科研速览 · Science Skim继续刷下去 · Keep skimming →
◆ Chemical Reviews2026-01-02· Chemistry

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

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

原始摘要(英文原文)· Original 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.
读原文 · Read the paper ↗

AI 追问PRO

登录后使用 AI 追问

讨论区

登录后参与讨论

相关论文 · Related

Multireference Embedding and Fragmentation Methods for Classical and Quantum Computers: From Model Systems to Realistic Applications — 科研速览 Science Skim