Masses and Ages for 230,000 LAMOST Giants, via Their Carbon and Nitrogen Abundances
Anna Y. Q. Ho (Caltech, MPIA), Hans-Walter Rix (MPIA), Melissa K. Ness, (MPIA), David W. Hogg (SCDA, NYU, MPIA), Chao Liu (Key Laboratory of Optical, Astronomy), Yuan-Sen Ting (Harvard)

TL;DR
This study develops a data-driven spectral model to accurately determine carbon, nitrogen, mass, and age for hundreds of thousands of giant stars using low-resolution spectra, vastly expanding stellar parameter catalogs.
Contribution
It introduces a novel application of The Cannon to infer stellar masses and ages from low-resolution spectra, leveraging APOGEE data for calibration and achieving high precision across a large star sample.
Findings
Measured [C/M] and [N/M] to within 0.1 dex for 450,000 stars.
Inferred stellar masses and ages for 230,000 stars with high accuracy.
Created the largest catalog of stellar ages and masses from low-resolution spectra.
Abstract
We measure carbon and nitrogen abundances to 0.1 dex for 450,000 giant stars from their low-resolution (R1800) 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: Teff, logg, [M/H], [/M], [C/M], [N/M], and Ak. We add seven colors to the Cannon model, based on the g, r, i, J, H, K, W1, and W2 magnitudes from APASS, 2MASS & WISE, which improves our constraints on Teff and logg by up to 20% and on Ak by up to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
