Transformation of Hubbard Hamiltonian into the Matrix and its Diagonalization

In order to perform larger scale physics research in the area of superconductivity, we have developed an application that can transform the Hubbard Hamiltonian into a matrix and diagonalize it to find the selected model’s energy spectrum. For that purpose we have used the Python language and its wide ecosystem. This paper proves that the selected tools are capable of creating scientific applications in a general sense.

After a short introduction into the physics problem and the designed algorithm, the paper presents the computer science problems and their solutions in creating scientific programs, in particular: performance and parallelization issues, storage of input data and results, bottleneck detection, as well as optimization and testing. The most interesting examples of the development cycle are described to give a ready solution for implementing other scientific software.

Computational Methods in Science and Technology, Volume 21 (4) 2015, 181–189 — read online or download PDF.