Discovery of a Little Red Dot Candidate at <i>z</i> ≳ 10 in COSMOS-web Based on MIRI-NIRCam Selection
Bibliographic record
Abstract
Abstract JWST has revealed a new high-redshift population called little red dots (LRDs). Since LRDs may be in the early phase of black hole growth, identifying them in the early Universe is crucial for understanding the formation of the first supermassive black holes. However, no robust LRD candidates have been identified at z > 10, because commonly used NIRCam photometry covers wavelengths up to ∼5 μ m and is insufficient to capture the characteristic V-shaped spectral energy distributions (SEDs) of LRDs. In this study, we present the first search for z ≳ 10 LRD candidates using both NIRCam and MIRI imaging from COSMOS-Web, which provides the largest joint NIRCam-MIRI coverage to date (0.20 deg 2 ). Taking advantage of MIRI/F770W to remove contaminants, we identify one robust candidate, CW-LRD-z10 at z phot = 10 . 5 − 0.6 + 0.7 with M UV = − 19 . 9 − 0.2 + 0.1 mag . CW-LRD-z10 exhibits a compact morphology, a distinct V-shaped SED, and a nondetection in F115W, all consistent with being an LRD at z ∼ 10. Based on this discovery, we place the first constraint on the number density of LRDs at z ∼ 10 with M UV ∼ −20 of 1 . 2 − 1.0 + 2.7 × 1 0 − 6 Mpc − 3 mag − 1 , suggesting that the fraction of LRDs among the overall galaxy population increases with redshift, reaching ∼3% at z ∼ 10. Although deep spectroscopy is necessary to confirm the redshift and the nature of CW-LRD-z10, our results imply that LRDs may be a common population at z > 10, playing a key role in the first supermassive black hole formation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".