RPA：一种计算静态非线性光学性质的精确且快速的方法
RPA, an accurate and fast method for the computation of static non-linear optical properties
AI总结：
本文提出利用随机相近似（RPA）结合有限差分法计算大型聚合物的静态非线性光学性质，其精度媲美最优双杂化泛函且无需系统特定调整。
摘要：
准确计算大型聚合物中的非线性光学性质（NLOPs）需要以合理的计算成本考虑电子相关效应。已知在绝热连接涨落定理中使用的随机相近似（RPA）是一种可靠且高性价比的方法，当与密度拟合技术和虚频积分相结合时，能够呈现电子相关效应。我们通过在有限电场存在下评估RPA电子能量，探索了RPA能量表达式预测NLOPs的能力，并使用有限差分法获得了静态极化率和超极化率。结果表明，基于杂化泛函自洽场计算的RPA所得到的NLOPs与当今开发的最优调谐双杂化泛函一样准确，且RPA具有避免任何特定系统调整的额外优势。
英文摘要：
The accurate computation of non-linear optical properties (NLOPs) in large polymers requires accounting for electronic correlation effects with a reasonable computational cost. The Random Phase Approximation (RPA) used in the adiabatic connection fluctuation theorem is known to be a reliable and cost-effective method to render electronic correlation effects when combined with the density-fitting techniques and the integration over imaginary frequencies. We explore the ability of the RPA energy expression to predict NLOPs by evaluating RPA electronic energies in the presence of finite electric fields to obtain (using the finite difference method) static polarizabilities and hyper-polarizabilities. We show that RPA based on hybrid functional self-consistent field calculations yields as accurate NLOPs as the best-tuned double-hybrid functionals developed today, with the additional advantage that RPA avoids any system-specific adjustment.
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