THREE-DIMENSIONAL STELLAR KINEMATICS AT THE GALACTIC CENTER: MEASURING THE NUCLEAR STAR CLUSTER SPATIAL DENSITY PROFILE, BLACK HOLE MASS, AND DISTANCE
Bibliographic record
Abstract
We present 3D kinematic observations of stars within the central 0.5 pc of\nthe Milky Way nuclear star cluster using adaptive optics imaging and\nspectroscopy from the Keck telescopes. Recent observations have shown that the\ncluster has a shallower surface density profile than expected for a dynamically\nrelaxed cusp, leading to important implications for its formation and\nevolution. However, the true three dimensional profile of the cluster is\nunknown due to the difficulty in de-projecting the stellar number counts. Here,\nwe use spherical Jeans modeling of individual proper motions and radial\nvelocities to constrain for the first time, the de-projected spatial density\nprofile, cluster velocity anisotropy, black hole mass ($M_\\mathrm{BH}$), and\ndistance to the Galactic center ($R_0$) simultaneously. We find that the inner\nstellar density profile of the late-type stars, $\\rho(r)\\propto r^{-\\gamma}$ to\nhave a power law slope $\\gamma=0.05_{-0.60}^{+0.29}$, much more shallow than\nthe frequently assumed Bahcall $\\&$ Wolf slope of $\\gamma=7/4$. The measured\nslope will significantly affect dynamical predictions involving the cluster,\nsuch as the dynamical friction time scale. The cluster core must be larger than\n0.5 pc, which disfavors some scenarios for its origin. Our measurement of\n$M_\\mathrm{BH}=5.76_{-1.26}^{+1.76}\\times10^6$ $M_\\odot$ and\n$R_0=8.92_{-0.55}^{+0.58}$ kpc is consistent with that derived from stellar\norbits within 1$^{\\prime\\prime}$ of Sgr A*. When combined with the orbit of\nS0-2, the uncertainty on $R_0$ is reduced by 30% ($8.46_{-0.38}^{+0.42}$ kpc).\nWe suggest that the MW NSC can be used in the future in combination with\nstellar orbits to significantly improve constraints on $R_0$.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".