SMART: A new implementation of Schwarzschild's Orbit Superposition technique for triaxial galaxies and its application to an N-body merger simulation
Bianca Neureiter, Jens Thomas, Roberto Saglia, Ralf Bender, Fabrizio, Finozzi, Aliaksei Krukau, Thorsten Naab, Antti Rantala, Matteo Frigo

TL;DR
SMART is a novel 3D Schwarzschild orbit superposition method that accurately models triaxial galaxies and recovers key properties like black hole mass and dark matter content from N-body simulations.
Contribution
It introduces a new implementation of the Schwarzschild method with a 5D orbital space, capable of fitting full LOSVDs and handling non-parametric densities in triaxial galaxies.
Findings
Achieves ~1% precision in velocity moments and anisotropy profiles.
Recovers black hole and dark matter parameters within a few percent.
Reconstructs full intrinsic velocity distributions, revealing stable orbit rotations.
Abstract
We present SMART, a new 3D implementation of the Schwarzschild Method and its application to a triaxial N-body merger simulation. SMART fits full line-of-sight velocity distributions (LOSVDs) to determine the viewing angles, black hole, stellar and dark matter (DM) masses and the stellar orbit distribution of galaxies. Our model uses a 5D orbital starting space to ensure a representative set of stellar trajectories adaptable to the integrals-of-motion space and it is designed to deal with non-parametric stellar and DM densities. SMART's efficiency is demonstrated by application to a realistic N-body merger simulation including supermassive black holes which we model from five different projections. When providing the true viewing angles, 3D stellar luminosity profile and normalized DM halo, we can (i) reproduce the intrinsic velocity moments and anisotropy profile with a precision of…
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.
