Scaling Density Functional Theory with Gaussian Splatting
Density functional theory (DFT) strikes a practical balance between accuracy and computational cost in many problems of computational chemistry and materials science. However, many DFT calculations are limited by fixed atom-centered basis sets, which dictate how accuracy and cost scale with system size. We propose Gaussian Splatting for Density Functional Theory (GS-DFT), which represents molecular orbitals as a cloud of Gaussians whose positions, shapes, and mixing coefficients are optimized jointly by gradient descent to minimize the energy without training data. Conceptually, GS-DFT is 3D Gaussian splatting with the renderer replaced by quantum mechanics. We introduce two key solver co...
| Authors | Andrés Guzmán-Cordero, Cindy Zhang, Majdi Hassan et al. |
|---|---|
| Primary category | physics.chem-ph |
| Published | 25 September 2026 |
| Last updated at source | 25 September 2026 |
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