Dynamic Made-To-Measure: A Method of Making Dynamically Self-Consistent Triaxial Dark Matter Halos
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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.