Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/171315
Title: | Automated classification of stellar spectra |
Author: | Jiménez Palau, Cristina |
Director/Tutor: | Solanes, José M. (José María) |
Keywords: | Espectres estel·lars Classificació dels estels Treballs de fi de grau Stars spectra Stars Classification Bachelor's theses |
Issue Date: | Jun-2020 |
Abstract: | We have analyzed the performance of a PCA-based automated classifier of stellar spectra into the MK system, using as benchmark the dataset of optical spectra listed in the SDSS-DR15. We have found that it is possible to account for 99% of the total variance arising from good-quality A, F, G, K, and M stellar spectra with only three principal components, though we have ended up using four to further increase the discriminant power of our methodology. The projections of a subset of 50; 000 good-quality spectra on this 4D space have been used to determine the most probable spectral type of test stars in samples of spectra of increasing quality, with which we have evaluated the goodness of our classification procedure. Within a general scenario of excellent results, we found that a Gaussian Kernel performs somewhat better than a Top-Hat Kernel when calculating membership probabilities, that the efficiency of our classification method improves with the S=N of the spectra, and that the classification of G-type stars is the less reliable and that of F-type stars the most incomplete. |
Note: | Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2020, Tutor: Josep Maria Solanes Majúa |
URI: | http://hdl.handle.net/2445/171315 |
Appears in Collections: | Treballs Finals de Grau (TFG) - Física |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
JIMÉNEZ PALAU CRISTINA_1338725_assignsubmission_file_TFG-Jiménez-Palau-Cristina.pdf | 955.05 kB | Adobe PDF | View/Open |
This item is licensed under a
Creative Commons License