ArticleJournal of chemical theory and computation2023
Effective Reconstruction of Expectation Values from Ab Initio Quantum Embedding.
Article in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 21 citations in OpenAlex.
- Molecular Quantum Computations on a Protein.Journal of chemical theory and computation · 2026Article
- A multi-resolution systematically improvable quantum embedding scheme for large-scale surface chemistry calculations.Nature communications · 2025Article
- Automatic Molecule Fragmentation for Density Matrix Embedding Theory.The journal of physical chemistry. A · 2025Article
- Dissociation Energies via Embedding Techniques.The journal of physical chemistry. A · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
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Abstract
Quantum embedding is an appealing route to fragment a large interacting quantum system into several smaller auxiliary "cluster" problems to exploit the locality of the correlated physics. In this work, we critically review approaches to recombine these fragmented solutions in order to compute nonlocal expectation values, including the total energy. Starting from the democratic partitioning of expectation values used in density matrix embedding theory, we motivate and develop a number of alternative approaches, numerically demonstrating their efficiency and improved accuracy as a function of increasing cluster size for both energetics and nonlocal two-body observables in molecular and solid state systems. These approaches consider the
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