An Automated Approach to the Study and Classification of Colliding and Interacting Galaxies

Colliding galaxies are perhaps the greatest events changing and evolving our Universe. Consequently, the need for an understanding of how that interaction originated is very important. This thesis presents a framework in which the study of these events can be conducted in a timely and efficient manner. A genetic algorithm coupled with an initial conditions generator, a physics engine and an analysis package performs an automated search to visually match an unknown galactic interaction with a known event, thus providing the starting conditions that created such an interaction.