<i>S</i>5: Probing the Milky Way and Magellanic Clouds potentials with the 6D map of the Orphan–Chenab stream
Bibliographic record
Abstract
ABSTRACT We present a 6D map of the Orphan–Chenab (OC) stream by combining the data from Southern Stellar Stream Spectroscopic Survey (S5) and Gaia. We reconstruct the proper motion, radial velocity, distance, on-sky track, and stellar density along the stream with spline models. The stream has a total luminosity of MV = −8.2 and metallicity of [Fe/H] = −1.9, similar to classical Milky Way (MW) satellites like Draco. The stream shows drastic changes in its physical width varying from 200 pc to 1 kpc, but a constant line-of-sight velocity dispersion of 5 $\mathrm{km\, s^{-1}}$. Despite the large apparent variation in the stellar number density along the stream, the flow rate of stars along the stream is remarkably constant. We model the 6D stream track by a Lagrange-point stripping method with a flexible MW potential in the presence of a moving extended Large Magellanic Cloud (LMC). This allows us to constrain the mass profile of the MW within the distance range 15.6 < r < 55.5 kpc, with the best measured enclosed mass of $(2.85\pm 0.1)\times 10^{11}\, \mathrm{\, M_\odot }$ within 32.4 kpc. Our stream measurements are highly sensitive to the LMC mass profile with the most precise measurement of its enclosed mass made at 32.8 kpc, $(7.02\pm 0.9)\times 10^{10}\, {\rm M}_\odot$. We also detect that the LMC dark matter halo extends to at least 53 kpc. The fitting of the OC stream allows us to constrain the past LMC trajectory and the degree of dynamical friction it experienced. We demonstrate that the stars in the OC stream show large energy and angular momentum spreads caused by LMC perturbation.
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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 | 0.000 |
| 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) | 0.003 | 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".