Lensed quiescent galaxies at <i>z</i> ∼ 2: What quenched their star formation?
Bibliographic record
Abstract
Abstract A key outstanding issue in galaxy evolution studies is how galaxies quench their star formation. I will present new results from our VLT/X-Shooter, ALMA and VLA campaign of a pilot sample of lensed quiescent massive galaxies at z > 1.5. Lensing magnification enables us to spatially resolve the stellar structure and kinematics of these compact galaxies, that are otherwise barely resolvable even with HST. Our deep X-Shooter spectra provided multiple absorption lines enabling strong constraints on their stellar populations, namely their star formation rates, ages, dispersions, and in some cases metallicities. Our complementary ALMA+VLA programme probes their molecular gas content through CO emission. All these observations provide unparalleled constraints on their quenching mechanisms. Our results indicate that quiescent galaxies at z ∼ 2 (1) have short star formation timescales of a few hundred Myrs; (2) have a variety of stellar morphology from exponential disks to bulges; (3) are devoid of molecular gas; and (4) host low-luminosity active galactic nuclei which may be responsible for suppressing star formation. In addition to discussing the insights gained on quenching, I will highlight how these findings bring about new questions that can be addressed with future JWST and ALMA studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".