Stellar parameters from Green et al. (2019)
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/AV9GXO
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资源简介:
Stellar parameters for 799 million stars, inferred by Green <i>et al.</i> (2019). The four parameters we infer are:<br/>
<ul>
<li>Distance modulus ("dm")</li>
<li>Reddening ("E")</li>
<li>Absolute r<sub>P1</sub> magnitude ("Mr")</li>
<li>Metallicity ("FeH")</li>
</ul>
These parameters are inferred by modeling the broad-band Pan-STARRS 1 and 2MASS photometry of the stars, as well as their Gaia DR2 parallaxes. We take into account priors on the distribution of stars of different types throughout the Milky Way.
Reddening is given in an arbitrary unit, which can be converted to magnitudes of extinction in the PS1 and 2MASS passbands by multiplying by the following coefficients:<br/>
<ul>
<li>g<sub>P1</sub>: 3.518</li>
<li>r<sub>P1</sub>: 2.617</li>
<li>i<sub>P1</sub>: 1.971</li>
<li>z<sub>P1</sub>: 1.549</li>
<li>y<sub>P1</sub>: 1.263</li>
<li>J: 0.7927</li>
<li>H: 0.4690</li>
<li>K<sub>s</sub>: 0.3026</li>
</ul>
The catalog is split into files containing approximately 8 million stars each. Each file contains the following groups:
<ul>
<li><i>metadata</i>: the locations of the stars, as well as a unique identifier for each star</li>
<li><i>data</i>: The PS1/2MASS photometry and Gaia DR2 parallaxes used to infer the stellar parameters</li>
<li><i>chisq</i>: The maximum-likelihood χ<sup>2</sup>/passband for the each star</li>
<li><i>samples</i>: Samples drawn from the posterior distribution of the stellar parameters, as well as the corresponding log likelihoods and priors</li>
<li><i>percentiles</i>: 16<sup>th</sup>, 50<sup>th</sup> and 84<sup>th</sup> percentiles of the marginal distribution of each parameter</li>
<li><i>gaia</i>: Gaia DR2 <code>source_id</code>. Additionally, the 16<sup>th</sup>, 50<sup>th</sup> and 84<sup>th</sup> percentiles of <i>E(BP-RP)</i> and <i>A<sub>G</sub></i> reported by Andrae <i>et al.</i> (2018)</li>
</ul>
Within each group, the stars are divided into datasets corresponding to an <code>nside = 32</code> HEALPix pixelization of the sky, with nested ordering, in Galactic coordinates.
提供机构:
Harvard Dataverse
创建时间:
2019-05-07



