Journal
ASTROPHYSICAL JOURNAL
Volume 841, Issue 1, Pages -Publisher
IOP Publishing Ltd
DOI: 10.3847/1538-4357/aa6db3
Keywords
methods: data analysis; methods: statistical; stars: abundances; stars: fundamental parameters; surveys; techniques: spectroscopic
Categories
Funding
- MPIA
- Miller Institute at UC Berkeley
- National Science Foundation [DGE1144469]
- European Research Council under the European Union's Seventh Framework Programme (FP 7) ERC Grant [321035]
- NSF [IIS-1124794]
- NASA [NNX08AJ48G]
- Moore-Sloan Data Science Environment at NYU
- Strategic Priority Research Program The Emergence of Cosmological Structures of the Chinese Academy of Sciences [XDB09000000]
- National Key Basic Research Program of China [2014CB845700]
- National Natural Science Foundation of China (NSFC) grant [11373032, 11333003]
- National Development and Reform Commission
- Alfred P. Sloan Foundation
- U.S. Department of Energy Office of Science
- Brazilian Participation Group
- Carnegie Institution for Science
- Carnegie Mellon University
- Chilean Participation Group
- French Participation Group
- Harvard-Smithsonian Center for Astrophysics
- Instituto de Astrofisica de Canarias
- Johns Hopkins University
- Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo
- Lawrence Berkeley National Laboratory
- Leibniz Institut fur Astrophysik Potsdam (AIP)
- Max-Planck-Institut fur Astronomie (MPIA Heidelberg)
- Max-Planck-Institut fur Astrophysik (MPA Garching)
- Max-Planck-Institut fur Extraterrestrische Physik (MPE)
- National Astronomical Observatory of China
- New Mexico State University
- New York University
- University of Notre Dame
- Observatario Nacional/MCTI
- Ohio State University
- Pennsylvania State University
- Shanghai Astronomical Observatory
- United Kingdom Participation Group
- Universidad Nacional Autonoma de Mexico
- University of Arizona
- University of Colorado Boulder
- University of Oxford
- University of Portsmouth
- University of Utah
- University of Virginia
- University of Washington
- University of Wisconsin
- Vanderbilt University
- Yale University
- Robert Martin Ayers Sciences Fund
- National Aeronautics and Space Administration
- National Science Foundation
- Center for High-Performance Computing at the University of Utah
Ask authors/readers for more resources
We measure carbon and nitrogen abundances to a precision of less than or similar to 0.1 dex for 450,000 giant stars from their low-resolution (R similar to 1800) LAMOST DR2 survey spectra. We use these [C/M] and[N/M] measurements, together with empirical relations based on the APOKASC sample, to infer stellar masses and implied ages for 230,000 of these objects to 0.08 dex and 0.2 dex respectively. We use The. Cannon, a data-driven approach to spectral modeling, to construct a predictive model for LAMOST spectra. Our reference set comprises 8125 stars observed in common between the APOGEE and LAMOST surveys, taking seven APOGEE DR12 labels (parameters) as ground truth: T-eff, log g,[M/H],[alpha/M], [C/M],[N/M], and A(k). We add seven colors to the Cannon model, based on the g, r, i, J, H, K, W1, W2 magnitudes from APASS, 2MASS, and WISE, which improves our constraints on T-eff and log g by up to 20% and on A(k) by up to 70%. Cross-validation of the model demonstrates that, for high-S/N objects, our inferred labels agree with the APOGEE values to within 50 K in temperature, 0.04 mag in A(k), and <0.1 dex in log g,[M/H], [C/M],[N/M], and[alpha/M]. We apply the model to 450,000 giants in LAMOST DR2 that have not been observed by APOGEE. This demonstrates that precise individual abundances can be measured from low-resolution spectra. and represents the largest catalog to date of homogeneous stellar [C/M],[N/M], masses, and ages. As a result, we greatly increase the number and sky coverage of stars with mass and age estimates.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available