# Self-consistent Modelling of the Milky Way using Gaia data

## TL;DR

This paper discusses using angle/action distribution function models, optimized with Gaia and other survey data, to accurately map the Milky Way's matter distribution.

## Contribution

It introduces a self-consistent modeling approach that leverages Gaia data to improve the accuracy of Milky Way mass distribution estimates.

## Key findings

- Enhanced accuracy in Milky Way modeling with Gaia data.
- Demonstrated the importance of full selection function in modeling.
- Improved understanding of the Galaxy's matter distribution.

## Abstract

Angle/action based distribution function (DF) models can be optimised based on how well they reproduce observations thus revealing the current matter distribution in the Milky Way. Gaia data combined with data from other surveys, e.g. the RAVE/TGAS sample, and its full selection function will greatly improve their accuracy.