Cross Correlation Function slow method (Application).
Application ccs calculates the cross correlation function of a time series by using a slow algorithm. It requires two input series. It is run in the Question/Answer user interface by typing:
[n]Xronos> ccsin the Partial Question/Answer user interface by typing:
[n]Xronos> ccs [series1] [series2]and in the Command-Driven user interface by typing:
[n]Xronos> ccs[/qualifier1/qual2/... etc] [series1] [series2]
The newbin time must correspond to an integer multiple of the maximum bin time. The default newbin time is either the maximum bin time (if fewer than 512 newbins are expected) or the integer multiple of it which gives a single interval with 512 newbins at most. The average count rate in each interval is subtracted from all newbins, and gaps and rejected newbins are replaced with zeroes, before the cross correlation function is calculated.
Time delays refer to the 1st series: therefore a cross correlation function peaking for positive time delays indicates that variations in the 2nd series lag those in the 1st series.
The cross correlation error bars are obtained either by propagating the theoretical error bars of the cross correlations from individual intervals (in turn obtained by propagating the newbin errors bars through the cross correlation formula) or by evaluating directly the standard deviation of the average of the cross correlation in each delay bin from different intervals. This depends on whether the specified number of intervals per frame is, respectively, smaller or larger than the value of global parameter number 9 (default =5). Error bars are plotted by default.
The effects introduced by windows, data gaps etc. can be studied by analysing the exposure profile of the time series, by setting global parameter number 10 to 1. By setting global parameter number 12 to 1, a strict simultaneousness between the two series can be imposed: any rejected newbin or gap found in one series will cause the corresponding newbin of the other series to be rejected. This is useful to check whether artificial time delay between the two series are introduced by a non-strict simultaneousness of the two series.
The analysis normalisation flag, specified by global parameter number 11, has the same meaning as in application ccf.