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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

The density-matrix renormalization group (DMRG) algorithm can be adapted to the calculation of dynamical correlation functions in various ways which all represent compromises between computational efficiency and physical accuracy. In this…

Strongly Correlated Electrons · Physics 2012-11-19 P. E. Dargel , A. Wöllert , A. Honecker , I. P. McCulloch , U. Schollwöck , T. Pruschke

We present an implementation of a perturbative triples correction for the coupled cluster ansatz including single and double excitations based on the transcorrelated Hamiltonian. Transcorrelation introduces explicit electron correlation in…

Chemical Physics · Physics 2025-02-19 Maximilian Mörchen , Alberto Baiardi , Michał Lesiuk , Markus Reiher

The physical properties of a quantum many-body system can, in principle, be determined by diagonalizing the respective Hamiltonian, but the dimensions of its matrix representation scale exponentially with the number of degrees of freedom.…

Strongly Correlated Electrons · Physics 2023-09-13 G. Catarina , Bruno Murta

Capturing the interplay between electronic correlations and many-particle entanglement requires a unified framework for Hamiltonian and eigenbasis renormalization. In this work, we apply the unitary renormalization group (URG) scheme…

Strongly Correlated Electrons · Physics 2021-10-25 Anirban Mukherjee , Siddhartha Lal

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, dynamical…

Condensed Matter · Physics 2007-05-23 Karen Hallberg

Renormalization is a powerful concept in the many-body problem. Inspired by the highly successful density matrix renormalization group (DMRG) algorithm, and the quantum chemical graphical representation of configuration space, we introduce…

Chemical Physics · Physics 2016-03-23 Zhendong Li , Garnet Kin-Lic Chan

A numerical algorithm for studying strongly correlated electron systems is proposed. The groundstate wavefunction is projected out after numerical renormalization procedure in the path integral formalism. The wavefunction is expressed from…

Strongly Correlated Electrons · Physics 2007-05-23 Masatoshi Imada , Tsuyoshi Kashima

We present a high-accuracy procedure for electronic structure calculations of strongly correlated materials. To address limitations in current electronic structure methods, we employ density functional theory in combination with the…

We apply the transcorrelated method to problems of multireference character. For this, we show that the choice of reference wavefunction during the Jastrow optimisation procedure is vital, and we propose a workflow wherein we use…

Applications of the similarity renormalization group (SRG) approach [F. Wegner, Ann. Phys. 506, 77 (1994), S. D. G{\l}azek and K. G. Wilson, Phys. Rev. D 49, 4214 (1994)] to the formulation of useful many-body theories of electron…

Chemical Physics · Physics 2015-06-19 Francesco A. Evangelista

In the Density Matrix Renormalization Group (DMRG) algorithm, Hamiltonian symmetries play an important role. Using symmetries, the matrix representation of the Hamiltonian can be blocked. Diagonalizing each matrix block is more efficient…

Strongly Correlated Electrons · Physics 2012-06-29 G. Alvarez

We present an efficient implementation of the Density Matrix Renormalization Group (DMRG) algorithm that includes an optimal ordering of the proton and neutron orbitals and an efficient expansion of the active space utilizing various…

Nuclear Theory · Physics 2015-11-18 Ö. Legeza , L. Veis , A. Poves , J. Dukelsky

Drachmann's regularization approach is implemented for floating explicitly correlated Gaussians (fECGs) and molecular systems. Earlier applications of drachmannized relativistic corrections for molecular systems were hindered due to the…

Chemical Physics · Physics 2024-06-11 Balázs Rácsai , Dávid Ferenc , Ádám Margócsy , Edit Mátyus

Quantum computing is emerging as a new computational paradigm with the potential to transform several research fields, including quantum chemistry. However, current hardware limitations (including limited coherence times, gate infidelities,…

The density-matrix renormalization group (DMRG) is a numerical algorithm for the efficient truncation of the Hilbert space of low-dimensional strongly correlated quantum systems based on a rather general decimation prescription. This…

Strongly Correlated Electrons · Physics 2009-11-10 Ulrich Schollwoeck

NISQ era devices suffer from a number of challenges like limited qubit connectivity, short coherence times and sizable gate error rates. Thus, quantum algorithms are desired that require shallow circuit depths and low qubit counts to take…

We introduce the Nuclear Electronic All-Particle Density Matrix Renormalization Group (NEAP-DMRG) method for solving the time-independent Schr\"odinger equation simultaneously for electrons and other quantum species. In contrast to already…

Chemical Physics · Physics 2020-05-29 Andrea Muolo , Alberto Baiardi , Robin Feldmann , Markus Reiher

In the numerical analysis of strongly correlated quantum lattice models one of the leading algorithms developed to balance the size of the effective Hilbert space and the accuracy of the simulation is the density matrix renormalization…

Strongly Correlated Electrons · Physics 2015-06-17 Csaba Nemes , Gergely Barcza , Zoltán Nagy , Örs Legeza , Péter Szolgay

The density matrix renormalization group (DMRG) method introduced by White for the study of strongly interacting electron systems is reviewed; the method is variational and considers a system of localized electrons as the union of two…

Strongly Correlated Electrons · Physics 2009-10-31 G. Fano , F. Ortolani , L. Ziosi