Integrating Simulation and Observation: Discovery Engines for Big Data
This new Grand Challenge project seeks to achieve revolutionary advances in two distinct disciplines: cosmology and materials science.
While these disciplines differ in their scientific focus, they share cross-cutting concerns that motivate this new project. In both disciplines, rapid evolution in sensor technology is productng a tsunami of data. For example, digiatal sky surveys now capture detailed infomation on billions of celestial objects; and in materials science, advances in instrumentation and experiment design have accelerated the rate at which data can be collected at DOE facilties such as the Advanced Photon Source.
To handle this data tsunami, both disciplines must collect, organize, and manage data from many experiments and simulations; both must perform complex analysis on large datasets; and both need to deploy new methods into the workflows of experimental and observational facilities.
To achieve these goals, we are pursuing the following activities:
- In cosmology, we are developing new methods for creating and analyzing virtual skies from large-scale simulations carried out on leadership-class computers. We will also deploy a system allowing interactive access to the simulated datasets and sky catalogs, enabling the broader community to explore and analyze the data and address some of the most fundamental questions concerning the nature of the dark universe.
- In materials science, we are integrating new imaging methodologies and simulation capabilities. Comprehensive measurements of single crystal diffuse scattering over a wide volume of reciprocal space can provide detailed insights into the mesoscale disorder underlying technologically important materials properties, such as fast ion conduction and unconventional superconductivity. We are developing new methods for acquiring, managing, and exploiting big data for x-ray scattering and spectroscopy applications.