The VIMOS-VLT Deep Survey - The evolution of galaxy clustering per spectral type to z~1.5
Bibliographic record
Abstract
We measure the evolution of clustering for galaxies with different spectral types from 6495 galaxies with 17.5<=I_AB<=24 and measured spectroscopic redshift in the first epoch VIMOS-VLT Deep Survey. We classify our sample into 4 classes, based on the fit of well-defined galaxy spectral energy distributions on observed multi-color data. We measure the projected function wp(rp) and estimate the best-fit parameters for a power-law real-space correlation function. We find the clustering of early-spectral-type galaxies to be markedly stronger than that of late-type galaxies at all redshifts up to z<=1.2. At z~0.8, early-type galaxies display a correlation length r_0=4.8+/-0.9h^{-1}Mpc, while late types have r_0=2.5+/-0.4h^{-1}Mpc. The clustering of these objects increases up to r_0=3.42+/-0.7h^{-1}Mpc for z~1.4. The relative bias between early- and late-type galaxies within our magnitude-limited survey remains approximately constant with b~1.7-1.8 from z~=0.2 up to z~=1, with indications for a decrease at z>1.2, due to the growth in clustering of the star-forming population. We find similar results when splitting the sample into `red' and `blue' galaxies using the observed color bi-modality. When compared to the expected linear growth of mass fluctuations, a natural interpretation of these observations is that: (a) the assembly of massive early type galaxies is already mostly complete in the densest dark matter halos at z~=1; (b) luminous late-type galaxies are located in higher-density, more clustered regions of the Universe at z~=1.5 than at present, indicating that star formation activity is progressively increasing, going back in time, in the higher-density peaks that today are mostly dominated by old galaxies.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".