(566b) Pysages: Flexible, Efficient, GPU-Accelerated Sampling Methods

Molecular Dynamics simulations are critical for understanding and predicting molecular properties, but determining the free energy of complex systems requires advanced sampling techniques. PySAGES is a Python open-source library that provides enhanced sampling methods for molecular dynamics simulations, including adaptive forces, harmonic bias, and forward flux sampling. PySAGES is designed for massive parallel applications and provides full GPU support, making it an efficient and scalable tool for exploring complex free energy landscapes. The software features an intuitive interface that facilitates inclusion of new collective variables and sampling methods. This work introduces the core features of PySAGES and provides concise examples of its capabilities, including benchmark results that demonstrate its performance. PySAGES is a versatile and efficient tool for studying complex molecular systems, advancing our understanding of molecular properties, and enabling the design of new materials.

*This work was supported by MICCoM, as part of the Computational Materials Sciences Program funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences, and Engineering Division through Argonne National Laboratory.