We report a novel algorithm for generating optimized look-up tables suitable for rapid evaluation of various light scattering parameters and other hard-to-evaluate functions. Our method uses a stochastic algorithm to minimize the number of look-up table points needed while achieving high accuracy and speed. As an example, we present a general Mie scattering look-up table applicable to a large range of size parameters (0.02 < x < 200) and most materials (organics, inorganics, minerals, metals etc.) with real and imaginary parts of the refractive index ranging from 0.2 to 5 and 0 to 5, respectively. The look-up table is up to 3500 times faster than evaluating the Mie analytical expressions (in Matlab). This method opens up new possibilities in detection algorithm development (e.g. large synthetic datasets for machine learning), inverse problems and all other problems where a large number of Mie scattering coefficients needs to be rapidly evaluated. Furthermore, this method is applicable to other, related scattering problems. For example, we also present look-up tables for scattering efficiencies for spheres on various substrates.

中文翻译：

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随机算法，用于为各种尺寸参数和光学常数创建高精度优化的散射查找表


我们报道了一种新算法，用于生成优化的查找表，适用于快速评估各种光散射参数和其他难以评估的函数。我们的方法使用随机算法来最大限度地减少所需的查找表点的数量，同时实现高精度和速度。例如，我们提出了一个通用的 Mie 散射查找表，适用于大范围的尺寸参数 （0.02 < x < 200） 和大多数材料（有机物、无机物、矿物、金属等），折射率的实部和虚部分别为 0.2 到 5 和 0 到 5。查找表比计算 Mie 解析表达式（在 Matlab 中）快 3500 倍。这种方法为检测算法开发（例如用于机器学习的大型合成数据集）、逆问题以及需要快速评估大量 Mie 散射系数的所有其他问题开辟了新的可能性。此外，此方法适用于其他相关的散射问题。例如，我们还提供了各种衬底上球体散射效率的查找表。