Discovery of Strong Lensing by an Elliptical Galaxy at <i>z</i> = 0.0345
Bibliographic record
Abstract
We have discovered strong gravitational lensing by the galaxy ESO 325-G004, in images obtained with the Advanced Camera for Surveys on the Hubble Space Telescope . The lens galaxy is a boxy group-dominant elliptical at z = 0.0345, making this the closest known galaxy-scale lensing system. The lensed object is very blue ( B - I C ≈ 1.1), and forms two prominent arcs and a less extended third image. The Einstein radius is R Ein = 1.9 kpc (~3'' on the sky), much smaller than the lens galaxy effective radius of 8.5 kpc. Assuming a high redshift for the source, the mass within R Ein is 1.4 × 10 11 M ☉ , and the mass-to-light ratio is 1.8 ( M / L ) ☉, I . The equivalent velocity dispersion is σ lens = 310 km s -1 , in excellent agreement with the measured stellar dispersion σ v = 320 km s -1 . Modeling the lensing potential with a singular isothermal ellipse (SIE), we find close agreement with the light distribution. The best-fit SIE model reproduces the ellipticity of the lens galaxy to ~10%, and its position angle within 1°. The model predicts the broad features of the arc geometry as observed; the unlensed magnitude of the source is estimated at I C ~ 23.75. We suggest that ~60 similarly massive elliptical galaxies within z < 0.1 will exhibit such a luminous, multiply imaged source.
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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 | 0.000 |
| 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".