THE DEPENDENCE OF QUENCHING UPON THE INNER STRUCTURE OF GALAXIES AT 0.5 ⩽<i>z</i>< 0.8 IN THE DEEP2/AEGIS SURVEY
Bibliographic record
Abstract
The shutdown of star formation in galaxies is generally termed "quenching." Quenching may occur through a variety of processes, e.g., active galactic nucleus (AGN) feedback, stellar feedback, or the shock heating of gas in the dark matter halo. However, which mechanism(s) is, in fact, responsible for quenching is still in question. This paper addresses quenching by searching for traces of possible quenching processes through their effects on galaxy structural parameters such as stellar mass ($M_{\\ast }$), $M_{\\ast }/r_{e}$, surface stellar mass density ($\\sim M_{\\ast }/r^{2}_{e}$), and Sérsic index ($n$). We analyze the rest-frame $U - B$ color correlations versus these structural parameters using a sample of galaxies in the redshift range $0.5 \\lesssim z < 0.8$ from the DEEP2/AEGIS survey. In addition to global radii, stellar masses, and Sérsic parameters, we also use "bulge" and "disk" photometric measurements from GIM2D fits to $\\textit{HST/ACS V}$ and $I$ images. We assess the tightness of the color relationships by measuring their "overlap regions," defined as the area in color-parameter space in which red and blue galaxies overlap; the parameter that minimizes these overlap regions is considered to be the most effective color discriminator. We find that Sérsic index ($n$) has the smallest overlap region among all tested parameters and resembles a step function with a threshold value of $n$ = 2.3. There exists, however, a significant population of outliers with blue colors yet high n values that seem to contradict this behavior; they make up $\\approx$ 40% of $n$ > 2.3 galaxies. We hypothesize that their Sérsic values may be distorted by bursts of star formation, AGNs, and/or poor fits, leading us to consider central surface stellar mass density, $\\sum^{\\ast }_{1 \\:\\text{kpc}}$, as an alternative to Sérsic index. Not only does $\\sum^{\\ast }_{1 \\:\\text{kpc}}$ correct the outliers, but it also forms a tight relationship with color, suggesting that the $\\textit{innermost structure of galaxies is most physically linked with quenching}$. Furthermore, at $z \\sim 0.65$, the majority of the blue cloud galaxies cannot simply fade onto the red sequence since their GIM2D bulge masses are only half as large on average as the bulge masses of similar red sequence galaxies, thus demonstrating that stellar mass must absolutely increase at the centers of galaxies as they quench. We discuss a two-stage model for quenching in which galaxy star formation rates are controlled by their dark halos while they are still in the blue cloud and a second quenching process sets in later, associated with the central stellar mass buildup. The mass buildup is naturally explained by any non-axisymmetric features in the potential, such as those induced by mergers and/or disk instabilities. However, the identity of the second quenching agent is still unknown. We have placed our data catalog online
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".