TNFlow: Amortized Posterior Inference for Trans-Neptunian Object Surface Composition

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On September 7, 2026, arXiv cs.LG published the paper “TNFlow: Amortized Posterior Inference for Trans-Neptunian Object Surface Composition”. This study proposed the TNFlow model for amortized posterior inference of the surface composition of trans-Neptunian objects.

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JWSTShkuratov radiative transfer modelTNFlowarXiv:2609.04305v1

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TNFlow1
arXiv:2609.04305v11
Shkuratov radiative transfer model1
JWST1

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A arXiv cs.LG en 2026-09-07 12:00

研究人员提出了 TNFlow，这是一种用于从反射光谱推断外海王星天体表面组成的架构。该模型在由 Shkuratov 辐射传输模型生成的合成光谱上训练作为其逆运算器，单核 CPU 处理单个光谱仅需约 0.7 秒，输出包含成分和粒径的多模态后验分布。在测试集上，最高权重模式与真实值的平均总变差距离为 0.149，且模型对已知成分的未见组合具有良好的泛化能力。然而，对真实 JWST 光谱的定性测试显示模型存在对某些材料的盲目性或偏差，这可能归因于模拟器保真度或训练集问题。