A PRIMAL view of the Milky Way, made possible by Gaia and M2M modelling

TL;DR

This paper introduces PRIMAL, a novel made-to-measure algorithm that models the Milky Way's structure and kinematics using Gaia-like data, effectively recovering key galactic features despite observational challenges.

Contribution

The paper presents PRIMAL, an innovative M2M algorithm that dynamically adjusts particle masses and potential to accurately model the Galactic disc from mock Gaia data.

Findings

PRIMAL successfully recovers the Milky Way's barred spiral structure.

The method accurately estimates the bar's pattern speed.

It remains effective despite extinction and observational errors.

Abstract

We have developed our original made-to-measure (M2M) algorithm, PRIMAL, with the aim of modelling the Galactic disc from upcoming Gaia data. From a Milky Way like N-body disc galaxy simulation, we have created mock Gaia data using M0III stars as tracers, taking into account extinction and the expected Gaia errors. In PRIMAL, observables calculated from the N-body model are compared with the target stars, at the position of the target stars. Using PRIMAL, the masses of the N-body model particles are changed to reproduce the target mock data, and the gravitational potential is automatically adjusted by the changing mass of the model particles. We have also adopted a new resampling scheme for the model particles to keep the mass resolution of the N-body model relatively constant. We have applied PRIMAL to this mock Gaia data and we show that PRIMAL can recover the structure and kinematics of a Milky Way like barred spiral disc, along with the apparent bar structure and pattern speed of the bar despite the galactic extinction and the observational errors.