Machine learning method for tight-binding Hamiltonian parameterization from ab-initio band structure
Abstract The tight-binding (TB) method is an ideal candidate for determining electronic and transport properties for a large-scale system. It describes the system as real-space Hamiltonian matrices expressed on a manageable number of parameters, leading to substantially lower computational costs tha...
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| Main Authors: | , , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/5828919a2b55495b889aabfc55773a47 |
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