Nat. Commun. | 准确刻画化学键断裂的从头算波函数基础模型

TL;DR - A Nature Communications study introduces Orbformer, a transferable deep-QMC foundation model for ab initio electronic wavefunctions. By reusing learned electronic-structure patterns across molecules, it accurately models bond breaking and other strongly correlated processes at substantially lower computational cost.

• Orbformer was pretrained without external energy labels on 22,350 equilibrium and nonequilibrium molecular geometries, then jointly fine-tuned across related structures or reaction pathways.
• On five bond-dissociation curves, it matched or exceeded the accuracy–cost Pareto frontier of conventional quantum-chemistry methods and converged systematically toward roughly 1 kcal/mol chemical accuracy.
• Joint fine-tuning yielded about a 20× efficiency gain; pretraining provided further speedups, especially when the target chemistry resembled the pretraining distribution.
• The model generalized from systems with at most 24 electrons during pretraining to systems with up to 106 electrons and learned physically meaningful localized orbitals and reusable local electronic-structure patterns.