A new implementation of the Schwarzschild method for constructing observationally-driven dynamical models of galaxies of all morphological types

TL;DR

This paper introduces Forstand, a new efficient code for constructing galaxy dynamical models using the Schwarzschild method, capable of handling all galaxy types and accurately recovering bar pattern speeds from observational data.

Contribution

The paper presents a novel implementation of the Schwarzschild method, applicable to all galaxy morphologies, with improved efficiency and public availability.

Findings

Pattern speed of bars can be recovered with 10-20% accuracy.

The method works regardless of galaxy orientation if 3D shape is known.

The implementation is validated with mock N-body datasets.

Abstract

We present Forstand, a new code for constructing dynamical models of galaxies with the Schwarzschild orbit-superposition method. These models are constrained by line-of-sight kinematic observations and applicable to galaxies of all morphological types, including disks and triaxial rotating bars. Our implementation has several novel and improved features, is computationally efficient, and made publicly available. Using mock datasets taken from N-body simulations, we demonstrate that the pattern speed of a bar can be recovered with an accuracy of 10-20%, regardless of orientation, if the 3D shape of the galaxy is known or inferred correctly.