The data catalog for Metallicity and alpha-abundance for 48 million stars in low-extinction regions in the Milky Way

<p>Stellar chemistry contains information on the environment in which the star was born. Therefore, measuring the chemical abundances of stars in the Milky Way, such as the overall metallicity [M/H] and the alpha-abundance [alpha/M], is essential in Galactic astronomy.</p> <p>We estimate ([M/H], [alpha/M]) for giants and dwarfs in low dust extinction region from the Gaia DR3 XP spectra by using tree-based machine-learning models trained on APOGEE DR17 (Abdurro&rsquo;uf et al. 2022) and the metal-poor star sample of Li et al. (2022).</p> <p>Here, we upload the catalogues of ([M/H], [alpha/M]) for 182 million stars. The data are divided into 10 fits files. The i-th file (i=1,2,...,10) contains stars with E(B-V) value between 0.1*(i-1) and 0.1*i. Because our machine-learning models are trained on stars with low dust extinction (E(B-V)&lt;0.1), we recommend using 48 million stars with low-dust extinction region with 0&lt;E(B-V)&lt;0.1 (table_light_mh_am_0p0ebv0p1.fits). The description for each column of the data is shown in column_description.png.&nbsp;</p> <p>The source paper of this catalog:</p> <ul> <li>Kohei Hatori "Metallicity and alpha-abundance for 48 million stars in low-extinction regions in the Milky Way" <br>https://iopscience.iop.org/article/10.3847/1538-4357/ad9686</li> </ul> <p>References:</p> <div> <div> <div> <ul> <li>Abdurro&rsquo;uf, Accetta, K., Aerts, C., et al. 2022, ApJS, 259, 1026 &nbsp;35, doi: 10.3847/1538-4365/ac4414</li> </ul> </div> </div> </div> <ul> <li>Li, H., Aoki, W., Matsuno, T., et al. 2022, ApJ, 931, 147, doi: 10.3847/1538-4357/ac6514</li> </ul> <p>&nbsp;</p>