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We investigate the application of the Density Matrix Renormalization Group (DMRG) to the Hubbard model in momentum-space. We treat the one-dimensional models with dispersion relations corresponding to nearest-neighbor hopping and $1/r$…

Strongly Correlated Electrons · Physics 2009-11-07 Satoshi Nishimoto , Eric Jeckelmann , Florian Gebhard , Reinhard M. Noack

We report cutting edge performance results for a hybrid CPU-multi GPU implementation of the spin adapted ab initio Density Matrix Renormalization Group (DMRG) method on current state-of-the-art NVIDIA DGX-H100 architectures. We evaluate 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

Dynamical electronic- and vibrational-structure theories have received a growing interest in the last years due to their ability to simulate spectra recorded with ultrafast experimental techniques. The exact time evolution of a molecular…

Computational Physics · Physics 2020-02-18 Alberto Baiardi , Markus Reiher

We develop an alternative time-dependent numerical renormalization group (TDNRG) formalism for multiple quenches and implement it to study the response of a quantum impurity system to a general pulse. Within this approach, we reduce the…

Strongly Correlated Electrons · Physics 2018-10-25 H. T. M. Nghiem , T. A. Costi

We present a new implementation of the driven similarity renormalization group (DSRG) based on a density matrix renormalization group (DMRG) reference. The explicit build of high-order reduced density matrices is avoided by forming…

Chemical Physics · Physics 2025-03-04 Chenyang Li , Xiaoxue Wang , Huanchen Zhai , Wei-Hai Fang

We derive analytic energy gradients of the driven similarity renormalization group (DSRG) multireference second-order perturbation theory (MRPT2) using the method of Lagrange multipliers. In the Lagrangian, we impose constraints for a…

Chemical Physics · Physics 2021-09-30 Shuhe Wang , Chenyang Li , Francesco A. Evangelista

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

We present a method for computing resonant inelastic x-ray scattering (RIXS) spectra in one-dimensional systems using the density matrix renormalization group (DMRG) method. By using DMRG to address the problem, we shift the computational…

Strongly Correlated Electrons · Physics 2018-09-20 A. Nocera , U. Kumar , N. Kaushal , G. Alvarez , E. Dagotto , S. Johnston

We present an efficient orbital optimization procedure that combines the highly GPU accelerated, spin-adapted density matrix renormalization group (DMRG) method with the complete active space self-consistent field (CAS-SCF) approach for…

We implement and apply time-dependent density matrix renormalization group (TD-DMRG) algorithms at zero and finite temperature to compute the linear absorption and fluorescence spectra of molecular aggregates. Our implementation is within a…

Chemical Physics · Physics 2019-07-30 Jiajun Ren , Zhigang Shuai , Garnet Kin-Lic Chan

Wilson's Numerical Renormalization Group (NRG) is so far the only nonperturbative technique that can reliably access low-energy properties of quantum impurity systems. We present a recent extension of the method, the DM-NRG, which yields…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Walter Hofstetter

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

The density matrix renormalization group (DMRG) algorithm was originally designed to efficiently compute the zero temperature or ground-state properties of one dimensional strongly correlated quantum systems. The development of the…

Strongly Correlated Electrons · Physics 2016-03-09 A. Nocera , G. Alvarez

We present a simple method, combining the density-matrix renormalization-group (DMRG) algorithm with finite-size scaling, which permits the study of critical behavior in quantum spin chains. Spin moments and dimerization are induced by…

Strongly Correlated Electrons · Physics 2009-10-31 Shan-Wen Tsai , J. B. Marston

Numerical renormalization group (NRG) calculations of quantum impurity models, based on a logarithmic discretization in energy of electronic or bosonic Hamiltonians, provide a powerful tool to describe physics involving widely separated…

Strongly Correlated Electrons · Physics 2009-11-13 Axel Freyn , Serge Florens

This study examines several techniques to improve the efficiency of the linearized multireference driven similarity renormalization group truncated to one- and two-body operators [MR-LDSRG(2)]. We propose a sequential MR-LDSRG(2)…

Chemical Physics · Physics 2019-03-29 Tianyuan Zhang , Chenyang Li , Francesco A. Evangelista

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

We present a novel formulation of the vibrational density matrix renormalization group (vDMRG) algorithm tailored to strongly anharmonic molecules described by general high-dimensional model representations of potential energy surfaces. For…

Chemical Physics · Physics 2023-12-29 Nina Glaser , Alberto Baiardi , Markus Reiher

We proposed a novel dense line spectrum super-resolution algorithm, the DMRA, that leverages dynamical multi-resolution of atoms technique to address the limitation of traditional compressed sensing methods when handling dense point-source…

Signal Processing · Electrical Eng. & Systems 2024-09-04 Mingguang Han , Yi Zeng , Xiaoguang Li , Tiejun Li