Spectral classification and composites of galaxies in LAMOST DR4
Li-Li Wang, A-Li Luo, Shi-Yin Shen, Wen Hou, Xiao Kong, Yi-Han Song,, Jian-Nan Zhang, Wu Hong, Zi-Huang Cao, Yong-Hui Hou, Yue-Fei Wang, Yong, Zhang, and Yong-Heng Zhao

TL;DR
This paper classifies 40,182 galaxy spectra from LAMOST DR4 into six categories, analyzes their composite spectra, and explores correlations with morphological parameters, providing a valuable galaxy catalog and spectral features for future research.
Contribution
The study introduces a new classification of LAMOST DR4 galaxy spectra into six types and provides composite spectra and morphological correlations, enhancing galaxy spectral analysis tools.
Findings
Six spectral classes identified and classified.
Composite spectra reveal key features differentiating classes.
Correlation between spectral types and morphological parameters established.
Abstract
We study the classification and composite spectra of galaxy in the fourth data release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). We select 40,182 spectra of galaxies from LAMOST DR4, which have photometric in- formation but no spectroscopic observations in the Sloan Digital Sky Survey(SDSS). These newly observed spectra are re-calibrated and classified into six classes, i.e. pas- sive, H{\alpha}-weak, star-forming, composite, LINER and Seyfert using the line intensity (H\b{eta}, [OIII]{\lambda}5007, H{\alpha} and [NII]{\lambda}6585). We also study the correlation between spectral classes and morphological types through three parameters: concentration index, (u - r) color, and D4000n index. We calculate composite spectra of high signal-to-noise ra- tio(S/N) for six spectral classes, and using these composites we pick out some features that can…
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.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
