Detection of a Substantial Molecular Gas Reservoir in a Brightest Cluster Galaxy at z = 1.7
Bibliographic record
Abstract
Abstract We report the detection of CO(2–1) emission coincident with the brightest cluster galaxy (BCG) of the high-redshift galaxy cluster SpARCS1049+56, with the Redshift Search Receiver (RSR) on the Large Millimeter Telescope (LMT). We confirm a spectroscopic redshift for the gas of z = 1.7091 ± 0.0004, which is consistent with the systemic redshift of the cluster galaxies of z = 1.709. The line is well fit by a single-component Gaussian with an RSR-resolution-corrected FWHM of 569 ± 63 km s−1. We see no evidence for multiple velocity components in the gas, as might be expected from the multiple image components seen in near-infrared imaging with the Hubble Space Telescope. We measure the integrated flux of the line to be 3.6 ± 0.3 Jy km s−1, and using = 0.8 M ⊙ (K km s−1 pc2)−1, we estimate a total molecular gas mass of 1.1 ± 0.1 × 1011 M ⊙ and a M H2/M ⋆ ∼ 0.4. This is the largest gas reservoir detected in a BCG above z > 1 to date. Given the infrared-estimated star formation rate of 860 ± 130 M ⊙ yr−1, this corresponds to a gas depletion timescale of ∼0.1 Gyr. We discuss several possible mechanisms for depositing such a large gas reservoir to the cluster center—e.g., a cooling flow, a major galaxy–galaxy merger, or the stripping of gas from several galaxies—but conclude that these LMT data are not sufficient to differentiate between them.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".