Multireference Embedding and Fragmentation Methods for Classical and Quantum Computers: From Model Systems to Realistic Applications

Chemical Reviews 2026

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Authors: Shreya Verma, Abhishek Mitra, Qiaohong Wang, Ruhee D’cunha, Bhavnesh Jangid, Matthew R. Hennefarth, Valay Agarawal, Leon Otis, Soumi Haldar, Matthew R. Hermes, Laura Gagliardi
DOI: 10.1021/acs.chemrev.5c00486
Cited by: 8
References: 253

Abstract

One of the primary challenges in quantum chemistry is the accurate modeling of strong electron correlation. While multireference methods effectively capture such correlation, their steep scaling with system size prohibits their application to large molecules and extended materials. Quantum embedding offers a promising solution by partitioning complex systems into manageable subsystems. In this Review, we highlight recent advances in multireference density matrix embedding and localized active space self-consistent field approaches for complex molecules and extended materials. We discuss both classical implementations and the emerging potential of these methods on quantum computers. By extending classical embedding concepts to the quantum landscape, these algorithms have the potential to expand the reach of multireference methods in quantum chemistry and materials.

Fields of Study & Subjects

Spectroscopy and Quantum Chemical Studies Quantum Computing Algorithms and Architecture Advanced Chemical Physics Studies

Publication details

Journal / source
Chemical Reviews
Publisher
American Chemical Society (ACS)
Volume
126
Issue
1
Pages
184–203
Publication date
2 January 2026
Language
EN