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We present an efficient stochastic algorithm for the recently introduced perturbative density matrix renormalization group (p-DMRG) method for large active spaces. The stochastic implementation bypasses the computational bottleneck involved…

Chemical Physics · Physics 2018-08-01 Sheng Guo , Zhendong Li , Garnet Kin-Lic Chan

The numerical renormalization group (NRG) is rephrased as a variational method with the cost function given by the sum of all the energies of the effective low-energy Hamiltonian. This allows to systematically improve the spectrum obtained…

Quantum Physics · Physics 2013-05-23 Iztok Pizorn , Frank Verstraete

The Density Matrix Renormalisation Group (DMRG) is an electronic structure method that has recently been applied to ab-initio quantum chemistry. Even at this early stage, it has enabled the solution of many problems that would previously…

We present a numerical implementation of the density matrix renormalization group (DMRG) using the discrete variable representation (DVR) basis set. One main advantage of using the local DVR basis sets is that the computations of…

Quantum Physics · Physics 2024-11-13 Bing Gu

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…

A distributed-memory parallelization strategy for the density matrix renormalization group is proposed for cases where correlation functions are required. This new strategy has substantial improvements with respect to previous works. A…

Strongly Correlated Electrons · Physics 2010-04-20 Julian Rincon , D. J. Garcia , K. Hallberg

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

The density matrix renormalization group (DMRG) approach is arguably the most successful method to numerically find ground states of quantum spin chains. It amounts to iteratively locally optimizing matrix-product states, aiming at better…

Quantum Physics · Physics 2015-06-26 J. Eisert

We employ the density matrix renormalization group (DMRG) and the wave function factorization method for the numerical solution of large scale nuclear structure problems. The DMRG exhibits an improved convergence for problems with realistic…

Nuclear Theory · Physics 2007-05-23 T. Papenbrock , D. J. Dean

The density matrix renormalization group (DMRG) has been extended to study quantum phase transitions on random graphs of fixed connectivity. As a relevant example, we have analysed the random Ising model in a transverse field. If the…

Disordered Systems and Neural Networks · Physics 2009-11-11 Javier Rodriguez-Laguna

We investigate the role of entanglement in quantum phase transitions, and show that the success of the density matrix renormalization group (DMRG) in understanding such phase transitions is due to the way it preserves entanglement under…

Quantum Physics · Physics 2007-05-23 Tobias J. Osborne , Michael A. Nielsen

In this paper, we propose a modified Density Matrix Renormalization Group (DMRG) algorithm to preferentially select minimum entropy states (minimally entangled states) in finite systems with asymptotic ground state degeneracy. The algorithm…

Strongly Correlated Electrons · Physics 2013-10-01 Hong-Chen Jiang , Leon Balents

The presence of many degenerate $d/f$ orbitals makes polynuclear transition metal compounds such as iron-sulfur clusters in nitrogenase challenging for state-of-the-art quantum chemistry methods. To address this challenge, we present the…

Chemical Physics · Physics 2023-12-22 Chunyang Xiang , Weile Jia , Wei-Hai Fang , Zhendong Li

We introduce a picture to analyze the density matrix renormalization group (DMRG) numerical method from a quantum information perspective. This leads us to introduce some modifications for problems with periodic boundary conditions in which…

Strongly Correlated Electrons · Physics 2007-05-23 F. Verstraete , D. Porras , J. I. Cirac

During the past 15 years, the density matrix renormalization group (DMRG) has become increasingly important for ab initio quantum chemistry. Its underlying wavefunction ansatz, the matrix product state (MPS), is a low-rank decomposition of…

Chemical Physics · Physics 2014-09-25 Sebastian Wouters , Dimitri Van Neck

We propose an initialization procedure for the density-matrix renormalization group (DMRG): {\it the recursive sweep method}. In a conventional DMRG calculation, the infinite-algorithm, where two new sites are added to the system at each…

Strongly Correlated Electrons · Physics 2007-05-23 Masaki Tezuka

We present two new analytic formulations of the Density Matrix Renormalization Group Method. In these formulations we combine the block renormalization group (BRG) procedure with Variational and Fokker-Planck methods. The BRG method is used…

Condensed Matter · Physics 2015-06-25 Miguel A. Martin-Delgado , German Sierra

There has been recent interest in the deployment of ab initio density matrix renormalization group computations on high performance computing platforms. Here, we introduce a reformulation of the conventional distributed memory ab initio…

Chemical Physics · Physics 2021-06-24 Huanchen Zhai , Garnet Kin-Lic Chan

We propose a simple modification of the density matrix renormalization group (DMRG) method in order to tackle strongly disordered quantum spin chains. Our proposal, akin to the idea of the adaptive time-dependent DMRG, enables us to reach…

Strongly Correlated Electrons · Physics 2018-11-14 J. C. Xavier , J. A. Hoyos , E. Miranda

We describe a low cost alternative to the standard variational DMRG (density matrix renormalization group) algorithm that is analogous to the combination of selected configuration interaction plus perturbation theory (SCI+PT). We denote the…

Chemical Physics · Physics 2018-03-28 Sheng Guo , Zhendong Li , Garnet Kin-Lic Chan
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