Simulon: An AI-Assisted, PyTorch-Native Framework of Molecular Dynamics and Modeling

The growing complexity of modern molecular simulations calls for new frameworks that unify physical modeling, machine learning, and human-AI interaction in the era of artificial intelligence. Simulon is an open-source, PyTorch-native molecular dynamics (MD) platform designed to bridge MD and artificial intelligence through a tensor-based architecture. By representing atomic systems, forces, and trajectories as differentiable tensors, Simulon enables end-to-end learning over molecular data while leveraging GPU hardware and PyTorch software to accelerate simulations. Compared with other similar frameworks, Simulon employs a highly optimized tensor-based computational kernel, achieving substantial speedup. A retrieval-augmented large language model (LLM) agent serves as an intelligent interface, translating natural-language instructions into executable simulation workflows and analytical routines, which allow scientists to configure, execute, and interpret MD simulations conversationally, forming an autonomous loop between physical computation and semantic intent. This integration can relieve scientists of tedious data processing jobs and enable them to focus on more creative work. Simulon supports both classical and machine-learning potentials under GPU acceleration and achieves quantitative agreement with established engines such as LAMMPS while maintaining ML compatibility. By combining differentiable simulation, scalable computation, and natural-language control, Simulon establishes a new paradigm for AI-assisted molecular modeling-where chemical information, data-driven potentials, and autonomous agents converge to accelerate scientific discovery.