The Asteroid Discovery, Analysis, and Mapping (ADAM) platform

The B612 Asteroid Institute has developed the Asteroid Discovery, Analysis, and Mapping (ADAM) platform to analyze and understand asteroid data sets. ADAM uses Google Compute Engine to perform precision cloud-based asteroid orbit propagations, orbit determination, targeted deflections, Monte Carlo impact probability calculations, and orbit visualizations. Our vision with ADAM is to create a cloud-based astrodynamics platform available to the scientific community that provides a unified interface to multiple tools and enables large-scale studies. ADAM includes pre-configured settings to match common practices, such as the use of various time standards and coordinate frames, removing the need for users to perform any necessary transformations for comparison to results from external tools. ADAM’s architecture consists of a web-service front-end, cloud-based storage, and cloud-based compute engines encapsulating multiple tools for computation and analysis. At the core of ADAM’s orbit propagation, targeting capabilities, and impact probability computations are a number of open source astrodynamics packages as well as the Analytical Graphics Inc. (AGI)’s Systems Tool Kit (STK) Components Segmented Propagation Library. The astrodynamics software “Astrogator” (included with Components) has been used internationally for pre-launch mission analysis and in operations on numerous commercial and government Earth-orbiting, lunar, and deep space missions, such as the WMAP, CONTOUR, LCROSS, IBEX, LADEE, LRO, MAVEN, MESSENGER, and New Horizons missions.

We present a study performed with ADAM to investigate the distribution of deflection delta-v required to divert asteroids on Earth impact trajectories as a function of time prior to impact for 10,000 synthetic impacting asteroids, calculating the distribution of deflection delta-v required if applied 10, 20, 30, 40, and 50 years prior to impact (Greenstreet et al., 2020). We also present the ongoing work to compute impact probabilities for the 10,000 synthetic impactors for six different size bins (a total of 60,000 synthetic impactors) over the 50 year period before impact sampled every 1-10 years. Lastly, we describe the integration of the Tracklet-less Heliocentric Orbit Recovery (THOR) algorithm (see abstract by J. Moeyens) into ADAM to utilize it’s cloud-computing capabilities to discover even the trickiest-to-find asteroids among current survey data.