The Rest-frame Optical (900 nm) Galaxy Luminosity Function at z ~ 4-7: Abundance Matching Points to Limited Evolution in the M_STAR/M_HALO Ratio at z >= 4
Bibliographic record
Abstract
We present the first determination of the galaxy luminosity function (LF) at z~4, 5, 6 and 7 in the rest-frame optical at lambda_rest~900 nm (z' band). The rest-frame optical light traces the content in low-mass evolved stars (~stellar mass - Mstar), minimizing potential measurement biases for Mstar. Moreover it is less affected by nebular line emission contamination and dust attenuation, is independent of stellar population models, and can be probed up to z~8 through Spitzer/IRAC. Our analysis leverages the unique full depth Spitzer/IRAC 3.6um-to-8.0um data over the CANDELS/GOODS-N, CANDELS/GOODS-S and COSMOS/UltraVISTA fields. We find that at absolute magnitudes M_z' fainter than >-23 mag, M_z' linearly correlates with M_UV,1600. At brighter M_z', M_UV,1600 presents a turnover, suggesting that the stellar mass-to-light ratio Mstar/L_UV,1600 could be characterised by a very broad range of values at high stellar masses. Median-stacking analysis recovers a Mstar/L_z' roughly independent on M_z' for M_z'>-23 mag, but exponentially increasing at brighter magnitudes. We find that the evolution of the LF marginally prefers a pure evolution in luminosity over a pure evolution in density, with the characteristic luminosity decreasing by a factor ~5x between z~4 and z~7. Direct application of the recovered Mstar/L_z' generates stellar mass functions consistent with average measurements from the literature. Measurements of the stellar-to-halo mass ratio at fixed cumulative number density show that it is roughly constant with redshift for Mh>10^12Msun. This is also supported by the fact that the evolution of the LF at 4<z<7 can be accounted for by a rigid displacement in luminosity corresponding to the evolution of the halo mass from abundance matching.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".