GS-DFT scales DFT with Gaussian Splatting, hits 2,742 atoms on four H200 GPUs
AllThingsApx · x · 2026-09-28
A new paper (arXiv:2609.31483) introduces GS-DFT, representing molecular orbitals as a cloud of Gaussians whose positions, shapes, and mixing coefficients are jointly optimized by gradient descent to minimize energy — no training data needed. Conceptually it's "3D Gaussian splatting with the renderer replaced by quantum mechanics."
- Key components: adaptive density fitting with screening for two-electron integrals, and regularized differentiable orbital orthogonalization
- Accuracy: matches the largest conventional basis sets with a fraction of the parameters, converging systematically in energy, density, and forces; captures stretched-bond and anion physics at equal parameter count
- Scale: quadratic peak memory scaling allows simulating up to 2,742 atoms (10,406 electrons) at triple-zeta on a single 4×H200 node
Paper and code are public; the next frontier is reliable forces at lower compute cost.
Related event: GS-DFT Scales Quantum Chemistry to 2,742 Atoms via Gaussian Splatting(4 posts)→
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