Pushing the accuracy of on-top functionals with agent-driven supervised learning
Multiconfiguration pair-density functional theory (MC-PDFT) combines multiconfigurational reference wave functions with on-top functionals to provide an efficient electronic-structure method for strongly correlated molecular systems. We developed a large language model-based agent for functional development and combined multiple databases into the large, chemically diverse MCDDB26 database. We then used MCDDB26 to develop two on-top functionals, MC26 and COF26. MC26 retains an existing analytical form but substantially improves performance by refitting its linear parameters with optimised weights for the training datasets. Building on this result, we developed COF26, a general hybrid on-t...
| Authors | Yuhao Chen, Dayou Zhang, Donald G. Truhlar et al. |
|---|---|
| Primary category | physics.chem-ph |
| Published | 7 May 2026 |
| Last updated at source | 28 September 2026 |
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