We present the new open source C++-based Python library CosTuuM that can be used to generate infrared absorption and emission coefficients for arbitrary mixtures of spheroidal dust grains that are (partially) aligned with a magnetic field. We outline the algorithms underlying the software, demonstrate the accuracy of our results using benchmarks from literature, and use our tool to investigate some commonly used approximative recipes. We find that the linear polarization fraction for a partially aligned dust grain mixture can be accurately represented by an appropriate linear combination of perfectly aligned grains and grains that are randomly oriented, but that the commonly used picket fence alignment breaks down for short wavelengths. We also find that for a fixed dust grain size, the absorption coefficients and linear polarization fraction for a realistic mixture of grains with various shapes cannot both be accurately represented by a single representative grain with a fixed shape, but that instead an average over an appropriate shape distribution should be used. Insufficient knowledge of an appropriate shape distribution is the main obstacle in obtaining accurate optical properties. CosTuuM is available as a standalone Python library and can be used to generate optical properties to be used in radiative transfer applications.

中文翻译：

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CosTuuM：磁性定向球粒的极化热粉尘发射

我们展示了新的基于 C++ 的开源 Python 库 CosTuuM，可用于为（部分）与磁场对齐的球状尘埃颗粒的任意混合物生成红外吸收和发射系数。我们概述了软件背后的算法，使用文献中的基准证明了我们结果的准确性，并使用我们的工具研究了一些常用的近似配方。我们发现，部分对齐的尘埃颗粒混合物的线性偏振分数可以通过完美对齐的颗粒和随机取向的颗粒的适当线性组合来准确表示，但常用的栅栏对齐在短波长时会失效。我们还发现，对于固定的粉尘粒度，具有各种形状的颗粒的实际混合物的吸收系数和线性极化率不能同时由具有固定形状的单个代表性颗粒准确表示，而应使用适当形状分布的平均值。对适当形状分布的了解不足是获得准确光学特性的主要障碍。CosTuuM 可作为独立的 Python 库使用，可用于生成用于辐射传输应用的光学特性。对适当形状分布的了解不足是获得准确光学特性的主要障碍。CosTuuM 可作为独立的 Python 库使用，可用于生成用于辐射传输应用的光学特性。对适当形状分布的了解不足是获得准确光学特性的主要障碍。CosTuuM 可作为独立的 Python 库使用，可用于生成用于辐射传输应用的光学特性。