Objectives: The primary objective is to develop the computational capability to carry out large scale numerical simulations of the physics of earthquakes in Southern California and elsewhere. To meet this objective, we will develop a state of the art problem solving environment that will facilitate:

1. The construction of numerical and computational algorithms and specific environment(s) needed to carry out large scale simulations of these nonlinear physical processes over a geographically widely distributed, heterogeneous computing network; and
2. The development of a testbed for earthquake "forecasting" & "prediction" methodologies which uses modern Object Oriented techniques and scalable systems, software and algorithms which are efficient for both people and computational execution time.

Method: We will base our work on numerical simulation techniques initially developed by Stuart (1986), Rundle (1988) and Ward and Goes (1993), using these efforts as starting points to model the physics of earthquake fault systems in southern California. The problem solving environment will be built using the best parallel algorithms and software systems. It will leverage DOE and other state of the art national activities in simulation of both cellular automata and large scale particle systems.

Scientific and Computational Foci: We will focus on developing the capability to carry out large scale simulations of complex, multiple, interacting fault systems using a software environment optimized for rapid prototyping of new phenomenological models. The software environment will require:

1. Developing algorithms for solving computationally difficult nonlinear problems involving ("discontinuous") thresholds and nucleation events in a networked parallel (super) computing environment, adapting new "fast multipole" methods previously developed for general N-body problems;
2. Leveraging the Los Alamos ACL Infrastructure, including the POOMA object oriented framework, which is already being applied to computationally related adaptive particle mesh problems; and
3. Developing a modern problem solving environment to allow researchers to rapidly integrate simulation data with field and laboratory data (visually and quantitatively). This task is becoming increasingly important with the exponential increase in seismic, as well as space-based deformation data.

Significance of Anticipated Results: The GEM approach will allow the physics of large networks of earthquake faults to be analyzed within a general theoretical framework for the first time. It will stimulate changes in earthquake science in much the same way that General Circulation Models have changed the way atmospheric science is carried out. The computational techniques developed by the project will have important applications in many other large, computationally hard problems, such as

1. Large particle-in-cell systems in ASCI;
2. Statistical physics approaches to random field spin systems; as well as
3. Simulating large neural networks with learning and cognition.

Investigator Team and Project Organization: We have assembled a group of internationally recognized experts in the three areas of

1. observational and theoretical earth science
2. statistical mechanics and complex systems and
3. computer and computational science. The latter include world experts in the critical algorithms, software and systems required.

1. results will discussed; and
2. specific research avenues will be formulated on a regular and timely basis.