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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Published on: April 8, 2020

High-performance ab initio density matrix renormalization group method: applicability to large-scale multireference

Yuki Kurashige¹, Takeshi Yanai

¹Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Okazaki, Aichi 444-8585, Japan. kura@ims.ac.jp

The Journal of Chemical Physics

|June 25, 2009

Summary

This summary is machine-generated.

This study introduces an advanced density matrix renormalization group (DMRG) algorithm for quantum chemistry, enhancing its efficiency for complex metal compounds. The optimized DMRG method accurately predicts electronic structures and energies, crucial for materials science and catalysis research.

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Last Updated: Jun 22, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

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Published on: April 12, 2019

Area of Science:

Quantum Chemistry
Computational Physics
Materials Science

Background:

The Density Matrix Renormalization Group (DMRG) is effective for one-dimensionally correlated systems.
Polynuclear transition metal compounds present challenges due to complex electron correlation.
Accurate electronic structure calculations are vital for understanding metal compound properties.

Purpose of the Study:

To develop an efficient and parallelized DMRG algorithm for quantum chemistry.
To adapt DMRG for applications to polynuclear transition metal compounds.
To improve the accuracy and applicability of DMRG for large active spaces.

Main Methods:

Implemented an efficient and parallelized DMRG algorithm.
Introduced extensions and optimizations for large multireference active spaces.
Utilized sparsity and symmetry for operator and wave function representations.

Main Results:

Achieved accurate energy predictions for Cr(2) molecules, comparable to full configuration interaction.
DMRG calculations for [Cu(2)O(2)](2+) closely matched coupled cluster with singles, doubles, and perturbative triple (CCSD(T)) results.
Demonstrated the necessity of auxiliary perturbative correction for DMRG convergence in metal compounds.

Conclusions:

The enhanced DMRG algorithm is suitable for complex metal compounds.
High entanglement in metal compounds requires a large number of renormalized basis states.
The developed method provides accurate electronic structure data for challenging chemical systems.