2024/08/12 by Yisheng Qiu, Qiu, Yisheng, Tianwei Zhang +11 · 1 citation
Chemistry · Physics and Astronomy · #Astrophysics of Galaxies (astro-ph.GA) #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Scientific Research and Discoveries #Solar and Stellar Astrophysics (astro-ph.SR) #Spectroscopy and Laser Applications
paper · pdf · doi:10.48550/arxiv.2408.06004
openalex publication_date 2024/08/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Interstellar molecules, which play an important role in astrochemistry, are identified using observed spectral lines. Despite the advent of spectral analysis tools in the past decade, the identification of spectral lines remains a tedious task that requires extensive manual intervention, preventing us from fully exploiting the vast amounts of data generated by large facilities such as ALMA. This study aims to address the aforementioned issue by developing a framework of automated line identification. We introduce a robust spectral fitting technique applicable for spectral line identification with minimal human supervision. Our method is assessed using published data from five line surveys of hot cores, including W51, Orion-KL, Sgr B2(M), and Sgr B2(N). By comparing the identified lines, our algorithm achieves an overall recall of ~ 74% - 93%, and an average precision of ~ 78% - 92%. Our code, named Spectuner, is publicly available on GitHub.