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  • TriOS Schwarzschild Orbit Modeling: Robustness of Parameter Inference for Masses and Shapes of Triaxial Galaxies with Supermassive Black Holes
Title: TriOS Schwarzschild Orbit Modeling: Robustness of Parameter Inference for Masses and Shapes of Triaxial Galaxies with Supermassive Black Holes
Abstract 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 massesMBHand other galaxy parameters. Here, we conduct a comprehensive assessment of the reliability of the triaxial Schwarzschild method atsimultaneouslydeterminingMBH, stellar mass-to-light ratioM*/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 theTriOScode, 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,MBHandM*/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.  more » « less
Award ID(s):
2206307
PAR ID:
10521440
Author(s) / Creator(s):
; ;
Publisher / Repository:
IOP
Date Published:
Journal Name:
The Astrophysical Journal
Volume:
966
Issue:
2
ISSN:
0004-637X
Page Range / eLocation ID:
205
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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