Low-Scaling algorithms for $GW$ and constrained random phase approximation using symmetry-adapted interpolative separable density fitting
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866911762950914048 |
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| author | Yeh, Chia-Nan Morales, Miguel A. |
| author_facet | Yeh, Chia-Nan Morales, Miguel A. |
| contents | We present low-scaling algorithms for $GW$ and constrained random phase approximation based on a symmetry-adapted interpolative separable density fitting (ISDF) procedure that incorporates the space-group symmetries of crystalline systems. The resulting formulations scale cubically with respect to system sizes and linearly with the number of $\mathbf{k}$-points, regardless of the choice of single-particle basis and whether a quasiparticle approximation is employed. We validate these methods through comparisons with published literature and demonstrate their efficiency in treating large-scale systems through the construction of downfolded many-body Hamiltonians for carbon dimer defects embedded in hexagonal boron nitride supercells. Our work highlights the efficiency and general applicability of ISDF in the context of large-scale many-body calculations with $\mathbf{k}$-point sampling beyond density functional theory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_12308 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Low-Scaling algorithms for $GW$ and constrained random phase approximation using symmetry-adapted interpolative separable density fitting Yeh, Chia-Nan Morales, Miguel A. Materials Science Chemical Physics Computational Physics We present low-scaling algorithms for $GW$ and constrained random phase approximation based on a symmetry-adapted interpolative separable density fitting (ISDF) procedure that incorporates the space-group symmetries of crystalline systems. The resulting formulations scale cubically with respect to system sizes and linearly with the number of $\mathbf{k}$-points, regardless of the choice of single-particle basis and whether a quasiparticle approximation is employed. We validate these methods through comparisons with published literature and demonstrate their efficiency in treating large-scale systems through the construction of downfolded many-body Hamiltonians for carbon dimer defects embedded in hexagonal boron nitride supercells. Our work highlights the efficiency and general applicability of ISDF in the context of large-scale many-body calculations with $\mathbf{k}$-point sampling beyond density functional theory. |
| title | Low-Scaling algorithms for $GW$ and constrained random phase approximation using symmetry-adapted interpolative separable density fitting |
| topic | Materials Science Chemical Physics Computational Physics |
| url | https://arxiv.org/abs/2401.12308 |