An Automated Approach to the Study and Classification of Colliding and Interacting Galaxies
Steven Boada · 2009
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.