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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 numerical study of anyonic systems is known to be highly challenging due to their non-bosonic, non-fermionic particle exchange statistics, and with the exception of certain models for which analytical solutions exist, very little is…

Strongly Correlated Electrons · Physics 2015-12-25 Robert N. C. Pfeifer , Sukhwinder Singh

The density matrix renormalization group (DMRG) is a powerful numerical technique to solve strongly correlated quantum systems: it deals well with systems which are not dominated by a single configuration (unlike Coupled Cluster) and it…

Chemical Physics · Physics 2025-12-16 Martina Nibbi , Luca Frediani , Evgueni Dinvay , Christian B. Mendl

A simplified version of White's Density Matrix Renormalization Group (DMRG) algorithm has been used to find the ground state of the free particle on a tight-binding lattice. We generalize this algorithm to treat the tight-binding particle…

Strongly Correlated Electrons · Physics 2009-10-31 M. A. Martin-Delgado , G. Sierra , R. M. Noack

We describe the use of the Density Matrix Renormalization Group method as a means of approximately solving large-scale nuclear shell-model problems. We focus on an angular-momentum-conserving variant of the method and report test results…

Nuclear Theory · Physics 2011-05-12 S. Pittel , N. Sandulescu

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 study the one-dimensional $S=1/2$ Heisenberg model with a uniform and a staggered magnetic fields, using the dynamical density-matrix renormalization group (DDMRG) technique. The DDMRG enables us to investigate the dynamical properties…

Strongly Correlated Electrons · Physics 2007-10-19 S. Nishimoto , M. Arikawa

The practical success of polynomial-time tensor network methods for computing ground states of certain quantum local Hamiltonians has recently been given a sound theoretical basis by Arad, Landau, Vazirani, and Vidick. The convergence…

Statistical Mechanics · Physics 2018-02-14 Brenden Roberts , Thomas Vidick , Olexei I. Motrunich

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

The Density Matrix Renormalization Group (DMRG) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamic and…

Strongly Correlated Electrons · Physics 2008-11-26 Karen Hallberg

We combine the Density Matrix Renormalization Group (DMRG) with Matrix Product State tangent space concepts to construct a variational algorithm for finding ground states of one dimensional quantum lattices in the thermodynamic limit. A…

Quantum Physics · Physics 2019-04-22 V. Zauner-Stauber , L. Vanderstraeten , M. T. Fishman , F. Verstraete , J. Haegeman

A major advance in density-matrix renormalization group (DMRG) calculations has been achieved by the invention of highly efficient DMRG techniques for the simulation of real-time dynamics of strongly correlated quantum systems in one…

Strongly Correlated Electrons · Physics 2007-05-23 U. Schollwoeck , S. R. White

We describe a large disorder renormalization group (LDRG) method for the Anderson model of localization in one dimension which decimates eigenstates based on the size of their wavefunctions rather than their energy. We show that our LDRG…

Disordered Systems and Neural Networks · Physics 2014-11-04 Sonika Johri , R. N. Bhatt

We present an alternative, memory-efficient, Schmidt decomposition-based description of the inherently bipartite restricted active space (RAS) scheme, which can be implemented effortlessly within the density matrix renormalization group…

We propose a new fast numerical renormalization group method,the corner transfer matrix renormalization group (CTMRG) method, which is based on a unified scheme of Baxter's corner transfer matrix method and White's density matrix…

Condensed Matter · Physics 2009-10-28 T. Nishino , K. Okunishi

We generalize the spectral sum rule preserving density matrix numerical renormalization group (DM-NRG) method in such a way that it can make use of an arbitrary number of not necessarily Abelian, local symmetries present in the quantum…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 A. I. Toth , C. P. Moca , O. Legeza , G. Zarand

The density matrix renormalization group (DMRG) method allows an efficient computation of the properties of interacting 1D quantum systems. Two-dimensional (2D) systems, capable of displaying much richer quantum behavior, generally lie…

Strongly Correlated Electrons · Physics 2014-08-06 Samuel Moukouri , Eytan Grosfeld

\textbf{Background} The reach of \textit{ab initio} theory has greatly increased in recent decades. However, predicting the location of the drip lines remains challenging due to uncertainties in nuclear forces and difficulties in describing…

Nuclear Theory · Physics 2026-01-23 A. Sehovic , K. Fossez , H. Hergert

The recently proposed Clifford augmented density matrix renormalization group (CA-DMRG) method seamlessly integrates Clifford circuits with matrix product states, and takes advantage of the expression power from both. CA-DMRG has been shown…

Quantum Physics · Physics 2025-11-14 Lizhong Fu , Honghui Shang , Jinlong Yang , Chu Guo

The density matrix renormalization group (DMRG) method has already proved itself as a very efficient and accurate computational method, which can treat large active spaces and capture the major part of strong correlation. Its application on…

Chemical Physics · Physics 2022-10-31 Pavel Beran , Katarzyna Pernal , Fabijan Pavosevic , Libor Veis