Agatha

Disentangling periodic signals from correlated noise in a periodogram framework

The number of proxies is counted from the fourth column of the data.

If more than one data sets are selected, only the MLP can be calculated for the combined data. To calculate the periodogram, the data sets are combined after subtracting the best-fit noise components..
There could be errors in the calculation of the BFP if the data is small (e.g. less than 20 data points) or not well sampled.
If the BFP is selected, only 'RV' is available for the following observable selection.
The users are encouraged to make their own periodogram figures, particularly the BFP, by downloading and using the relevant data.

If more than one data sets are selected, only the MLP-based 2D periodogram can be calculated for the combined data. To calculate the periodogram, the data sets are combined after subtracting the best-fitted noise components.


The above parameters are called 'calculating parameters', which are used for calculate the moving periodogram. The following parameters are called 'visualization parameters', and are set to optimize the visulization of signals.
If you change the calculating parameters, click both 'calculate' and 'plot' to show the 2D periodogram. If you only change the visualization parameters, only click 'plot' to show the periodogram.
The users are encouraged to make their own plot of moving periodogram by downloading and using the relevant data. The first row is the centers of time windows. The first column is the periods, and the rest data is the matrix of periodogram powers.