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====== TransientX - Lessons learned ====== [[https://github.com/ypmen/TransientX | TransientX github]] ====== The general concept of TransientX ====== TransientX is a powerful tool to search for single pulses. It analyses the data in several steps during the search that also includes RFI mitigation and clustering of candidates. The following marks my knowledge as of 2024-07-01. The steps of ''transientx_fil'' are as follows - Skewness/kurtosis filtering - Downsampling - Normalization - Baseline removal - RFI mitigation (''-z'' options) - De-dispersion - Matched filtering (search for single pulse candidates) - Clustering of candidates - Plotting ===== Skewness/kurtosis filtering ===== This filtering method is always on and controlled by the ''-zapthre'' option. There is no flag to turn it off directly. However, a high threshold basically disables it. ===== Downsampling ===== Next, the filterbank is downsampled in time and frequency according to the values given by ''--td'' and ''--fd''. Be aware that this is down in addition to values given in the ''ddplan'' Hence, the file might be downsampled multiple times! ===== Normalization ===== ===== Baseline removal ===== This step is similar to the ''zdot'' option and removes the zero DM RFI of each frequency channel, where the contribution is weighted individually for each channel. However, it is smoothing the curve that is to be subtracted from the corresponding frequency channel by a factor. This is controlled by the ''--baseline'' option. It takes two options, the first one should be left at 0, the second gives the smoothing (in s). It is be used when the astrophysical signal is expected to have a significant dispersion delay. Otherwise, this might remove real signals as well. ===== RFI mitigation ===== TransientX has several options to mitigate RFI: * ''zdot'' This is a advanced zeroDM filter which removes a weighted zeroDM from each frequency channel. It is be used when the astrophysical signal is expected to have a significant dispersion delay. Otherwise, this might remove real signals as well. **This is effectively removing wideband RFI.** * ''KadaneF tdRFI fdRFI'' filters chunks of the data in frequency (downsampled with fdRFI (frequency) and tdRFI (time)). If they exceed the threshold (given by''--threKadaneF'') they are removed. **This is useful against "wide" (not a few time bins) signals, that cover only a small number of frequency channels.** * ''mask'' Can filter out **strong and short outliers, i.e. a few time bins/frequency channels.** The threshold is given by ''--threMask''. * ''KadaneT tdRFI fdRFI'' as ''KadaneF'' but in time. **Probably not so useful given ''zdot''.** * ''zero'' classical zero DM filtering. * ''zap fl fh'' Removes frequency channels in the given frequency range given from ''fl'' to ''fh''. Must be specified in MHz. ===== De-dispersion ===== The data is de-dispersed using subband de-dispersion. The size of the subbands is controlled by the loss of S/N controlled by ''--snrloss''. The trails are controlled by ''dms'' (Start DM), ''ndm''0 (Number of DMs) and ''ddm'' (DM step size). ===== Matched filtering ===== The De-dispersed time series is searched for single pulse candidates using matched filtering. The searched widths (''--minw'', ''--maxw'') and S/N threshold (''thre'') can be specified. ===== Clustering of candidates ===== To avoid seeing the same candidates at several DMs, transientX clusters them based on the DBSCAN algorithm. This algorithm searches for other candidates in a radius around a candidate in DM (difference in dispersive delay) and time. If the specified number of candidates is found, they are collected as a core point, i.e. summarized into the one with the highest S/N. The radius is controlled with ''-r'' and should be large enough so that the delay from DM step size fits comfortable in the radius. ===== Plotting ===== Finally the plots of the candidates are created. ====== replot_fil ====== Next to ''transientx_fil'', ''replot_fil'' is the second important tool when searching single pulses. The purpose of replot_fil is to do a finer search for the TOA, DM and the width of the pulse candidates. If a candidate is RFI, the change is large and then the candidate is dropped.