APPLICATIONS

Romeel Davé and his team at the University of Arizona used NCSA's Tungsten cluster to develop a new astrophysics tool called SPOC. It approximates the physical properties -- including stellar mass and star-formation rate -- of galaxies that have been observed but are not well understood because limited spectral data are available. SPOC takes very basic photometry data from an observed galaxy and uses a Bayesian method to compare that to an array of photometry data generated by computationally modeled galaxies. Inferring that if the spectral properties match then other properties will match as well, it provides upper and lower constraints on what the other properties are for the observed galaxy. The team introduced SPOC, short for Simulated Photometry-derived Observational Constraints, in an April 2007 Monthly Notices of the Royal Astronomical Society paper. The publication tested SPOC using six high-redshift galaxies with large amounts of observed spectral data available. The properties of five of the galaxies as defined by SPOC well matched the observed data. The sixth was unlike anything in the array of data to which the galaxies were compared. Because it was successfully flagged as such, this outlier showed that SPOC can also be used to identify objects that challenge existing models and observations. This research is supported by NASA and the National Science Foundation.