The luminosity function, halo masses and stellar masses of luminous Lyman-break galaxies at redshifts 5 < z < 6
Bibliographic record
Abstract
We present the results of a study of a large sample of luminous (z′AB < 26) Lyman-break galaxies (LBGs) in the redshift interval 4.7 < z < 6.3, selected from a contiguous 0.63 deg2 area covered by the UKIRT Infrared Deep Sky Survey Ultra Deep Survey and the Subaru XMM–Newton Survey. Utilizing the large area coverage and the excellent available optical+near-infrared data, we use a photometric redshift analysis to derive a new, robust, measurement of the bright end (L≥L★) of the ultraviolet-selected luminosity function at high redshift. When combined with literature studies of the fainter LBG population, our new sample provides improved constraints on the luminosity function of redshift 5 < z < 6 LBGs over the luminosity range 0.1L★≲L≲ 10L★. A maximum likelihood analysis returns best-fitting Schechter function parameters of M★1500=−20.73 ± 0.11, φ★= 0.0009 ± 0.0002 Mpc−3 and α=−1.66 ± 0.06 for the luminosity function at z= 5, and M★1500=−20.04 ± 0.12, φ★= 0.0018 ± 0.0005 Mpc−3 and α=−1.71 ± 0.11 at z= 6. In addition, an analysis of the angular clustering properties of our LBG sample demonstrates that luminous 5 < z < 6 LBGs are strongly clustered (r0= 8.1+2.1−1.5h−170 Mpc), and consistent with the occupation of dark matter haloes with masses of ≃1011.5−12 M⊙. Moreover, by stacking the available multiwavelength imaging data for the high-redshift LBGs, it is possible to place useful constraints on their typical stellar mass. The results of this analysis suggest that luminous LBGs at 5 < z < 6 have an average stellar mass of log10(M/M⊙) = 10.0+0.2−0.4, consistent with the results of the clustering analysis assuming plausible values for the ratio of stellar to dark matter. Finally, by combining our luminosity function results with those of the stacking analysis we derive estimates of ≃1 × 107 and ≃4 × 106 M⊙ Mpc−3 for the stellar mass density at z≃ 5 and 6, respectively.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".