Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
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2026
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| author | Elsborg, Jonas Ærtebjerg, Felix Thiede, Luca Aspuru-Guzik, Alán Vegge, Tejs Bhowmik, Arghya |
| author_facet | Elsborg, Jonas Ærtebjerg, Felix Thiede, Luca Aspuru-Guzik, Alán Vegge, Tejs Bhowmik, Arghya |
| contents | We introduce ELECTRAFI, a fast, end-to-end differentiable model for predicting periodic charge densities in crystalline materials. ELECTRAFI constructs anisotropic Gaussians in real space and exploits their closed-form Fourier transforms to analytically evaluate plane-wave coefficients via the Poisson summation formula. This formulation delegates non-local and periodic behavior to analytic transforms, enabling reconstruction of the full periodic charge density with a single inverse FFT. By avoiding explicit real-space grid probing, periodic image summation, and spherical harmonic expansions, ELECTRAFI matches or exceeds state-of-the-art accuracy across periodic benchmarks while being up to $633 \times$ faster than the strongest competing method, reconstructing crystal charge densities in a fraction of a second. When used to initialize DFT calculations, ELECTRAFI reduces total DFT compute cost by up to ~20%, whereas slower charge density models negate savings due to high inference times. Our results show that accuracy and inference cost jointly determine end-to-end DFT speedups, and motivate our focus on efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_19966 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink Elsborg, Jonas Ærtebjerg, Felix Thiede, Luca Aspuru-Guzik, Alán Vegge, Tejs Bhowmik, Arghya Materials Science Machine Learning Chemical Physics Computational Physics We introduce ELECTRAFI, a fast, end-to-end differentiable model for predicting periodic charge densities in crystalline materials. ELECTRAFI constructs anisotropic Gaussians in real space and exploits their closed-form Fourier transforms to analytically evaluate plane-wave coefficients via the Poisson summation formula. This formulation delegates non-local and periodic behavior to analytic transforms, enabling reconstruction of the full periodic charge density with a single inverse FFT. By avoiding explicit real-space grid probing, periodic image summation, and spherical harmonic expansions, ELECTRAFI matches or exceeds state-of-the-art accuracy across periodic benchmarks while being up to $633 \times$ faster than the strongest competing method, reconstructing crystal charge densities in a fraction of a second. When used to initialize DFT calculations, ELECTRAFI reduces total DFT compute cost by up to ~20%, whereas slower charge density models negate savings due to high inference times. Our results show that accuracy and inference cost jointly determine end-to-end DFT speedups, and motivate our focus on efficiency. |
| title | Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink |
| topic | Materials Science Machine Learning Chemical Physics Computational Physics |
| url | https://arxiv.org/abs/2601.19966 |