five

3D dust map from Green et al. (2017)

收藏
DataCite Commons2025-05-11 更新2025-05-17 收录
下载链接:
https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/LCYHJG
下载链接
链接失效反馈
官方服务:
资源简介:
A three-dimensional map of dust reddening, covering the three quarters of the sky surveyed by the Pan-STARRS 1 (PS1) survey. We use PS1 and 2MASS optical and near-infrared photometry to infer distances and reddenings to ~800 million stars. These stars trace the reddening along different lines of sight, allowing us to build up a map of reddening in 3D. This work builds on Green et al. (2015).<br/><br/> The map is structured as a set of sightlines, each of which contains multiple samples of the cumulative dust reddening as a function of distance. Each sightline is identified by a HEALPix nside parameter and nested pixel index. Within each sightline, cumulative reddening is given at discrete distances, spaced evenly in distance modulus. For each pixel, we provide multiple samples from the posterior on dust reddening.<br/><br/> Quality assurance information is given for each pixel, including:<br/> <ul> <li>Whether the fit converged in the pixel</li> <li>The minimum/maximum reliable distance moduli in the pixel</li> <li>The number of stars in the sightline</li> <li>The number of stars in the sightline with good convergence, and which passed a cut on Bayesian evidence (termed "good" stars)</li> <li>The number of "good" stars which are inferred to be Main-Sequence stars.</li> </ul><br/> Reddening is given in an arbitrary unit, which can be converted to extinction in the PS1 and 2MASS passbands by multiplying by the following coefficients:<br/> <ul> <li>g: 3.384</li> <li>r: 2.483</li> <li>i: 1.838</li> <li>z: 1.414</li> <li>y: 1.126</li> <li>J: 0.650</li> <li>H: 0.327</li> <li>Ks: 0.161</li> </ul><br/> The 3D map is described in more detail in Green et al. (2017), and tools for accessing the map are provided at <a href="http://argonaut.skymaps.info">argonaut.skymaps.info</a>. This map is included in the Python <a href="http://dustmaps.readthedocs.io/en/latest/">"dustmaps" package</a>, which can be installed on Linux/Mac systems with the following command:<br/><br/> <pre>pip install dustmaps</pre>
提供机构:
Harvard Dataverse
创建时间:
2017-09-20
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作