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In the Density Matrix Renormalization Group (DMRG) algorithm, Hamiltonian symmetries play an important role. Using symmetries, the matrix representation of the Hamiltonian can be blocked. Diagonalizing each matrix block is more efficient than diagonalizing the original matrix. This paper explains how the the DMRG++ code has been extended to handle the non-local SU(2) symmetry in a model independent way. Improvements in CPU times compared to runs with only local symmetries are discussed for the one-orbital Hubbard model, and for a two-orbital Hubbard model for iron-based superconductors. The computational bottleneck of the algorithm and the use of shared memory parallelization are also addressed.
A detailed description of the time-step-targetting time evolution method within the DMRG algorithm is presented. The focus of this publication is on the implementation of the algorithm, and on its generic application. The case of one-site excitations
We analyze the antiferromagnetic $text{SU}(3)$ Heisenberg chain by means of the Density Matrix Renormalization Group (DMRG). The results confirm that the model is critical and the computation of its central charge and the scaling dimensions of the fi
The DMRG method is applied to integrable models of antiferromagnetic spin chains for fundamental and higher representations of SU(2), SU(3), and SU(4). From the low energy spectrum and the entanglement entropy, we compute the central charge and the
We study the phase diagram of a one-dimensional version of the Kitaev spin-1/2 model with an extra ``$Gamma$-term, using analytical, density matrix renormalization group and exact diagonalization methods. Two intriguing phases are found. In the gaple
We generalize the formalism of the dynamical vertex approximation (D$Gamma$A) -- a diagrammatic extension of the dynamical mean-field theory (DMFT)-- to treat magnetically ordered phases. To this aim, we start by concisely illustrating the many-elect