3 papers
physics.chem-ph2026
Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential
Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal +10
Electronic rearrangements associated with bond forming/breaking in catalytic enzymes require quantum mechanical (QM) treatment beyond classical molecular mechanics (MM). Hybrid QM/…
physics.comp-ph2026
Data-driven reconstruction of dynamical systems using Takens' Theorem, manifold learning, and universal function approximators
Maximilian Topel, Andrew L. Ferguson
Embedding theorems can be used to provide theoretical guarantees about the relation between low-dimensional observations of a system and its full-dimensional state and dynamics. Su…
cs.AI2025
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)
Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97
This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 w…