Density-Matrix Renormalization Group Algorithm with Multi-Level Active Space

TL;DR

This paper introduces a multi-level active space control in the DMRG algorithm, improving computational efficiency for large active space quantum chemistry calculations through hierarchical orbital ordering.

Contribution

The paper presents a novel ML-DMRG algorithm with hierarchical orbital ordering, enhancing efficiency in large active space calculations compared to traditional DMRG methods.

Findings

ML-DMRG achieves noticeable efficiency gains.

Hierarchical orbital re-ordering reduces computational time.

Effective for ground and excited state calculations.

Abstract

The density-matrix renormalization group (DMRG) method, which can deal with a large active space composed of tens of orbitals, is nowadays widely used as an efficient addition to traditional complete active space (CAS)-based approaches. In this paper, we present the DMRG algorithm with a multi-level (ML) control of the active space based on chemical intuition-based hierarchical orbital ordering, which is called as ML-DMRG with its self-consistent field variant ML-DMRG-SCF. Ground and excited state calculations of H2O, N2, indole, and Cr2 with comparisons to DMRG references using fixed number of kept states (M) illustrate that MLtype DMRG calculations can obtain noticeable efficiency gains. It is also shown that the orbital re-ordering based on hierarchical multiple active subspaces may be beneficial for reducing computational time for not only ML-DMRG calculations but also DMRG ones with fixed M values.