  The LAMOST survey has acquired low-resolution spectra (R=1,800) for 5 million
stars across the Milky Way, far more than any current stellar survey at a
corresponding or higher spectral resolution. It is often assumed that only very
few elemental abundances can be measured from such low-resolution spectra,
limiting their utility for Galactic archaeology studies. However, Ting et al.
(2017) used ab initio models to argue that low-resolution spectra should enable
precision measurements of many elemental abundances, at least in theory. Here
we verify this claim in practice by measuring the relative abundances of 14
elements from LAMOST spectra with a precision of $\lesssim$ 0.1 dex for objects
with ${\rm S/N}_{\rm LAMOST}$ > 30 (per pixel). We employ a spectral modeling
method in which a data-driven model is combined with priors that the model
gradient spectra should resemble ab initio spectral models. This approach
assures that the data-driven abundance determinations draw on physically
sensible features in the spectrum in their predictions and do not just exploit
astrophysical correlations among abundances. Our analysis is constrained to the
number of elemental abundances measured in the APOGEE survey, which is the
source of the training labels. Obtaining high quality/resolution spectra for a
subset of LAMOST stars to measure more elemental abundances as training labels
and then applying this method to the full LAMOST catalog will provide a sample
with more than 20 elemental abundances that is an order of magnitude larger
than current high-resolution surveys, substantially increasing the sample size
for Galactic archaeology.
