The Application of Bayesian Spectral Analysis in Photometric Time Series

S. Latif 1, H. Safari 2, I. Safaei 3 1 Abdolrahman Sufi Razi Higher Education Institute, Zanjan
2 Faculty of Science, Department of Physics, University of Zanjan
3 Faculty of Physics, University of Kashan


The present paper introduces the Bayesian spectral analysis as a powerful and efficient method for spectral analysis of photometric time series. For this purpose, Bayesian spectral analysis has programmed in Matlab software for XZ Dra photometric time series which is non-uniform with large gaps and the power spectrum of this analysis has compared with the power spectrum which obtained from the Period04 software, which designed for statistical analysis of astronomical time series and used of artificial data for unify the time series. Although in the power spectrum of this software, the main spectral peak which represent the main frequency of XZ Dra variable star oscillations in the f = 2.09864 (day -1) is well known but false spectral peaks are also seen. Also, in this software it’s not clear how to generate the synthetic data. These false peaks have been removed in the power spectrum which obtained from theBayesian analysis; also this spectral peak which is around the desired frequency has a shorter width and is more accurate. It should be noted that in Bayesian spectral analysis, it’s not require to unify the time series for obtaining a desired power spectrum. Moreover, the researcher also becomes aware of the exact calculation process.

Keywords: Bayesian Spectral Analysis, Bayes’ Theorem, Period04 Software, Power Spectrum, Variable Star,
Light Curve.
PACS Numbers: 80, 90, 95, 97.


Publication in the “Iranian Journal of Physics Research”, November, 2017, Isfahan, Iran, Series . IJPR. 2017; 17 (4) :541-551.