The fast DM transform, in Julia.

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This package implements the fast DM transform (FDMT), as described in Zackay and Ofek (2014), in pure Julia. I follow the implementation as laid out in pyfdmt, written by Vincent Morello, which implements the FDMT in Python using recursion. This approach is different from the pseudocode provided in the original paper, and the code in MATLAB/Python provided by the original authors, which use nested loops.

Install it by typing and running:

] add FastDedispersion

in the Julia REPL.

Here is an example of the DM transform, obtained via FastDedispersion.jl, from 30 seconds of simulated FRB data. The FRB has a DM of 1000 pc cm $^{-3}$, and an arrival time of 5 seconds, and was dedispersed from 900 to 1100 pc cm $^{-3}$. Note that the plot is zoomed-in, so that we may easily see the expected bow-tie pattern:

Plot: Example dedispersed time series via FastDedispersion.jl

The simulation was carried out using the simulateSearch library. The corresponding data file, in the SIGPROC filterbank format, is included in this package as a part of its testing suite here.