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Stellar Parameterisation using KPCA and SVM

Published online by Cambridge University Press:  29 August 2019

H. Yuan ,
Y. Zhang ,
Y. Lei ,
Y. Dong ,
Z. Bai ,
G. Li ,
W. Zhang ,
H. Zhang  and
Y. Zhao
H. Yuan
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
Y. Zhang
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
Y. Lei
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
Y. Dong
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
Z. Bai
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
G. Li
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
W. Zhang
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
H. Zhang
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
Y. Zhao
Affiliation:
Key Laboratory of Optical Astronomy, NAO, CAS, Beijing, China email: [email protected]
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Abstract

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With so many spectroscopic surveys, both past and upcoming, such as SDSS and LAMOST, the number of accessible stellar spectra is continuously increasing. There is therefore a great need for automated procedures that will derive estimates of stellar parameters. Working with spectra from SDSS and LAMOST, we put forward a hybrid approach of Kernel Principal Component Analysis (KPCA) and Support Vector Machine (SVM) to determine the stellar atmospheric parameters effective temperature, surface gravity and metallicity. For stars with both APOGEE and LAMOST spectra, we adopt the LAMOST spectra and APOGEE parameters, and then use KPCA to reduce dimensionality and SVM to measure parameters. Our method provides reliable and precise results; for example, the standard deviation of effective temperature, surface gravity and metallicity for the test sample come to approximately 47–75 K, 0.11–0.15 dex and 0.06–0.075 dex, respectively. The impact of the signal:noise ratio of the observations upon the accuracy of the results is also investigated.

Keywords

Techniques: spectroscopicmethods: data analysisstars: atmospheres
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 14 , Symposium S339: Southern Horizons in Time-Domain Astronomy , November 2017 , pp. 345 - 348
Copyright
© International Astronomical Union 2019 

References

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