Can We Distinguish Low-mass Black Holes in Neutron Star Binaries?
Bibliographic record
Abstract
Abstract The detection of gravitational waves (GWs) from coalescing binary neutron stars (NS) represents another milestone in gravitational-wave astronomy. However, since LIGO is currently not as sensitive to the merger/ringdown part of the waveform, the possibility that such signals are produced by a black hole (BH)–NS binary can not be easily ruled out without appealing to assumptions about the underlying compact object populations. We review a few astrophysical channels that might produce BHs below 3 M ⊙ (roughly the upper bound on the maximum mass of an NS), as well as existing constraints for these channels. We show that, due to the uncertainty in the NS equation of state, it is difficult to distinguish GWs from a binary NS system from those of a BH–NS system with the same component masses, assuming Advanced LIGO sensitivity. This degeneracy can be broken by accumulating statistics from many events to better constrain the equation of state, or by third-generation detectors with higher sensitivity to the late-spiral to post-merger signal. We also discuss the possible differences in electromagnetic (EM) counterparts between binary NS and low-mass BH–NS mergers, arguing that it will be challenging to definitively distinguish the two without better understanding of the underlying astrophysical processes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".