Context
I am interested in identifying damped modes such as those in self gravitating galaxies:
This requires extending to the lower complex plane a dispersion relation which is computed numerically and known over a grid in the upper complex plane.
The (interpolated) complex data in the upper plane looks like this:
Question
How to I extend this function below the real axis?
I.e. how can I sample the analytic continuation of my data set in the lower complex plane?
Toy model
For the sake of constructing a toy model, let me assume that I know numerically the (shifted) Zeta function above the plane as
ComplexPlot[Zeta[z + I], {z, 0, 4 + 2 I},
ColorFunction -> "CyclicReImLogAbs"]
My goal to be able to make a plot like this
ComplexPlot[Zeta[z + I], {z, -2 I, 4 + 2 I},
ColorFunction -> "CyclicReImLogAbs"]
I am told this is possible to some extend (?)
I am aware it is not an easy question in general and that the analytic continuation is only valid on some limited interval which depends on the accuracy of my sampling in the upper plane.
I hope having a genetic tool to do this would be useful to others?
Pade Approximation seems an obvious venue, but I did not understand how to feed it with data rather than functions?
I believe an implementation in fortran is discussed in this paper (Appendix D).
Thank you for your help!