THE<i>CHANDRA</i>DEEP PROTOCLUSTER SURVEY: Lyα BLOBS ARE POWERED BY HEATING, NOT COOLING
Bibliographic record
Abstract
We present the results of a 400 ks Chandra survey of 29 extended Lyα emitting nebulae (Lyα Blobs, LABs) in the z = 3.09 protocluster in the SS A22 field. We detect luminous X-ray counterparts in five LABs, implying a large fraction of active galactic nuclei (AGN) in LABs, f AGN = 17 +12 −7 % down to L 2–32 keV ∼ 10 44 erg s −1 . All of the AGN appear to be heavily obscured, with spectral indices implying obscuring column densities of N H > 10 23 cm −2 . The AGN fraction should be considered a lower limit, since several more LABs not detected with Chandra show AGN signatures in their mid-infrared (mid-IR) emission. We show that the UV luminosities of the AGN are easily capable of powering the extended Lyα emission via photoionization alone. When combined with the UV flux from a starburst component, and energy deposited by mechanical feedback, we demonstrate that "heating" by a central source, rather than gravitational cooling is the most likely power source of LABs. We argue that all LABs could be powered in this manner, but that the luminous host galaxies are often just below the sensitivity limits of current instrumentation, or are heavily obscured. No individual LABs show evidence for extended X-ray emission, and a stack equivalent to a ≳9 Ms exposure of an average LAB also yields no statistical detection of a diffuse X-ray component. The resulting diffuse X-ray/Lyα luminosity limit implies there is no hot ( T ≳ 10 7 K) gas component in these halos, and also rules out inverse Compton scattering of cosmic microwave background photons, or local far-IR photons, as a viable power source for LABs.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".