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Chemical tagging has great promise as a technique to unveil our Galaxys history. Grouping stars based on their similar chemistry can establish details of the star formation and merger history of the Milky Way. With precise measurements of stellar chemistry, chemical tagging may be able to group together stars born from the same gas cloud, regardless of their current positions and kinematics. Successfully tagging these birth clusters requires high quality chemical space information and a good cluster-finding algorithm. To test the feasibility of chemical tagging on data from current and upcoming spectroscopic surveys, we construct a realistic set of synthetic clusters, creating both observed spectra and derived chemical abundances for each star. We use Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to group stars based on their spectra or abundances; these groups are matched to input clusters and are found to be highly homogeneous and complete. The percentage of clusters with more than 10 members recovered is 40% when tagging on abundances with uncertainties achievable with current techniques. Based on our fiducial model for the Milky Way, we predict recovering over 600 clusters with at least 10 observed members and 70% membership homogeneity in a sample similar to the APOGEE survey. Tagging larger surveys like the GALAH survey and the future Milky Way Mapper in SDSS V could recover tens of thousands of clusters at high homogeneity. Access to so many unique co-eval clusters will transform how we understand the star formation history and chemical evolution of our Galaxy.
We measure chemical abundances for over 20 elements of 15 N-rich field stars with high resolution ($R sim 30000$) optical spectra. We find that Na, Mg, Al, Si, and Ca abundances of our N-rich field stars are mostly consistent with those of stars from
Using the observed submillimetre source counts, from 250-1200 microns (including the most recent 250, 350 and 500 micron counts from BLAST), we present a model capable of reproducing these results, which is used as a basis to make predictions for upc
Improving distance measurements in large imaging surveys is a major challenge to better reveal the distribution of galaxies on a large scale and to link galaxy properties with their environments. Photometric redshifts can be efficiently combined with
We present a study using the second data release of the GALAH survey of stellar parameters and elemental abundances of 15 pairs of stars identified by Oh et al 2017. They identified these pairs as potentially co-moving pairs using proper motions and