SchwarMAX delivers a fast GPU-native Schwarzschild modeling code that recovers density profiles and bar pattern speed from mock IFU data of a simulated barred galaxy.
The stellar orbit distribution in present-day galaxies inferred from the CALIFA survey
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abstract
Galaxy formation entails the hierarchical assembly of mass, along with the condensation of baryons and the ensuing, self-regulating star formation. The stars form a collisionless system whose orbit distribution retains dynamical memory that can constrain a galaxy's formation history. The ordered-rotation dominated orbits with near maximum circularity $\lambda_z \simeq1$ and the random-motion dominated orbits with low circularity $\lambda_z \simeq0$ are called kinematically cold and kinematically hot, respectively. The fraction of stars on `cold' orbits, compared to the fraction of stars on `hot' orbits, speaks directly to the quiescence or violence of the galaxies' formation histories. Here we present such orbit distributions, derived from stellar kinematic maps via orbit-based modelling for a well defined, large sample of 300 nearby galaxies. The sample, drawn from the CALIFA survey, includes the main morphological galaxy types and spans the total stellar mass range from $10^{8.7}$ to $10^{11.9}$ solar masses. Our analysis derives the orbit-circularity distribution as a function of galaxy mass, $p(\lambda_z~|~M_\star)$, and its volume-averaged total distribution, $p(\lambda_z)$. We find that across most of the considered mass range and across morphological types, there are more stars on `warm' orbits defined as $0.25\le \lambda_z \le 0.8$ than on either `cold' or `hot' orbits. This orbit-based "Hubble diagram" provides a benchmark for galaxy formation simulations in a cosmological context.
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SchwarMAX: a GPU-friendly Schwarzschild orbit-superposition modelling framework
SchwarMAX delivers a fast GPU-native Schwarzschild modeling code that recovers density profiles and bar pattern speed from mock IFU data of a simulated barred galaxy.