A large population of strongly lensed faint submillimetre galaxies in future dark energy surveys inferred from <i>JWST</i> imaging
Bibliographic record
Abstract
ABSTRACT Bright galaxies at submillimetre wavelengths from Herschel are now well known to be predominantly strongly gravitationally lensed. The same models that successfully predicted this strongly lensed population also predict about 1 per cent of faint 450 μm-selected galaxies from deep James Clerk Maxwell Telescope (JCMT) surveys will also be strongly lensed. Follow-up ALMA campaigns have so far found one potential lens candidate, but without clear compelling evidence, for example, from lensing arcs. Here, we report the discovery of a compelling gravitational lens system confirming the lensing population predictions, with a zs = 3.4 ± 0.4 submm source lensed by a zspec = 0.360 foreground galaxy within the COSMOS field, identified through public JWST imaging of a 450 μm source in the SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES) catalogue. These systems will typically be well within the detectable range of future wide-field surveys such as Euclid and Roman, and since submillimetre galaxies are predominantly very red at optical/near-infrared wavelengths, they will tend to appear in near-infrared channels only. Extrapolating to the Euclid-Wide survey, we predict tens of thousands of strongly lensed near-infrared galaxies. This will be transformative for the study of dusty star-forming galaxies at cosmic noon, but will be a contaminant population in searches for strongly lensed ultra-high-redshift galaxies in Euclid and Roman.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".