arXiv 1901.059712019-01astro-ph.GAastro-ph.SR

仅使用盖亚数据绘制附近尘埃云的图表

Charting nearby dust clouds using Gaia data only

R. H. Leike, T. A. Enßlin

发表信息：: A&A 631, A32 (2019)
DOI：: 10.1051/0004-6361/201935093

摘要：

目标：高分辨率的银河系局部尘埃图是天空辐射模型的一个重要组成部分。在几乎整个电磁波谱中，人们都能看到尘埃的痕迹，其中许多来自300 pc范围内的尘埃云。对这些局部尘埃云进行详细的3D重建可以进行详细的研究，有助于量化对其他可观测数据的影响，并且是实现更大重建所必需的里程碑，因为更遥远物体的每一条视线都将穿过局部尘埃。方法：为了推断尘埃密度，我们使用盖亚合作组织在其第二次数据发布中发布的视差和吸收估计。我们使用分层贝叶斯模型作为一个对数正态过程的灰尘模型。我们还推断非参数的对数正态过程，这对应于物理空间相关功率谱的对数密度的内核。结果如下：仅使用第二次盖亚数据发布的盖亚数据，我们重建了以太阳为中心的600pc立方体中的3D尘埃密度及其空间相关谱。本文报道了$3.1$的对数尘埃密度在傅立叶尺度上的光谱指数，波长在2pc和125pc之间。由此产生的3D尘埃图以及功率谱和后验样本可供下载。

英文摘要：

Aims: Highly resolved maps of the local Galactic dust are an important ingredient for sky emission models. In nearly the whole electromagnetic spectrum one can see imprints of dust, many of which originate from dust clouds within 300pc. Having a detailed 3D reconstruction of these local dust clouds enables detailed studies, helps to quantify the impact on other observables and is a milestone necessary to enable larger reconstructions, as every sightline for more distant objects will pass through the local dust. Methods: To infer the dust density we use parallax and absorption estimates published by the Gaia collaboration in their second data release. We model the dust as a log-normal process using a hierarchical Bayesian model. We also infer non-parametrically the kernel of the log-normal process, which corresponds to the physical spatial correlation power spectrum of the log-density. Results: Using only Gaia data of the second Gaia data release, we reconstruct the 3D dust density and its spatial correlation spectrum in a 600pc cube centered on the Sun. We report a spectral index of the logarithmic dust density of $3.1$ on Fourier scales with wavelengths between 2pc and 125pc. The resulting 3D dust map as well as the power spectrum and posterior samples are publicly available for download.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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