Measuring dark matter by modeling interacting galaxies

TL;DR

This paper introduces a genetic algorithm-based modeling method to analyze interacting galaxies, enabling the measurement of dark matter content in regions beyond traditional equilibrium assumptions.

Contribution

The study presents a novel genetic algorithm approach for modeling complex interacting galaxy systems to constrain their dark matter distribution.

Findings

Successfully modeled tidal tails and stellar streams to estimate dark matter content.

Demonstrated applicability across various systems, including the Milky Way, M51, and the Antennae.

Provided insights into the dynamical history of observed galaxy interactions.

Abstract

The dark matter content of galaxies is usually determined from galaxies in dynamical equilibrium, mainly from rotationally supported galactic components. Such determinations restrict measurements to special regions in galaxies, e.g. the galactic plane(s), whereas other regions are not probed at all. Interacting galaxies offer an alternative, because extended tidal tails often probe outer or off-plane regions of galaxies. However, these systems are neither in dynamical equilibrium nor simple, because they are composed of two or more galaxies, by this increasing the associated parameter space.We present our genetic algorithm based modeling tool which allows to investigate the extended parameter space of interacting galaxies. From these studies, we derive the dynamical history of (well observed) galaxies. Among other parameters we constrain the dark matter content of the involved galaxies. We demonstrate the applicability of this strategy with examples ranging from stellar streams around theMilkyWay to extended tidal tails, from proto-typical binary galaxies (like M51 or the Antennae system) to small group of galaxies.