The SWELLS survey - IV. Precision measurements of the stellar and dark matter distributions in a spiral lens galaxy
Bibliographic record
Abstract
We construct a fully self-consistent mass model for the lens galaxy SDSS J2141 at redshift 0.14, and use it to improve on previous studies by modelling its gravitational lensing effect, gas rotation curve and stellar kinematics simultaneously. We adopt a very flexible axisymmetric mass model constituted by a generalized Navarro–Frenk–White (NFW) dark matter halo and a stellar mass distribution obtained by deprojecting the multi-Gaussian expansion fit to the high-resolution K′-band laser guide star adaptive optics imaging data of the galaxy, with the (spatially constant) mass-to-light ratio as a free parameter. We model the stellar kinematics by solving the anisotropic Jeans equations. We find that the inner logarithmic slope of the dark halo is weakly constrained, i.e. , and consistent with an unmodified NFW profile; we can conclude, however, that steep profiles (γ≥ 1.5) are disfavoured (<14 per cent posterior probability). We marginalize over this parameter to infer the galaxy to have (i) a dark matter fraction within 2.2 disc radii of , independent of the galaxy stellar population, implying a maximal disc for SDSS J2141; (ii) an apparently uncontracted dark matter halo, with concentration and virial velocity , consistent with Λ cold dark matter (ΛCDM) predictions; (iii) a slightly oblate halo (), consistent with predictions from baryon-affected models. Comparing the tightly constrained gravitational stellar mass inferred from the combined analysis () with that inferred from stellar population modelling of the galaxies’ colours, and accounting for an expected cold gas fraction of 20 ± 10 per cent, we determine a preference for a Chabrier IMF over Salpeter IMF by a Bayes factor of 5.7 (corresponding to substantial evidence). We infer a value for the orbital anisotropy parameter in the meridional plane, in agreement with most studies of local disc galaxies, and ruling out at 99 per cent confidence level that the dynamics of this system can be described by a two-integral distribution function.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".