A Wide and Deep Exploration of Radio Galaxies with Subaru HSC (WERGS). VI. Distant Filamentary Structures Pointed Out by High-z Radio Galaxies at z ∼ 4
Bibliographic record
Abstract
Abstract We present the environmental properties around high-z radio galaxies (HzRGs) at z ∼ 4, which have been poorly investigated because of their rarity. We use the largest samples of HzRGs and g-dropout galaxy overdense regions at z ∼ 4, which were constructed from the Hyper Suprime-Cam Subaru Strategic Program, to characterize the HzRG environments statistically. We measure the g-dropout galaxy overdensities around 21 HzRGs whose rest-frame 1.4 GHz radio luminosities (L 1.4 GHz) are 1026–27 W Hz−1. We find that the overdensities around the faint HzRGs with L 1.4 GHz ∼ 1026.0–26.5 W Hz−1 tend to be higher than those of the g-dropout galaxies. On the other hand, no significant difference of density environments is found between the luminous HzRGs with L 1.4 GHz ∼ 1026.5–27.0 W Hz−1 and the g-dropout galaxies. The HzRGs are found to occupy more massive halos than g-dropout galaxies through a cross-correlation between the HzRGs and g-dropout galaxies. This trend is more pronounced in the faint HzRGs. These results are consistent with a scenario where HzRGs get older and more massive as the radio luminosity decreases. The HzRGs are expected to trace the progenitors of Local Cluster halos from their calculated halo mass. In addition, we find that surrounding galaxies tend to distribute along the radio jet major axis of the HzRGs at angular distances of ≲500 physical kpc. Our findings imply the onset of the filamentary structures around the HzRGs at z ∼ 4.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".