High performance computing algorithms in theoretical physics

The proposed interdisciplinary project deals with the study of several algorithms from the following partly overlapping wider fields of theoretical physics: theory of superconductivity, three-body problem, nonlinear systems and biophysics. The purpose of the project is to increase the efficiency of the group"s own code packages on available hardware. This implies better analytical and mathematical algorithms as well as code optimization. For example, in the theory of superconductivity we shall study code optimization for exact Hamiltonian diagonalization, which is a memory-intensive problem. In the three-body problem we shall poerform precise calculations in ionization, and generalizations of the new quasilinearization method. The latter is a processor-intensive problem, parallelizable using directives alone. Problems related to complex systems and nonlinear dynamics typically belong to the class allowing message-passing treatment on hardware with many processors. Thre expected results will be generally applicable, despite the fact that they stem from well-defined physical problems. They will also improve the efficiency of usage of existing hardware, which has been judiciously built out of memory and network-intensive and processor-intensive components.