Investigating Bar Structure of Disc Galaxies via PRIMAL: A PaRtIcle-by-particle M2M ALgorithm

TL;DR

This paper introduces PRIMAL, an enhanced particle-by-particle M2M algorithm for modeling barred galactic discs, capable of accurately recovering structural and kinematic features from simulated data.

Contribution

The paper presents a novel likelihood-based velocity constraint in PRIMAL and demonstrates its effectiveness in recovering galactic bar structures and dynamics from N-body simulations.

Findings

PRIMAL accurately recovers surface density profiles.

PRIMAL reproduces velocity dispersion and rotation curves.

The method successfully identifies bar pattern speed and structure.

Abstract

We have modified our particle-by-particle adaptation of the made-to-measure (M2M) method, with the aim of modelling the Galactic disc from upcoming Galactic stellar survey data. In our new particle-by-particle M2M algorithm, PRIMAL, the observables of the target system are compared with those of the model galaxy at the position of the target stars, i.e. particles. The mass of the model particles are adjusted to reproduce the observables of the target system, and the gravitational potential is automatically adjusted by the changing mass of the particles. This paper builds upon our previous work, introducing likelihood-based velocity constraints in PRIMAL. In this paper we apply PRIMAL to barred disc galaxies created by a N-body simulation in a known dark matter potential, with no error in the observables. This paper demonstrates that PRIMAL can recover the radial profiles of the surface density, velocity dispersion in the radial and perpendicular directions, and the rotational velocity of the target discs, along with the apparent bar structure and pattern speed of the bar, especially when the reference frame is adjusted so that the bar angle of the target galaxy is aligned to that of the model galaxy at every timestep.