Michael S Vogeley

We measure the distribution of void sizes in the SDSS using an objective void finding algorithm and statistically characterize the spectrum of voids by measuring the Void Probability Function for volume-limited samples of this survey. These void statistics provide powerful constraints on models that describe the relationship between luminous and dark matter. The properties of galaxies in voids provide further contraints on galaxy formation models: On average, galaxies in the rarified environments of voids exhibit bluer colors, higher specific star formation rates, lower dust content, and more disk-like morphology than objects in denser regions. This trend persists in comparisons of samples in low vs. high-density regions with similar luminosity and morphology. Large-scale modulation of the halo mass function partially explains this dependence of galaxy evolution on environment.

We are developing an integrated suite of parallelized analysis and visualization tools, designed to run on large Beowulf-class clusters of computers. Using efficient and scalable algorithms, this toolkit will harness the low-cost computing power of these parallel systems to allow real time analysis and visualization of data sets in the multi-terabyte to petabyte range. Software components for data input/output, transformations, statistical analysis, and 3D visualization will communicate and operate seamlessly within a symbolic user interface.