Self-consistent models of our Galaxy

TL;DR

This paper introduces a self-consistent, action-based modeling framework for the Milky Way, integrating stellar dynamics, chemistry, and dark matter to match Gaia data and predict Galactic structure.

Contribution

It presents a novel class of self-consistent Galaxy models using action-based distribution functions for multiple stellar components and dark matter, incorporating chemistry and Gaia data.

Findings

Model accurately reproduces stellar kinematics and densities.

Dark halo structure prior to baryonic infall determined.

High-alpha stars confined to specific orbital parameters.

Abstract

A new class of models of stellar discs is introduced and used to build a self-consistent model of our Galaxy. The model is defined by the parameters that specify the action-based distribution functions (DFs) f(J) of four stellar discs (three thin-disc age cohorts and a thick disc), spheroidal bulge and spheroidal stellar and dark haloes. From these DFs plus a specified distribution of gas, we solve for the densities of stars and dark matter and the potential they generate. The principal observational constraints are the kinematics of stars with Gaia RVS data and the density of stars in the column above the Sun. The model predicts the density and kinematics of stars and dark matter throughout the Galaxy. We determine the structure of the dark halo prior to the infall of baryons. A simple extension of the DFs of stellar components to include chemistry allows the model to reproduce the way the Galaxy's chemistry is observed to vary in the (R,z) plane. Surprisingly, the data indicate that high-alpha stars are confined to orbits with J_z >~ 50 kpc km/s. The code used to create the model is available on Github.