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The Density Matrix Renormalization Group (DMRG) was introduced by Steven White in 1992 as a method for accurately describing the properties of one-dimensional quantum lattices. The method, as originally introduced, was based on the…

Mesoscale and Nanoscale Physics · Physics 2011-05-12 Jorge Dukelsky , Stuart Pittel

I present a density-matrix renormalization-group (DMRG) method for calculating dynamical properties and excited states in low-dimensional lattice quantum many-body systems. The method is based on an exact variational principle for dynamical…

Strongly Correlated Electrons · Physics 2009-11-07 Eric Jeckelmann

A momentum-space approach of the density-matrix renormalization-group (DMRG) method is developed. Ground state energies of the Hubbard model are evaluated using this method and compared with exact diagonalization as well as quantum…

Condensed Matter · Physics 2009-10-28 T. Xiang

The dissociation of $\rm N_2$ and $\rm N_2^+$ has been studied by using the \emph{ab initio} Density Matrix Renormalization Group (DMRG) method. Accurate Potential Energy Surfaces (PES) have been obtained for the electronic ground states of…

Chemical Physics · Physics 2018-02-21 Christian Stemmle , Örs Legeza , Beate Paulus

The density-matrix renormalization group method (DMRG) has established itself over the last decade as the leading method for the simulation of the statics and dynamics of one-dimensional strongly correlated quantum lattice systems. In the…

Strongly Correlated Electrons · Physics 2011-01-04 Ulrich Schollwoeck

We present the theory of a density matrix renormalization group (DMRG) algorithm which can solve for both the ground and excited states of non-Hermitian transcorrelated Hamiltonians, and show applications in \emph{ab initio} molecular…

The Density Matrix Renormalization Group (DMRG) is a state-of-the-art numerical technique for a one dimensional quantum many-body system; but calculating accurate results for a system with Periodic Boundary Condition (PBC) from the…

Strongly Correlated Electrons · Physics 2016-11-29 Dayasindhu Dey , Debasmita Maiti , Manoranjan Kumar

Compared to ground state electronic structure optimizations, accurate simulations of molecular real-time electron dynamics are usually much more difficult to perform. To simulate electron dynamics, the time-dependent density matrix…

Chemical Physics · Physics 2024-11-15 Imam S. Wahyutama , Henrik R. Larsson

In the realm of quantum chemistry, the accurate prediction of electronic structure and properties of nanostructures remains a formidable challenge. Density Functional Theory (DFT) and Density Matrix Renormalization Group (DMRG) have emerged…

Strongly Correlated Electrons · Physics 2024-02-21 T. Pauletti , M. Sanino , L. Gimenes , I. M. Carvalho , V. V. França

We recently introduced [J. Chem. Phys. 152 2020, 204103] the nuclear-electronic all-particle density matrix renormalization group method (NEAP-DMRG) to solve the molecular Schr\"{o}dinger equation, based on a stochastically optimized…

Chemical Physics · Physics 2022-01-31 Robin Feldmann , Andrea Muolo , Alberto Baiardi , Markus Reiher

The density matrix renormalization group (DMRG) method is applied to the interaction round a face (IRF) model. When the transfer matrix is asymmetric, singular-value decomposition of the density matrix is required. A trial numerical…

Condensed Matter · Physics 2009-10-28 Tomotoshi Nishino

Using the dynamical mean-field theory (DMFT) as a `booster-rocket', the functional renormalization group (fRG) can be upgraded from a weak-coupling method to a powerful computation tool for strongly interacting fermion systems. The strong…

Strongly Correlated Electrons · Physics 2019-03-13 Demetrio Vilardi , Ciro Taranto , Walter Metzner

The symmetrized Density-Matrix-Renormalization-Group (DMRG) method is used to study linear and nonlinear optical properties of Free base porphine and metallo-porphine. Long-range interacting model, namely, Pariser-Parr-Pople (PPP) model is…

Mesoscale and Nanoscale Physics · Physics 2015-05-30 Manoranjan Kumar , Y. Anusooya Pati , S. Ramasesha

We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of time-dependent DMRG from the usual situation of hermitian Hamiltonian matrices to…

Complex quantum systems are often multiscale in nature with strong interactions between different scales. We present a novel idea: iteratively suppressing, rather than tracing out, the fast, high-energy degrees of freedom in strongly…

Quantum Physics · Physics 2026-05-01 Bing Gu

We improve the density-matrix renormalization group (DMRG) evaluation of the Kubo formula for the zero-temperature linear conductance of one-dimensional correlated systems.The dynamical DMRG is used to compute the linear response of a…

Strongly Correlated Electrons · Physics 2018-10-08 Jan-Moritz Bischoff , Eric Jeckelmann

The density-matrix renormalization-group (DMRG) algorithm is extended to treat time-dependent problems. The method provides a systematic and robust tool to explore out-of-equilibrium phenomena in quantum many-body systems. We illustrate the…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 M. A. Cazalilla , J. B. Marston

We present a new hybrid multiconfigurational method based on the concept of range-separation that combines the density matrix renormalization group approach with density functional theory. This new method is designed for the simultaneous…

The density matrix renormalization group (DMRG) is a numerical method that optimizes a variational state expressed by a tensor product. We show that the ground state is not fully optimized as far as we use the standard finite system…

Statistical Mechanics · Physics 2010-05-20 H. Takasaki , T. Hikihara , T. Nishino

The Density Matrix Renormalization Group (DMRG) algorithm is a powerful tool for solving eigenvalue problems to model quantum systems. DMRG relies on tensor contractions and dense linear algebra to compute properties of condensed matter…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-26 Ryan Levy , Edgar Solomonik , Bryan K. Clark