用局部高斯函数快速生成晶体电荷密度，精度高且速度超快。
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
- 基于实空间各向异性高斯函数与傅里叶变换，解析计算平面波系数。
- 在周期性基准上精度达顶尖水平，最快比竞品快633倍。
- 适合需要快速初始化密度泛函计算的材料模拟研究者。
我们提出ELECTRAFI，一种快速、端到端可微的模型，用于预测晶体材料中的周期性电荷密度。ELECTRAFI在实空间构建各向异性高斯函数，并利用其闭式傅里叶变换，通过泊松求和公式解析计算平面波系数。该方法将非局部与周期性行为交由解析变换处理，仅需一次逆FFT即可重建完整周期性电荷密度。通过避免显式的实空间网格探测、周期图像求和及球谐展开，ELECTRAFI在周期性基准上达到或超越现有最先进精度，同时比最强竞争方法快最多633倍，可在不到一秒内完成晶体电荷密度重建。用于初始化密度泛函理论（DFT）计算时，可将总DFT计算成本降低约20%；而更慢的电荷密度模型因推断时间过长反而抵消节省。结果表明，精度与推断成本共同决定端到端DFT加速效果，凸显效率的重要性。
原文摘要 · Abstract (English)
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.
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