The total mass of the Large Magellanic Cloud from its perturbation on the Orphan stream
Bibliographic record
Abstract
In a companion paper by Koposov et al., RR Lyrae from Gaia Data Release 2 are used to demonstrate that stars in the Orphan stream have velocity vectors significantly misaligned with the stream track, suggesting that it has received a large gravitational perturbation from a satellite of the Milky Way. We argue that such a mismatch cannot arise due to any realistic static Milky Way potential and then explore the perturbative effects of the Large Magellanic Cloud (LMC). We find that the LMC can produce precisely, the observed motion-track mismatch and we therefore use the Orphan stream to measure the mass of the Cloud. We simultaneously fit the Milky Way and LMC potentials and infer that a total LMC mass of 1.38 +0.27 -0.24 10 11 M is required to bend the Orphan stream, showing for the first time that the LMC has a large and measurable effect on structures orbiting the Milky Way. This has far-reaching consequences for any technique which assumes that tracers are orbiting a static Milky Way. Furthermore, we measure the Milky Way mass within 50 kpc to be 3.80 +0.14 -0.11 10 11 M . Finally, we use these results to predict that, due to the reflex motion of the Milky Way in response to the LMC, the outskirts of the Milky Way's stellar halo should exhibit a bulk, upwards motion.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".