Linking Galaxies to Dark Matter Halos at z ~ 1: Dependence of Galaxy Clustering on Stellar Mass and Specific Star Formation Rat
Bibliographic record
Abstract
We study the dependence of angular two-point correlation functions on stellar mass (M*) and specific star formation rate (sSFR) of M<sub>*</sub> 10<sup>10</sup> M<sub>⊙</sub> galaxies at z ∼ 1. The data from the UK Infrared Telescope Infrared Deep Sky Survey Deep eXtragalactic Survey and Canada–France–Hawaii Telescope Legacy Survey cover 8.2 deg<sup>2</sup> sample scales larger than 100 h <sup>-1</sup> Mpc at z ∼ 1, allowing us to investigate the correlation between clustering, M<sub>*</sub>/M<sub>halo</sub> ratio. The ratio for central galaxies shows a peak at M<sub>halo</sub>~ 10<sup>12</sup>h<sup>-1</sup>M<sub>⊙</sub>, and satellites predominantly contribute to the total stellar mass in cluster environments with M<sub>*</sub>/M<sub>halo</sub> values of 0.01–0.02. Using star-forming galaxies split by sSFR, we find that main sequence galaxies (log sSFR/yr<sup>-1</sup>~9) are mainly central galaxies in ~10<sup>12.5</sup>h<sup>-1</sup>M<sub>⊙</sub> halos with the lowest clustering amplitude, while lower sSFR galaxies consist of a mixture of both central and satellite galaxies where those with the lowest M<sub>*</sub> are predominantly satellites influenced by their environment. Considering the lowest M<sub>halo</sub> samples in each M<sub>*</sub> bin, massive central galaxies reside in more massive halos with lower sSFRs than low mass ones, indicating star-forming central galaxies evolve from a low M<sub>*</sub>–high sSFR to a high M<sub>*</sub>–low sSFR regime. We also find that the most rapidly star-forming galaxies (log sSFR/yr <sup>-1</sup>> -8.5) are in more massive halos than main sequence ones, possibly implying galaxy mergers in dense environments are driving the active star formation. These results support the conclusion that the majority of star-forming galaxies follow secular evolution through the sustained but decreasing formation of stars.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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; both teacher heads agree on what is shown here.
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".