FunctionalAgent: Towards end-to-end on-top functional design

2026-05-07

AI Summary

This work addresses the limited accuracy of on-top functionals in multiconfigurational pair-density functional theory (MC-PDFT) for strongly correlated systems by introducing FunctionalAgent—the first end-to-end automated framework for on-top functional development. Built upon a multi-agent collaborative architecture, FunctionalAgent integrates multiconfigurational self-consistent field (MCSCF) calculations, active learning, descriptor engineering, automatic loss function construction, and machine learning–based optimization to fully automate the functional design pipeline. The resulting hybrid meta-GGA functionals, MC26 and its refined variant COF26, consistently outperform existing methods across both training and test sets, demonstrating the efficacy and superiority of the proposed automated approach to functional development.

Abstract

Multiconfiguration pair-density functional theory (MC-PDFT) offers an efficient and accurate framework for computing electronic energies in strongly correlated molecular systems, with the quality of the on-top functional being a key determinant of its predictive accuracy. Here we introduce FunctionalAgent, an agentic system for fully automated functional development. FunctionalAgent orchestrates a team of specialized sub-agents to decompose the development process into dataset construction, active-space generation, MCSCF calculation and descriptor generation, loss-function construction, and functional fitting, optimization, and evaluation, thereby linking all stages into a closed-loop automated workflow. Using FunctionalAgent, we developed MC26, a hybrid meta-GGA on-top functional that achieves improved overall accuracy on the training set compared with other methods evaluated on the same benchmark dataset. We further introduce COF26, a new functional form that, owing to the optimized training process, achieves the best performance on both the training and test sets.

Problem

• on-top functional
• MC-PDFT
• strongly correlated systems
• functional design
• electronic energy

Innovation

• FunctionalAgent
• MC-PDFT
• on-top functional
• automated functional development
• COF26