<tt>Simba</tt>-<tt>C</tt>: the evolution of the thermal and chemical properties in the intragroup medium
Bibliographic record
Abstract
ABSTRACT The newly updated GIZMO and Simba based simulation, Simba-C, with its new stellar feedback, chemical enrichment, and recalibrated AGN feedback, allows for a detailed study of the intragroup medium X-ray properties. We discuss the impact of various physical mechanisms, e.g. stellar and AGN feedback, and chemical enrichment, on the composition and the global scaling relations of nearby galaxy groups. We also study the evolution (z = 2 to 0) of the global properties for the $1\, \mathrm{keV}$ temperature groups. Simba-C shows improved consistent matching with the observations of all X-ray scaling relations compared to Simba. It is well known that AGN feedback has a significant influence on LX, 0.5–2.0–Tspec, corr, S500/2500–Tspec, corr, and gas mass fractions, with our Simba-C results consistent with it. Our recalibrated AGN feedback strength also showed an additional improvement in gas entropy, which now aligns with CLoGS observations. The updated stellar feedback and chemical enrichment model is shown to play an important role in our understanding of the chemical abundance ratios and their evolution within galaxy groups. In particular, we find that Simba-C produces an increase in the amount of heavier elements (specifically Si and Fe) relative to O, compared to Simba.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".