Models for the Observable System Parameters of Ultraluminous X‐Ray Sources
Bibliographic record
Abstract
We investigate the evolution of model populations of ultraluminous X-ray sources (ULXs), consisting of a black hole accretor in a binary with a donor star. Two of the models we consider invoke stellar-mass (up to ~25 M ☉ ) black hole binaries (LMBHs), generated with a binary population synthesis code, while a third model uses intermediate-mass (~1000 M ☉ ) black hole accretors (IMBHs). For each model, we computed 30,000 binary evolution sequences. A scheme for calculating the optical flux from ULXs is discussed. We present ``probability images'' for the color-magnitude diagrams (CMDs) and for the orbital period-X-ray luminosity ( P orb - L x ) plane. We show how a population of luminous X-ray sources in a cluster of stars evolves with time. The most probable ULX system parameters correspond to high-mass donors (of initial mass ≳25 M ☉ ) with effective O through late B spectral types, and P orb between 1 and 10 days. Estimates of the numbers of ULXs in a typical galaxy as a function of L x are also presented. We find that if LMBHs are allowed to have super-Eddington L x , the binding energy parameter for the stellar envelope of the black hole progenitor must be λ ≲ 0.03 in order not to overproduce ULXs. Comparison of six known ULX counterparts with our model CMDs indicates that the IMBH model somewhat more closely matches the observations. We find that a significant contribution to the optical flux from the IMBH systems comes from intrinsic accretion disk radiation. In effect, IMBH systems, when operating at their maximum luminosities (10 41 -10 42 ergs s −1 ), are milli-AGNs . While models of IMBH systems during the X-ray phase are attractive, their formation mechanism remains uncertain.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".