An Assessment of the In Situ Growth of the Intracluster Light in the High-redshift Galaxy Cluster SpARCS1049+56
Bibliographic record
Abstract
Abstract The formation of the stellar mass within galaxy cluster cores is a poorly understood process. It features the complicated physics of cooling flows, active galactic nucleus feedback, star formation, and more. Here we study the growth of the stellar mass in the vicinity of the brightest cluster galaxy (BCG) in a z = 1.7 cluster, SpARCS1049+56. We synthesize a reanalysis of existing Hubble Space Telescope imaging, a previously published measurement of the star formation rate, and the results of new radio molecular gas spectroscopy. These analyses represent the past, present, and future star formation, respectively, within this system. We show that a large amount of stellar mass—between (2.2 ± 0.5) × 1010 M ⊙ and (6.6 ± 1.2) × 1010 M ⊙ depending on the data processing—exists in a long and clumpy tail-like structure that lies roughly 12 kpc off the BCG. Spatially coincident with this stellar mass is a similarly massive reservoir ((1.0 ± 0.7) × 1011 M ⊙) of molecular gas that we suggest is the fuel for the immense star formation rate of 860 ± 130 M ⊙ yr−1, as measured by infrared observations. Hlavacek-Larrondo et al. surmised that massive, runaway cooling of the hot intracluster X-ray gas was feeding this star formation, a process that had not been observed before at high redshift. We conclude, based on the amount of fuel and current stars, that this event may be rare in the lifetime of a cluster, producing roughly 15%–21% of the intracluster light mass in one go, though perhaps a common event for all galaxy clusters.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".