ArXiv TLDR

A General Framework for Radial Velocity Calibration in Low-Resolution Spectroscopic Surveys: Correcting Wavelength-Dependent and Global Systematics with Application to LAMOST DR9

🐦 Tweet
2604.19119

Jinming Zhang, Haibo Yuan, Zhijia Tian

astro-ph.SRastro-ph.GAastro-ph.IM

TLDR

A new framework corrects wavelength-dependent and global radial velocity systematics in low-resolution spectroscopic surveys, significantly improving precision.

Key contributions

  • Developed a general framework to correct wavelength-dependent and global RV systematics in low-resolution spectra.
  • Corrected wavelength-dependent shifts using segment-wise polynomial fitting at spectrograph and fiber levels.
  • Applied hierarchical zero-point correction using repeat observations and external catalogs (APOGEE, Gaia).
  • Improved LAMOST RV precision by a factor of two (from ~3.6 to ~1.8 km/s) and released a 5.7M star catalog.

Why it matters

Radial velocities are vital for understanding stellar motion and galaxy evolution. This work provides a robust method to correct systematics in large spectroscopic surveys like LAMOST, significantly enhancing data quality. The framework is generalizable, offering a blueprint for future RV calibration efforts.

Original Abstract

Radial velocity (RV) is crucial for stellar kinematics and Galactic archaeology. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) has obtained over ten million low-resolution spectra ($R \sim 1800$), yielding RVs for millions of stars, but these suffer from (1) wavelength-dependent inconsistencies (relative shifts between spectral segments) and (2) global zero-point offsets (uniform shifts of entire spectra). In this work, we comprehensively characterize and correct both. Each spectrum is first divided into eight segments of about 500 Angstrom. We organize the data at the spectrograph and fiber levels, measure segment-wise RV offsets relative to the full spectrum at each level, and then fit these offsets with low-order polynomials to correct wavelength-dependent systematics. We then correct zero-points hierarchically: at the spectrograph level by minimizing a joint chi-squared constrained by repeat observations and cross-matches with APOGEE and Gaia RVS, and at the fiber level by averaging seasonal offsets. After correction, RV precision improves significantly: for cross-night repeats, the standard deviation of RV differences at high signal-to-noise ratios drops by a factor of two from about 3.6 to about 1.8 km s$^{-1}$, implying a single-measurement precision of about 1.3 km s$^{-1}$. External checks with APOGEE and Gaia show dispersions drop from about 4.0 to about 2.0 km s$^{-1}$. The precision approaches, though slightly below, the theoretical limit at $R \sim 1800$. We release a value-added RV catalog with corrected velocities for about 5.7 million spectra, providing a homogeneous and systematically corrected dataset. The framework established in this work is also applicable to RV calibration in other large-scale spectroscopic surveys.

📬 Weekly AI Paper Digest

Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.