STELLAR POPULATIONS OF Lyα EMITTERS AT<i>z</i>= 4.86: A COMPARISON TO<i>z</i>∼ 5 LYMAN BREAK GALAXIES
Bibliographic record
Abstract
(abridged) We present a study of stellar population of LAEs at z=4.86 in GOODS-N and its flanking field. With the publicly available IRAC data in GOODS-N and further IRAC observations in the flanking fields, we select five LAEs which are not contaminated by neighboring objects in IRAC images and construct their observed SEDs with I_c, z', IRAC 3.6micron, and 4.5micron band photometry. The SEDs cover the rest-frame UV to optical wavelengths. We derive stellar masses, ages, color excesses, and star formation rates of five LAEs using SED fitting method. Assuming the constant star formation history, we find that the stellar masses range from 10^8 to $10^{10} Msun with the median value of 2.5x10^9 Msun. The derived ages range from very young ages (7.4 Myr) to 437 Myr with a median age of 25 Myr. The color excess E(B-V) are between 0.1-0.4 mag. Star formation rates are 55-209 Msun/yr. A comparison of the stellar populations is made between three LAEs and 88 LBGs selected at the same redshift, in the same observed field, and down to the same limit of the rest-frame UV luminosity. These three LAEs are the brightest and reddest samples among the whole LAE samples at z=4.86. The LAEs distribute at the relatively faint part of UV-luminosity distribution of LBGs. Deriving the stellar properties of the LBGs by fitting their SEDs with the same model ensures that model difference does not affect the comparison. It is found that the stellar properties of the LAEs lie on distributions of those of LBGs. On average, the LAEs show less dust extinction, and lower star formation rates than LBGs, while the stellar mass of LAEs nearly lies in the middle part of the mass distribution of LBGs. However, the stellar properties of LAEs and LBGs are similar at the fixed UV or optical luminosity. We also examine the relations between the output properties from the SED fitting and the rest-frame Lya equivalent width.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".