the crust compared to what has been inferred for other crust-cooling sources and tentatively suggest that this layer might be located around the neutron drip. The reason for this difference is unclear, but might be related to the fact that IGR J17480–2446 harbours a relatively slowly rotating neutron star (with a spin of 11 Hz) that has a relatively strong inferred surface magnetic field (109−10 Gauss) compared to what is known or typically assumed for other cooling sources.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".