Buried Black Hole Growth in IR-selected Mergers: New Results from Chandra
Bibliographic record
Abstract
Abstract Observations and theoretical simulations suggest that a significant fraction of merger-triggered accretion onto supermassive black holes is highly obscured, particularly in late-stage galaxy mergers, when the black hole is expected to grow most rapidly. Starting with the Wide-Field Infrared Survey Explorer all-sky survey, we identified a population of galaxies whose morphologies suggest ongoing interaction and which exhibit red mid-infrared colors often associated with powerful active galactic nuclei (AGNs). In a follow-up to our pilot study, we now present Chandra/ACIS and XMM-Newton X-ray observations for the full sample of the brightest 15 IR-preselected mergers. All mergers reveal at least one nuclear X-ray source, with 8 out of 15 systems exhibiting dual nuclear X-ray sources, highly suggestive of single and dual AGNs. Combining these X-ray results with optical line ratios and with near-IR coronal emission line diagnostics, obtained with the near-IR spectrographs on the Large Binocular Telescope, we confirm that 13 out of the 15 mergers host AGNs, two of which host dual AGNs. Several of these AGNs are not detected in the optical. All X-ray sources appear X-ray weak relative to their mid-infrared continuum, and of the nine X-ray sources with sufficient counts for spectral analysis, eight reveal strong evidence of high absorption with column densities of N H ≳ 1023 cm−2. These observations demonstrate that a significant population of single and dual AGNs are missed by optical studies, due to high absorption, adding to the growing body of evidence that the epoch of peak black hole growth in mergers occurs in a highly obscured phase.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".