Dynamic Made-To-Measure: A Method of Making Dynamically Self-Consistent Triaxial Dark Matter Halos
Abstract
In this thesis we modify the Made-To-Measure (M2M) algorithm to be dynamically selfconsistent
and apply it to the problem of generating equilibrium collisionless systems with
non-spherical halos. Our M2M algorithm systematically adjusts the masses of particles in a
system slowly, keeping the system in equilibrium. The adjustments are performed according
to some given constraints and proceed until pseudo-observations of the system match
the constraints. We use this algorithm to generate isolated triaxial dark matter halos and
disk-halo systems with prolate halos. The isolated triaxial dark-matter halo simulations
provide a test for the algorithm. These tests show that our algorithm can generate equilibrium
collisionless systems with non-spherical halos, but we also find that our algorithm
requires a large amount of computational time to converge to the final target system. The
disk-halo simulations show that prolate halos modify the morphology and velocity profile
of dark matter dominated disks that cause errors in the measurement of the inclination and
understanding the rotation curve. As a result of these errors, a mass estimate from the
observed rotation curve of a disk in a prolate halo will depend on the observers position
relative to the disk. The mass estimates from the same disk observed at different positions
may vary by up to a factor of three.