The Atlas3D project - XII. Recovery of the mass-to-light ratio of simulated early-type barred galaxies with axisymmetric dynamical models
Pierre-Yves Lablanche, Michele Cappellari, Eric Emsellem, Frederic, Bournaud, Leo Michel-Dansac, Katherine Alatalo, Leo Blitz, Maxime Bois,, Martin Bureau, Roger L. Davies, Timothy A. Davis, P. T. de Zeeuw,, Pierre-Alain Duc, Sadegh Khochfar, Davor Krajnovic, Harald Kuntschner,

TL;DR
This study assesses how well axisymmetric dynamical models recover the mass-to-light ratio in simulated early-type barred galaxies, highlighting biases due to non-axisymmetry and projection effects.
Contribution
It demonstrates the limitations and biases of axisymmetric models like JAM when applied to non-axisymmetric barred galaxy simulations.
Findings
Inclination is well recovered by models.
M/L is accurately recovered in unbarred galaxies at moderate inclinations.
Barred galaxies show up to 15% bias in M/L depending on bar orientation.
Abstract
We investigate the accuracy in the recovery of the stellar dynamics of barred galaxies when using axisymmetric dynamical models. We do this by trying to recover the mass-to-light ratio (M/L) and the anisotropy of realistic galaxy simulations using the Jeans Anisotropic Multi-Gaussian Expansion (JAM) method. However, given that the biases we find are mostly due to an application of an axisymmetric modeling algorithm to a non-axisymmetric system and in particular to inaccuracies in the de-projected mass model, our results are relevant for general axisymmetric modelling methods. We run N-body collisionless simulations to build a library with various luminosity distribution, constructed to mimic real individual galaxies, with realistic anisotropy. The final result of our evolved library of simulations contains both barred and unbarred galaxies. The JAM method assumes an axisymmetric mass…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
