SpecZoo: An AI-Powered Platform for Spectral Analysis and Visualization in Science and Education

Astronomical spectra, which encode rich astrophysical and chemical information, are fundamental to understanding celestial objects and universal laws. The advent of large-scale spectroscopic surveys, generating tens of millions of spectra, presents significant challenges for efficient data processing and analysis. To address these challenges, we develop an AI-powered platform (named “SpecZoo”) for spectral visualization and analysis. This platform integrates modern information technology and machine learning to lower the barrier to spectral data utilization and enhance research efficiency. Its core functionalities include interactive visualization, automated spectral classification, physical parameter measurement, spectral annotation, and multi-band/multi-modal data fusion, all supported by flexible user and data management systems. It has become an essential tool for the National Astronomical Data Center, directly supporting spectral data processing and research for major projects including LAMOST, SDSS, DESI, and so on. Furthermore, the platform demonstrates strong potential for science-education integration, providing a novel resource for cultivating talent in astronomy and data science.

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Publication Details

Journal
Universe
Published
2026-02-27
DOI
https://doi.org/10.3390/universe12030064
Primary Topic
Astronomy and Astrophysical Research
Type
article
Field-Weighted Citation Impact
0.00

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article

SpecZoo: An AI-Powered Platform for Spectral Analysis and Visualization in Science and Education

Xunzhou Chen, Haijun Tian, Guohong Lei, Yang Xu et al.
Universe
Astronomy and Astrophysical Research
article

SpecZoo: An AI-Powered Platform for Spectral Analysis and Visualization in Science and Education

Xunzhou Chen, Haijun Tian, Guohong Lei, Yang Xu, Yuanhao Pu
article en

Abstract

Astronomical spectra, which encode rich astrophysical and chemical information, are fundamental to understanding celestial objects and universal laws. The advent of large-scale spectroscopic surveys, generating tens of millions of spectra, presents significant challenges for efficient data processing and analysis. To address these challenges, we develop an AI-powered platform (named “SpecZoo”) for spectral visualization and analysis. This platform integrates modern information technology and machine learning to lower the barrier to spectral data utilization and enhance research efficiency. Its core functionalities include interactive visualization, automated spectral classification, physical parameter measurement, spectral annotation, and multi-band/multi-modal data fusion, all supported by flexible user and data management systems. It has become an essential tool for the National Astronomical Data Center, directly supporting spectral data processing and research for major projects including LAMOST, SDSS, DESI, and so on. Furthermore, the platform demonstrates strong potential for science-education integration, providing a novel resource for cultivating talent in astronomy and data science.

UniverseVol. 12(3)
China Three Gorges University (CN), Chinese Academy of Sciences (CN), Zhejiang Lab (CN), National Astronomical Observatories (CN), Hangzhou Dianzi University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 46%
Astronomy and Astrophysical Research
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