Modern astronomy predominantly consists of analyzing large data sets from automated sky surveys. The largest survey project, the Legacy Survey of Space and Time (LSST), is currently under construction at the Vera C. Rubin Observatory. One of its goals is to create a catalog of smaller objects such as asteroids and comets in the Solar System. The LSST Solar System Object catalog and other LSST-sourced data critically rely on the ability to predict object positions, as well as to recognize and to link previously unknown ones. Object positions are calculated with software known as integrators. There are several well-known integrators in the solar system dynamics community: JPL Horizons, OpenOrb, and OrbFit. They are credited as acceptable for calculating positions, however, they have not been rigorously compared to one another. This project addresses this issue. For my research, I built an automated system that compares the most popular integrators by testing them on a set of known objects. These objects are picked to explore both usual and unusual regions in space. The system compares the object positions by evaluating a number of metrics (e.g., on-sky distance, position vector 3D distance, and others), and will visualize the results in form of a dashboard. This allows for the assessment of various integration package suitability as a function of population to be integrated, as well as tracking their performance in an automated fashion as improvements and changes are made. The most important product of my work is the clear definition of each integrator's bounds of applications. Currently, this is the only comprehensive comparison of its kind. Using my comparison, other scientists will be able to decide what integrator to use for their specific use case. Given the broad implications, this work will prove to be invaluable to the astronomical community as a whole.

Astronomy of the 21st century is driven by large data sets collected by large automated sky surveys. The largest survey project currently being built is the Legacy Survey of Space and Time (LSST), which will be a 10-year survey of the southern sky, expected to discover 5.5 million small bodies in our Solar System. The greater scientific community needs to know what the research potential and scope of the data LSST will collect. I am building a database -- accessible at http://ls.st/ssdb -- of simulated LSST observations of asteroids in our Solar System. My work delves into simulation accuracy, big data analysis, and database management. This dataset consists of individual observations, an orbit catalog, and a catalog of physical and observational characteristics. Using simulations from the University of Washington’s Data Intensive Research in Astrophysics and Cosmology Institute (DiRAC) and scripting in Python, I am attempting to accurately present this data and areas of possible research before LSST becomes operational. This project will be integral to preparing for research projects that will analyze actual LSST data.