Mass and Age determination of the LAMOST data with different Machine Learning methods

Abstract

We present a catalog of 948,216 stars with mass label and a catalog of 163,105 red clump (RC) stars with mass and age labels simultaneously. The training dataset is cross matched from the LAMOST (The Large Sky Area Multi-Object Fiber Spectroscopic Telescope) DR5 and high resolution asteroseismology data, mass and age are predicted by random forest method or convex hull algorithm. The stellar parameters with high correlation with mass and age are extracted and the test dataset shows that the median relative error of the prediction model for the mass of large sample is 3\% and meanwhile, the mass and age of red clump stars are 4\% and 7\%. We also compare the predicted age of red clump stars with the recent works and find that the final uncertainty of the RC sample could reach 18\% for age and 9\% for mass, in the meantime, final precision of the mass for large sample with different type of stars could reach 13\% without considering systematics, all these are implying that this method could be widely used in the future. Moreover, we explore the performance of different machine learning methods for our sample, including bayesian linear regression (BYS), gradient boosting decision Tree (GBDT), multilayer perceptron (MLP), multiple linear regression (MLR), random forest (RF) and support vector regression (SVR). Finally we find that the performance of nonlinear model is generally better than that of linear model, and the GBDT and RF methods are relatively better.

19 pages, 23 figures, Accepted for publication in the ApJS

References in corpus (13)

• Structure and Evolution of Nearby Stars with Planets II. Physical Properties of ~1000 Cool Stars from the SPOCS Catalog
• Self-consistent Stellar Radial Velocities from LAMOST Medium-Resolution Survey (MRS) DR7
• The K2 M67 Study: Revisiting old friends with K2 reveals oscillating red giants in the open cluster M67
• A new standard: Age and distance for the open cluster NGC 6791 from the eclipsing binary member V20
• Ages and masses of million Galactic disk main sequence turn-off and sub-giant stars from the LAMOST Galactic spectroscopic surveys
• Mapping the Galactic disk with the LAMOST and Gaia Red clump sample: I: precise distances, masses, ages and 3D velocities of $\sim$ 140000 red clump stars
• Ages and Masses of 0.64 million Red Giant Branch stars from the LAMOST Galactic Spectroscopic Survey
• Detection and characterisation of oscillating red giants: first results from the TESS satellite
• Prospects for Galactic and stellar astrophysics with asteroseismology of giant stars in the $TESS$ Continuous Viewing Zones and beyond
• Mapping the Galactic disk with the LAMOST and Gaia Red clump sample. VI: An evidence for the long lived non-steady warp of non-gravitational scenarios
• TESS asteroseismology of the Kepler red giants
• BVI photometry of the very old open cluster Berkeley 17
• Photospheric diagnostics of core helium burning in giant stars

Cited by in corpus (3)

• The [Y/Mg] chemical clock in the Galactic Disk: The influence of metallicity and Galactic population in the solar neighbourhood
• Evidence for Populations-dependent vertical motions and the Long-lived Non-Steady Lopsided Milky Way Warp
• Kinematic-Chemical analysis and Time tagging for the Diagonal Ridge Structure of the Galactic Outer Disk with LAMOST Red Giant Branch Stars