Stochastic GW -GPU: Rapid Quasi-Particle Energies for Molecules beyond 10,000 Atoms
Abstract
Stochastic GW is a code for computing accurate quasi-particle (QP) energies of molecules and material systems in the GW approximation. Stochastic GW utilizes the stochastic Resolution of the Identity (sROI) technique to enable a massively parallel implementation with computational costs that scale semilinearly with system size, allowing the method to access systems with tens of thousands of electrons. We introduce a new implementation, Stochastic GW – GPU, for which the main bottleneck steps have been ported to GPUs and give substantial performance improvements over previous versions of the code. We showcase the new code by computing band gaps of hydrogenated silicon clusters (Si x H y ) containing up to 10,001 atoms and 35,144 electrons, and we obtain individual QP energies with a statistical precision of better than ±0.03 eV with times-to-solution of less than 1 h.
Fields of Study & Subjects
Advanced Chemical Physics Studies
Machine Learning in Materials Science
Advanced Physical and Chemical Molecular Interactions
Publication details
- Journal / source
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Volume
- 22
- Issue
- 8
- Pages
- 3960–3970
- Publication date
- 7 April 2026
- Language
- EN