Science potential for stellar-mass black holes as neighbors of Sgr <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msup><mml:mrow><mml:mi mathvariant="normal">A</mml:mi></mml:mrow><mml:mrow><mml:mo>*</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math>
Bibliographic record
Abstract
It has been suggested that there is possibly a class of stellar-mass black holes (BHs) residing near (distance $\ensuremath{\le}{10}^{3}M$) the galactic center massive black hole, Sgr A*. Possible formation scenarios include the mass segregation of massive stellar-mass black holes and/or the disk migration if there was an active accretion flow near Sgr A* within $\mathcal{O}(10)\text{ }\text{ }\mathrm{Myr}$. In this work, we explore the application of this type of objects as sources of space-borne gravitational wave detectors, such as Laser Interferometer Space Antenna (LISA). We find it is possible to probe the spin of Sgr A* based on the precession of the orbital planes of these stellar-mass black holes moving around Sgr A*. We also show that the dynamical friction produced by accumulated cold dark matter near Sgr A* generally produces small measurable phase shift in the gravitational waveform. In the case that there is an axion cloud near Sgr A*, the dynamical friction induced modification to gravitational waveform is measurable only if the mass of the axion field is in a narrow range of the mass spectrum. Gravitational interaction between the axion cloud and the stellar-mass black holes may introduce additional precession around the spin of Sgr A*. This additional precession rate is generally weaker than the spin-induced Lense-Thirring precession rate, but nevertheless may contaminate the spin measurement in a certain parameter regime. At last, we point out that the multibody gravitational interaction between these stellar-mass black holes generally causes negligible phase shift during the LISA lifetime.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".