A SEARCH FOR HYPERLUMINOUS X-RAY SOURCES IN THE XMM-NEWTON SOURCE CATALOG
Bibliographic record
Abstract
ABSTRACT We present a new method to identify luminous off-nuclear X-ray sources in the outskirts of galaxies from large public redshift surveys, distinguishing them from foreground and background interlopers. Using the 3XMM-DR5 catalog of X-ray sources and the SDSS DR12 spectroscopic sample of galaxies, with the help of this off-nuclear cross-matching technique, we selected 98 sources with inferred X-ray luminosities in the range 1041 < L X < 1044 erg s−1, compatible with hyperluminous X-ray objects (HLX). To validate the method, we verify that it allowed us to recover known HLX candidates such as ESO 243–49 HLX–1 and M82 X–1. From a statistical study, we conservatively estimate that up to 71 ± 11 of these sources may be foreground- or background sources, statistically leaving at least 16 that are likely to be HLXs, thus providing support for the existence of the HLX population. We identify two good HLX candidates and using other publicly available data sets, in particular the VLA FIRST in radio, UKIRT Infrared Deep Sky Survey in the near-infrared, GALEX in the ultraviolet and Canada–France–Hawaii Telescope Megacam archive in the optical, we present evidence that these objects are unlikely to be foreground or background X-ray objects of conventional types, e.g., active galactic nuclei, BL Lac objects, Galactic X-ray binaries, or nearby stars. However, additional dedicated X-ray and optical observations are needed to confirm their association with the assumed host galaxies and thus secure their HLX classification.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".