Discovery of a faint, star-forming, multiply lensed, Lyman-<i>α</i>blob
Bibliographic record
Abstract
We report the discovery of a multiply lensed Lyman-α blob (LAB) behind the galaxy cluster AS1063 using the Multi Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope (VLT). The background source is at z = 3.117 and is intrinsically faint compared to almost all previously reported LABs. We used our highly precise strong lensing model to reconstruct the source properties, and we find an intrinsic luminosity of LLyα = 1.9 × 1042 erg s-1, extending to 33 kpc. We find that the LAB is associated with a group of galaxies, and possibly a protocluster, in agreement with previous studies that find LABs in overdensities. In addition to Lyman-α (Lyα) emission, we find C iv, He ii, and O iii] ultraviolet (UV) emission lines arising from the centre of the nebula. We used the compactness of these lines in combination with the line ratios to conclude that the Lyα nebula is likely powered by embedded star formation. Resonant scattering of the Lyα photons then produces the extended shape of the emission. Thanks to the combined power of MUSE and strong gravitational lensing, we are now able to probe the circumgalatic medium of sub-L∗ galaxies at z ≈ 3.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".