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This paper provides a study and discussion of earlier as well as novel more efficient schemes for the precise evaluation of finite-temperature response functions of strongly correlated quantum systems in the framework of the time-dependent…

Quantum Physics · Physics 2013-07-19 Thomas Barthel

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

Based on the contractor renormalization group (CORE) method and the density matrix renormalization group (DMRG) method, a new computational scheme, which is called the block density matrix renormalization group with effective interactions…

Strongly Correlated Electrons · Physics 2009-11-18 Haibo Ma , Chungen Liu , Yuansheng Jiang

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

Expanding and improving the repertoire of numerical methods for studying quantum lattice models is an ongoing focus in many-body physics. While the density matrix renormalization group (DMRG) has been established as a practically useful…

Strongly Correlated Electrons · Physics 2021-09-28 Maxwell Block , Johannes Motruk , Snir Gazit , Michael P. Zaletel , Zeph Landau , Umesh Vazirani , Norman Y. Yao

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

We summarize our recent efforts to develop the Density Matrix Renormalization Group (DMRG) method into a practical truncation strategy for large-scale nuclear shell model calculations. Following an overview of the essential features of the…

Nuclear Theory · Physics 2009-04-16 S. Pittel , B. Thakur

The Density Matrix Renormalization Group (DMRG) algorithm has been a rising star for the accurate ab initio exploration of Born-Oppenheimer potential energy surfaces in theoretical chemistry. However, owing to its iterative numerical…

Chemical Physics · Physics 2014-05-13 Sebastian F. Keller , Markus Reiher

We describe how density-matrix renormalization group (DMRG) can be used to solve the full-CI problem in quantum chemistry. As an illustration of the potential of this method, we apply it to a paramagnetic molecule. In particular, we show…

Strongly Correlated Electrons · Physics 2007-05-23 S. Daul , I. Ciofini , C. Daul , Steven R. White

We apply a recent adaptation of White's density matrix renormalisation group (DMRG) method to a simple quantum spin model, the dimerised $XY$ chain, in order to assess the applicabilty of the DMRG to quantum systems at non-zero temperature.…

Condensed Matter · Physics 2009-10-28 R. J. Bursill , T. Xiang , G. A. Gehring

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

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

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

In the approaches based on matrix-product states (MPSs), such as the density-matrix renormalization group (DMRG) method, the ordering of the sites crucially affects the computational accuracy. We investigate the performance of an algorithm…

Statistical Mechanics · Physics 2026-01-07 Ryo Watanabe , Toshiya Hikihara , Hiroshi Ueda

We have devised and implemented a local ab initio Density Matrix Renormalization Group (DMRG) algorithm to describe multireference nondynamic correlations in large systems. For long molecules that are extended in one of their spatial…

Strongly Correlated Electrons · Physics 2009-11-11 Johannes Hachmann , Wim Cardoen , Garnet Kin-Lic Chan

The infinite Density Matrix Renormalisation Group (iDMRG) algorithm is a highly successful numerical algorithm for the study of low-dimensional quantum systems, and is also frequently used to initialise the more popular finite DMRG…

Strongly Correlated Electrons · Physics 2015-12-02 Robert N. C. Pfeifer

In this paper we give an introduction to the numerical density matrix renormalization group (DMRG) algorithm, from the perspective of the more general matrix product state (MPS) formulation. We cover in detail the differences between the…

Strongly Correlated Electrons · Physics 2009-11-13 Ian P. McCulloch

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 report a way of wave function estimation for the density matrix renormalization group (DMRG) method applied to quantum systems, which has 2-site modulation, when the system size extension is necessary in both the finite and the infinite…

Quantum Physics · Physics 2011-02-11 Hiroshi Ueda , Tomotoshi Nishino , Koichi Kusakabe

Google's Tensor Processing Units (TPUs) are integrated circuits specifically built to accelerate and scale up machine learning workloads. They can perform fast distributed matrix multiplications and therefore be repurposed for other…

Strongly Correlated Electrons · Physics 2023-06-27 Martin Ganahl , Jackson Beall , Markus Hauru , Adam G. M. Lewis , Jae Hyeon Yoo , Yijian Zou , Guifre Vidal