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February 28, 2026Universe0 citationsOpen Access

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

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YPYuanhao PuGLGuohong LeiYXYang Xu

Key Points

  • The aim is to create a user-friendly platform for analyzing and visualizing astronomical spectra using AI techniques.
  • Developed an AI-powered platform named SpecZoo for spectral visualization and analysis.
  • Integrated machine learning for automated classification and measurement of physical parameters.
  • Enabled multi-band and multi-modal data fusion capabilities to support diverse data types.
  • Established flexible user and data management systems for easier access and processing.
  • SpecZoo became essential for National Astronomical Data Center, aiding major projects like LAMOST and SDSS.
  • Enhanced efficiency in spectral data utilization was observed due to automated features and interactive tools.
  • Demonstrated potential for science education by providing resources that cultivate skills in astronomy and data science.

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.

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Cite This Study

Pu et al. (2026) studied this question.

synapsesocial.com/papers/69a288170a974eb0d3c041a5https://doi.org/10.3390/universe12030064
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