Presentation #332.07 in the session The Sun and Solar System II.
Over 800 outer Solar System objects have been identified in the Dark Energy Survey data, making this one of the largest catalogs of trans-Neptunian objects (TNOs) to date. A unique feature of this data set is that the search was conducted using images taken in the grizY filters, and so these objects collectively have 30 thousand photometric measurements in these bands. I briefly introduce the dedicated scene modeling photometry processing used for these measurements, a technique that uses information from all images taken by the survey of a given region of the sky to obtain an optimal photometric measurement of each source, and the methodology used to obtain color estimates for each object. I discuss a rigorous data driven study of these colors, combining model regression and principal component analysis to determine which photometric bands have information of the object’s composition. A subsequent mixture model based clustering technique that accounts for measurement uncertainties and the discovery efficiency as a function of magnitude, color and orbital elements is used to estimate a color distribution as well as the optimal number of color clusters for each dynamical class of the trans-Neptunian region. Preliminary results indicate that all photometric bands have unique information about each object’s surface, and that the color distribution vary as a function of dynamical class. The final result will also include a taxonomical classification derived from first principles for these objects.