Stellar classification as a research area encompasses the quantitative and qualitative schemes used to categorize stars based on their spectra, effective temperatures, luminosities, chemical abundances, and other observable parameters, and to refine those schemes through observational and theoretical studies. It integrates spectroscopy, radiative transfer modeling, stellar atmosphere theory, and statistical analysis of large photometric and spectroscopic surveys to improve classification criteria and boundaries. Research focuses on extending the MK system, developing automated and machine-learning-based classifiers, calibrating spectral types to physical parameters, and exploring how classification encodes information about stellar evolution, populations, and Galactic structure.
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