Reaching for the performance limit of hybrid density functional theory for molecular chemistry
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866910069706194944 |
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| author | Liang, Jiashu Head-Gordon, Martin |
| author_facet | Liang, Jiashu Head-Gordon, Martin |
| contents | Density functional theory (DFT) offers an exceptional balance between accuracy and efficiency, but practical density functional approximations face an unavoidable trade-off among simplicity, accuracy, and transferability. A systematic protocol is therefore needed to develop functionals that are reliably most accurate within a chosen application domain. Here we present such a protocol by combining constraint enforcement, flexible functional forms, and modern optimization. Applying this strategy to the range-separated hybrid (RSH) meta-GGA framework, we obtain the carefully optimized and appropriately constrained hybrid (COACH) functional. Across broad molecular benchmarks, COACH improves both accuracy and transferability relative to leading RSH meta-GGAs, including \omegaB97M-V, while retaining the computational practicality of its rung. Finally, our analysis of the remaining trade-offs and saturation behavior suggests that further systematic progress will likely require the incorporation of genuinely nonlocal information. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_23466 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Reaching for the performance limit of hybrid density functional theory for molecular chemistry Liang, Jiashu Head-Gordon, Martin Chemical Physics Computational Physics Quantum Physics Density functional theory (DFT) offers an exceptional balance between accuracy and efficiency, but practical density functional approximations face an unavoidable trade-off among simplicity, accuracy, and transferability. A systematic protocol is therefore needed to develop functionals that are reliably most accurate within a chosen application domain. Here we present such a protocol by combining constraint enforcement, flexible functional forms, and modern optimization. Applying this strategy to the range-separated hybrid (RSH) meta-GGA framework, we obtain the carefully optimized and appropriately constrained hybrid (COACH) functional. Across broad molecular benchmarks, COACH improves both accuracy and transferability relative to leading RSH meta-GGAs, including \omegaB97M-V, while retaining the computational practicality of its rung. Finally, our analysis of the remaining trade-offs and saturation behavior suggests that further systematic progress will likely require the incorporation of genuinely nonlocal information. |
| title | Reaching for the performance limit of hybrid density functional theory for molecular chemistry |
| topic | Chemical Physics Computational Physics Quantum Physics |
| url | https://arxiv.org/abs/2603.23466 |