Direct extension of the density-matrix renormalization group method toward two-dimensional large quantum lattices and related high-performance computing

The density-matrix renormalization group (DMRG) method is widely used by computational physicists as a high accuracy tool to explore the ground state in large quantum lattice models, e.g., Heisenberg and Hubbard models, which are well-known standard models describing interacting spins and electrons, respectively, in solid states. After the DMRG method was originally developed for 1-D lattice/chain models, some specific extensions toward 2-D lattice (n-leg ladder) models have been proposed. However, high accuracy as obtained in 1-D models is not always guaranteed in their extended versions because the original exquisite advantage of the algorithm is partly lost. Thus, we choose an alternative way. It is a direct 2-D extension of DMRG method which instead demands an enormously large memory space, but the memory explosion is resolved by parallelizing the DMRG code with performance tuning. The parallelized direct extended DMRG shows a good accuracy like 1-D models and an excellent parallel efficiency as the number of states kept increases. This success promises accurate analysis on large 2-D (n-leg ladder) quantum lattice models in the near future when peta-flops parallel supercomputers are available.