Spectral similarities in galaxies through an unsupervised classification of spaxels

HIGHLIGHTS

• What: The work shows that the unsupervised classification of spaxels takes full advantage of the richness of the information in the data cubes by presenting the spectral and spatial information in combined and synthetic way. The authors propose a more physical approach by grouping spaxels based on spectral similarity using unsupervised classification under objective statistical criteria. The authors demonstrate the capabilities of an unsupervised classification of spaxels on two galaxies that were observed with the multi-unit spectroscopic explorer installed at the very large telescope (MUSE/VLT) and one galaxy that was observed with the near infrared . . .
  

   

  

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