Evaluating Lyα Emission as a Tracer of the Largest Cosmic Structure at z ∼ 2.47
Bibliographic record
Abstract
Abstract The discovery and spectroscopic confirmation of Hyperion, a protosupercluster at z ∼ 2.47, provides an unprecedented opportunity to study distant galaxies in the context of their large-scale environment. We carry out deep narrowband imaging of a ≈1° × 1° region around Hyperion and select 157 Lyα emitters (LAEs). The inferred LAE overdensity is δ g ≈ 40 within an effective volume of 30 × 20 × 15 cMpc3, consistent with the fact that Hyperion is composed of multiple protoclusters and will evolve into a supercluster with a total mass of M tot ≈ 1.4 × 1015 M ⊙ at z = 0. The distribution of LAEs closely mirrors that of known spectroscopic members, tracing the protocluster cores and extended filamentary arms connected to them, suggesting that they trace the same large-scale structure. By cross-correlating the LAE positions with H i tomography data, we find weak evidence that LAEs may be less abundant in the highest H i regions, perhaps because Lyα is suppressed in such regions. The Hyperion region hosts a large population of active galactic nuclei (AGNs) ≈ 12 times more abundant than that in the field. The prevalence of AGNs in protocluster regions hints at the possibility that they may be triggered by physical processes that occur more frequently in dense environments, such as galaxy mergers. Our study demonstrates LAEs as reliable markers of the largest cosmic structures. When combined with ongoing and upcoming imaging and spectroscopic surveys, wide-field narrowband imaging has the potential to advance our knowledge in the formation and evolution of cosmic structures and of their galaxy inhabitants.
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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 | 0.000 |
| 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".