After the data has been compiled, the program attempts to find an optical depth for the star. Using this optical depth guess as a starting point, Superfit searches through models until it finds one that fits better than all the others. Once the best fit was found, the optical depth and grain composition, as well as input observations of number and source of data points, relative errors and so forth, are extracted and catalogued. Presumably the poorer fits are a symptom of not having enough models and, with more models to choose among, the fits would look better. Furthermore we can see from Fig 6 that our initial method of estimating optical depth correlates fairly well with the numbers chosen by Superfit.
Most sources fall within less than an order of magnitude of the predicted values.
Acknowledgements None of this work would have been possible without the generous support of the University of Kentucky Center for Computational Science and its director Dr. John Connolly. My advisor, Dr. Moshe Elitzur and Dr. Zeljko Ivezic of the University of Kentucky were the originators of the project and produced most of the actual science. Draine, B. T. And Lee, H. M. 1984, ApJ, 285,89. An example of stellar dust evolution tracks plotted on a color-color diagram. The solid lines represent amorphous carbon dust while the dashed lines are silicates.