The HYENAS project: a prediction for the X-ray undetected galaxy groups
Bibliographic record
Abstract
ABSTRACT Galaxy groups contain the majority of bound mass with a significant portion of baryons due to the combination of halo mass and abundance (Cui 2024). Hence they serve as a crucial missing piece in the puzzle of galaxy formation and the evolution of large-scale structures in the Universe. In observations, mass-complete group catalogues are normally derived from galaxy redshift surveys detected through various three-dimensional group-finding algorithms. Confirming the reality of such groups, particularly in the X-rays, is critical for ensuring robust studies of galaxy evolution in these environments. Recent works have reported numerous optical groups that are X-ray undetected (see, e.g. Popesso et al. 2024), sparking debates regarding the reasons for the unexpectedly low hot gas fraction in galaxy groups. To address this issue, we utilize zoomed-in simulations of galaxy groups from the novel Hyenas project to explore the range of hot gas fractions within galaxy groups and investigate the intrinsic factors behind the observed variability in X-ray emission. We find that the halo formation time can play a critical role–we see that groups in haloes that formed earlier exhibit up to an order of magnitude brighter X-ray luminosities compared to those formed later. This suggests that undetected X-ray groups are preferentially late-formed haloes and highlights the connection between gas fraction and halo formation time in galaxy groups. Accounting for these biases in galaxy group identification is essential for advancing our understanding of galaxy formation and achieving precision in cosmological studies.
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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 | 0.002 | 0.008 |
| 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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".