TriOS Schwarzschild Orbit Modeling: Robustness of Parameter Inference for Masses and Shapes of Triaxial Galaxies with Supermassive Black Holes

Autor: Jacob Pilawa, Emily R. Liepold, Chung-Pei Ma
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: The Astrophysical Journal, Vol 966, Iss 2, p 205 (2024)
Druh dokumentu: article
ISSN: 1538-4357
DOI: 10.3847/1538-4357/ad3935
Popis: Evidence for the majority of the supermassive black holes in the local Universe has been obtained dynamically from stellar motions with the Schwarzschild orbit superposition method. However, there have been only a handful of studies using simulated data to examine the ability of this method to reliably recover known input black hole masses M _BH and other galaxy parameters. Here, we conduct a comprehensive assessment of the reliability of the triaxial Schwarzschild method at simultaneously determining M _BH , stellar mass-to-light ratio M */ L , dark matter mass, and three intrinsic triaxial shape parameters of simulated galaxies. For each of 25 rounds of mock observations using simulated stellar kinematics and the TriOS code, we derive best-fitting parameters and confidence intervals after a full search in the 6D parameter space with our likelihood-based model inference scheme. The two key mass parameters, M _BH and M */ L , are recovered within the 68% confidence interval, and other parameters are recovered between the 68% and 95% confidence intervals. The spatially varying velocity anisotropy of the stellar orbits is also well recovered. We explore whether the goodness-of-fit measure used for galaxy model selection in our pipeline is biased by variable complexity across the 6D parameter space. In our tests, adding a penalty term to the likelihood measure either makes little difference, or worsens the recovery in some cases.
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