Resolving finite-size errors in EOM-CCSD band gaps of solids with interacting-bath dynamical embedding theory
Periodic equation-of-motion coupled-cluster theory with single and double excitations (EOM-CCSD) has shown promise for quantitative calculations of band structures in solids. However, its steep computational scaling has limited calculations to relatively coarse k-point meshes, leading to sizable finite-size errors and discrepant estimates of thermodynamic-limit band gaps in recent benchmarks. In this work, we revisit EOM-CCSD band gaps for ten semiconductors and insulators using interacting-bath dynamical embedding theory (ibDET), a systematically improvable Green's function embedding framework that enables dense Brillouin-zone sampling at modest computational cost. By pushing the k-point sampling up to 10 × 10 × 10, well beyond the system sizes accessible in canonical periodic EOM-CCSD calculations, we significantly reduce finite-size errors and obtain stable thermodynamic-limit extrapolations. We further compare G0W0@PBE, G0W0@HF, and EOM-CCSD on an equal footing using the same numerical settings in PySCF. We find that EOM-CCSD yields a mean absolute error of 0.32 eV relative to experimental band gaps for a test set of ten semiconductors and insulators, which is lower than that of G0W0@PBE. For ZnO, EOM-CCSD also accurately describes the Zn 3d-band binding energy, despite overestimating the band gap. These results demonstrate that ibDET offers a practical route to high-accuracy many-body electronic structure calculations in periodic systems.
Authors
- Christopher Hillenbrand (ORCID: https://orcid.org/0009-0000-2682-070X)
- Christian Venturella (ORCID: https://orcid.org/0009-0005-0355-8485)
- Enzhi Chen
- Tianyu Zhu
- Jiachen Li
Institutions
- Yale University (US)
Publication Details
- Journal
- The Journal of Chemical Physics
- Published
- 2026-09-01
- DOI
- https://doi.org/10.1063/5.0347878
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- National Defense Science and Engineering Graduate