The origin of the intracluster light in The Three Hundred simulations
Bibliographic record
Abstract
We investigated the origin and formation mechanisms of the intracluster light (ICL) in T HE T HREE H UNDRED simulations, a set of 324 hydrodynamically resimulated massive galaxy clusters. The ICL, a diffuse component comprised of stars not bound to any individual galaxy, serves as a critical tracer of cluster formation and evolution. Using two implementations of hydrodynamics, G ADGET -X and G IZMO -S IMBA , we identified the stellar particles that constitute the ICL at z = 0 and traced them back in time to the moments when they were formed and accreted into the ICL. Our analysis reveals that, across our 324 clusters, half of the present-day ICL mass is typically in place between z ∼ 0.2 and 0.5. The main ICL formation channel is the stripping of stars from subhalos after their infall into the host cluster. Within this channel, 65−80% of the ICL comes from objects with stellar (infall) masses above 10 11 M ⊙ , corresponding to massive galaxies, groups and clusters. When we also consider the ratio of the infalling halo to the total cluster mass, we see that a median of 35% of the mass is brought in major merger events, although the percentage varies significantly across clusters (15−55%). Additional contributions come from minor mergers (25−35%) and smooth accretion (20−50%). The infall redshift of the primary contributors is generally below z ≤ 1, with smaller fractions arriving at redshifts between 1 and 2. Regarding other formation channels, we find minor contributions from stars formed in subhalos after their infall and stars stripped while their contributing halo remains outside the host cluster (and can eventually fall inside or stay outside). Finally, for our two sets of simulations, we find medians of 12 (G ADGET -X) and 2 (G IZMO -S IMBA ) percent of the ICL mass formed in situ, i.e. directly as part of the diffuse component. However, this component can be attributed to stripping of gas in high-velocity infalling satellite galaxies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".