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Obtaining accurate representations of the eigenstates of an array of coupled superconducting qubits is a crucial step in the design of circuit quantum electrodynamics (QED)-based quantum processors. However, exact diagonalization of the…

The density matrix renormalization group (DMRG) algorithm is a popular alternating minimization scheme for solving high-dimensional optimization problems in the tensor train format. Classical DMRG, however, is based on sequential…

Numerical Analysis · Mathematics 2025-12-09 Laura Grigori , Muhammad Hassan

A new density matrix renormalisation group (DMRG) approach is presented for quantum systems of two spatial dimensions. In particular, it is shown that it is possible to create a multi-chain-type 2D DMRG approach which utilises previously…

Strongly Correlated Electrons · Physics 2009-11-10 Damian J. J. Farnell

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

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 Technique (DMRG) with Green Function Monte Carlo (GFMC) simulations. The DMRG is most successful in 1-dimensional systems and can only be extended to 2-dimensional systems for strips of limited width. GFMC is…

Condensed Matter · Physics 2009-10-31 M. S. L. du Croo de Jongh , J. M. J. van Leeuwen , W. van Saarloos

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

In order to extend the density-matrix renormalization-group (DMRG) method to two-dimensional systems, we formulate two alternative methods to prepare the initial states. We find that the number of states that is needed for accurate energy…

Condensed Matter · Physics 2007-05-23 Shoudan Liang , Hanbin Pang

We demonstrate how to parallelize the density matrix renormalization group (DMRG) algorithm in real space through a straightforward modification of serial DMRG. This makes it possible to apply at least an order of magnitude more…

Strongly Correlated Electrons · Physics 2013-04-25 E. M. Stoudenmire , Steven R. White

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 propose a new approach to implement the density matrix renormalization group (DMRG) in two dimensions. With this approach the initial blocks of a L by L lattice are built up directly from the matrix elements of a (L-1) by L-1) lattice…

Strongly Correlated Electrons · Physics 2009-11-07 Tao Xiang , Jizhong Lou , Zhaobin Su

The density matrix renormalization group (DMRG) of White 1992 remains to this day an integral component of many state-of-the-art methods for efficiently simulating strongly correlated quantum systems. In quantum chemistry, QC-DMRG became a…

Quantum Physics · Physics 2021-03-16 Mazen Ali

The Haldane gap of the S=2 Heisenberg antiferromagnet in a one-dimensional linear chain is examined by a numerical-diagonalization method. A precise estimate for the magnitude of the gap is successfully obtained by a multistep…

Strongly Correlated Electrons · Physics 2018-09-12 Hiroki Nakano , Toru Sakai

The widely used density matrix renormalization group (DRMG) method often fails to converge in systems with multiple length scales, such as lattice discretizations of continuum models and dilute or weakly doped lattice models. The local…

Quantum Gases · Physics 2012-07-17 M. Dolfi , B. Bauer , M. Troyer , Z. Ristivojevic

We develop a correction to the density matrix used in density matrix renormalization group calculations to take into account the incompleteness of the environment block. The correction allows successful calculations using only a single site…

Strongly Correlated Electrons · Physics 2016-08-31 Steven R. White

The purpose of this paper is (i) to present a generic and fully functional implementation of the density-matrix renormalization group (DMRG) algorithm, and (ii) to describe how to write additional strongly-correlated electron models and…

Strongly Correlated Electrons · Physics 2015-05-13 G. Alvarez

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

Strongly Correlated Electrons · Physics 2014-05-22 Sebastian Wouters

The Density Matrix Renormalization Group (DMRG) method is developed for application to realistic nuclear systems. Test results are reported for 24Mg.

Nuclear Theory · Physics 2007-05-23 S. S. Dimitrova , S. Pittel , J. Dukelsky , M. V. Stoitsov

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

We extend the symmetrized density matrix renormalization group (SDMRG) method to compute the dynamic nonlinear optic coefficients for long chains. By computing correction vectors in the appropriate symmetry subspace we obtain the dynamic…

Condensed Matter · Physics 2007-05-23 Swapan K. Pati , S. Ramasesha , Z. Shuai , J. L. Bredas