Shell galaxies as laboratories for testing MOND
Bibliographic record
Abstract
Tests of MOND in elliptical galaxies are relatively rare because they often lack kinematic tracers in the regions where MOND effects are significant. Stellar shells observed in many elliptical galaxies offer a promising way to constrain their gravitational fields. Shells appear as glowing arcs around the host galaxy, with radii observed up to ∼100 kpc. The stars in axially symmetric shell systems move in nearly radial orbits. The radial distributions of shell locations and the spectra of stars in shells can be used to constrain the gravitational potential of their host galaxy. The symmetrical shell systems, being especially suitable for these studies, occur in approximately 3% of all early-type galaxies. Hence, if we overcome several problems (e.g., multiple shell generations present in the system, shells missed by observations, blurry shell edges, dynamical friction during the merger), the shells substantially increase the number of ellipticals in which MOND can be tested up to large radii. In this paper, we review our work on shell galaxies in MOND. We summarize Bílek et al. (Astron. Astrophys. 559, A110 (2013)), where we demonstrated the consistency of shell radii in an elliptical NGC 3923 with MOND, and Bílek et al. (arXiv:1404.1109. 2014), in which we predicted a giant (∼200 kpc), yet undiscovered shell of NGC 3923. We explain the shell identification method that was used in these two papers. We further describe the expected shape of line profiles in shell spectra in MOND, which is very special because of the direct relation of the gravitational field and baryonic matter distribution (Bílek et al. 2014, in preparation).
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".