Speeding up numerical Fourier Transform

I wrote this function NFourierTransform, which takes a function $f(k)$ and numerically calculates the fourier transform integral for discrete values of $k \in [k_{\text{min}},k_{\text{max}}]$, finally returning an InterpolatingFunction object.

NFourierTransform[f_Function, {kmin_, kmax_}] :=
Interpolation@
Table[{k, Chop@NIntegrate[f@x E^(-I k x), {x, -Infinity, Infinity}]},
{k, kmin, kmax, (kmax - kmin)/100}]


In my application (calculating the time propagation of wave functions) I need to evaluate NFourierTransform for a function $\psi(k,t)$, where $t$ assumes discrete values in some interval $[t_{\text{min}},t_{\text{max}}]$. So effectively I create a table of NFourierTransform.

TimePropagate[f_Function, kl : {kmin_, kmax_}, {tl__}] :=
Quiet@Table[
NFourierTransform[f[#] Exp[-(#^2/2) t] &, kl], {t, tl}]


Calculating a very simple example with only 2 time values, e.g. TimePropagate[Exp[-Abs@#] &, {-3, 3}, {0, 0.1, 0.1}] takes about 20 seconds to evaluate.

Is there any way to use Compile to speed up the calculations? As far as I know that's only possible for numeric function arguments. What are, in your experience, suitable setings for NIntegrate options such as MaxRecursion or AccuracyGoal, and how do they effect evaluation time?

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I never integrate over t. Each value for t is inserted, and the integration is over some variable x, where k ranges from kmin to kmax. –  einbandi Nov 23 '12 at 14:28
I looked into that. My problem is that I don't really understand the mathematics behind discrete fourier transform (Fourier). I'm much more comfortable with continuous FT. –  einbandi Nov 23 '12 at 14:34
It would be helpful to know what can we assume of your function. If you can be sure about some bandwidth and support then using Fourier is surely a fast way. Meaning, a maximum frequency in which the function has a not too small fourier transform, and a maximum time in which the function is not too small. –  Rojo Nov 23 '12 at 14:43
If that's the case, I remembered a previous question in which my poor answer got the least votes and was barely seen. I don't even remember if it works but you could try it and let me know :P –  Rojo Nov 23 '12 at 14:44
What Rojo said. The responses here seem to cover this topic. My answer got but one vote more than Rojo's. I think that fish might do what you want though (at least once suitably scaled). –  Daniel Lichtblau Nov 26 '12 at 7:20

I had a play with various Compile options and didn't get anywhere (I managed to make it slower though!). However, you can get a nice little speed boost using ParallelTable. Your original on my machine:

NFourierTransform[f_Function, {kmin_, kmax_}] :=
Interpolation@
Table[{k,
Chop@NIntegrate[f@x E^(-I k x), {x, -Infinity, Infinity}]}, {k,
kmin, kmax, (kmax - kmin)/100}]
TimePropagate[f_Function, kl : {kmin_, kmax_}, {tl__}] :=
Quiet@Table[NFourierTransform[f[#] Exp[-(#^2/2) t] &, kl], {t, tl}]


TimePropagate[Exp[-Abs@#] &, {-3, 3}, {0, 0.1, 0.1}] // AbsoluteTiming runs in 5.65 seconds. I launch some kernels

LaunchKernels[]


and throw in a ParallelTable

NFourierTransform[f_Function, {kmin_, kmax_}] :=
Interpolation@
ParallelTable[{k,
Chop@NIntegrate[f@x E^(-I k x), {x, -Infinity, Infinity}]}, {k,
kmin, kmax, (kmax - kmin)/100}]
TimePropagate[f_Function, kl : {kmin_, kmax_}, {tl__}] :=
Quiet@Table[NFourierTransform[f[#] Exp[-(#^2/2) t] &, kl], {t, tl}]


to get an execution time of 2.04 seconds for the same function call: TimePropagate[Exp[-Abs@#] &, {-3, 3}, {0, 0.1, 0.1}] // AbsoluteTiming

A speed-up of almost 3 times.

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Hi Mike, welcome to Mathematica at Stack Exchange! I've been reading your blog with great interest for a while now. It's great that you joined, and I hope you will like the community here. Gives me a pleasure to give you the first upvote on this site,+1. –  Leonid Shifrin Nov 26 '12 at 12:51
Thanks. I have been keeping an eye on this site for a while (I promoted the original proposal - walkingrandomly.com/?p=4014 - hope it helped) and have learned many useful tricks here. I rarely answer anything because the site regulars here are too efficient for their own good :) –  WalkingRandomly Nov 26 '12 at 13:43
Finally a useful tip that uses my original functions! Thanks a lot! –  einbandi Nov 26 '12 at 14:30
Welcome to the site, Mike. I've edited your post to format it a little better. A tip: while backticks are useful for inline code, you can typeset blocks of code by indenting it by 4 spaces (or selecting it and pressing the {} button in the edit window). This way, it's also pretty printed with a custom Mathematica syntax highlighter (developed here!) –  The Toad Nov 26 '12 at 15:25
Ok, thanks for that. I did a very quick scan around the site to see how to do code formatting but didn't find anything. Probably my bad as it was a VERY quck scan :) –  WalkingRandomly Nov 26 '12 at 16:03