SPT: Spectral Transformer for Red Giant Stars Age and Mass Estimation
Mengmeng Zhang Fan Wu Yude Bu Shanshan Li Zhenping Yi Meng Liu Xiaoming Kong
The age and mass of red giants are essential for understanding the structure
and evolution of the Milky Way. Traditional isochrone methods for these
estimations are inherently limited due to overlapping isochrones in the
Hertzsprung-Russell diagram, while asteroseismology, though more precise,
requires high-precision, long-term observations. In response to these
challenges, we developed a novel framework, Spectral Transformer (SPT), to
predict the age and mass of red giants aligned with asteroseismology from their
spectra. A key component of SPT, the Multi-head Hadamard Self-Attention
mechanism, designed specifically for spectra, can capture complex relationships
across different wavelength. Further, we introduced a Mahalanobis
distance-based loss function to address scale imbalance and interaction mode
loss, and incorporated Monte Carlo dropout for quantitative analysis of
prediction uncertainty.Trained and tested on 3,880 red giant spectra from
LAMOST, the SPT achieved remarkable age and mass estimations with average
percentage errors of 17.64% and 6.61%, respectively, and provided uncertainties
for each corresponding prediction. The results significantly outperform those
of traditional machine learning algorithms and demonstrate a high level of
consistency with asteroseismology methods and isochrone fitting techniques. In
the future, our work will leverage datasets from the Chinese Space Station
Telescope and the Large Synoptic Survey Telescope to enhance the precision of
the model and broaden its applicability in the field of astronomy and
astrophysics.