Skip to main content

numerical integration - Solution of a singular integral equation using interpolation and truncated methods


I am trying to code the following integral equation to find the solution numerically using Mathematica.


First we define the following functions:



phi[x_]:=Piecewise[{{1, 0 < x < 1}}, 0]

psi1[x_] := (phi[2 x-1] - phi[2 x]);

psijk[x_, j_, k_] := (Sqrt[2])^j psi1[-2^j x - k]

f[x_] := 1/1155 (112 (-1 + x)^(3/4) + x (144 (-1 + x)^(3/4) + x (1155 + 256 (-1 + x)^(3/4) - 1280 x^(3/4) - (1155 + 512 (-1 + x)^(3/4)) x + 1024 x^(7/4))));

exactsoln[x_] := x^2 (1 - x);


I am trying to solve the following integral equation for u (x) (numerically). where


u[x] + Integrate[(x - t)^(-1/4)*u[t], {t, 0, x}] - 
Integrate[(x - t)^(-3/4)*u[t], {t, 0, 1}] = f[x];

where f[x] is defined as above. Here is the numerical scheme. The approximated solution \approx[x] which can be written as


approxsoln[x_, n_] := 
Sum[c[j, k]*psijk[x, j, k], {j, 0, n}, {k, -2^n, 2^n - 1}]

Then, we will end up by


Sum[c[j, k]*(psijk[x, j, k] - 

Integrate[(x - t)^(-1/4)* psijk[t, j, k], {t, 0, x}] -
Integrate[(x - t)^(-1/4)* psijk[t, j, k], {t, 0, 1}]), {j, 0, n}, {k, -2^n, 2^n - 1}];

I think it is worth to try for n=10 first.



Answer



The numerical method I suggested here also works for this case.It uses expression describing the integral Integrate[(x - t)^(-1/4),t]


f[x_] := 1/
1155 (112 (-1 + x)^(3/4) +
x (144 (-1 + x)^(3/4) +
x (1155 + 256 (-1 + x)^(3/4) -

1280 x^(3/4) - (1155 + 512 (-1 + x)^(3/4)) x +
1024 x^(7/4))));
ker[t_, x_] := -(4/3) (-t + x)^(3/4)

np = 101; points = fun = Table[Null, {np}];
Table[points[[i]] = i/np, {i, np}];
sol = Unique[] & /@ points;
Do[fun[[i]] = f[t] /. t -> points[[i]], {i, np}]; sol1 =
sol /. First@
Solve[Table[

sol[[j]] -
Sum[.5*(sol[[i]] +
sol[[i + 1]])*(ker[points[[i + 1]], points[[j]]] -
ker[points[[i]], points[[j]]]), {i, 1, np - 1}] -
Sum[.5*(sol[[i]] +
sol[[i + 1]])*(ker[points[[i + 1]], points[[j]]] -
ker[points[[i]], points[[j]]])*If[i >= j, 0, 1], {i, 1,
np - 1}] == fun[[j]], {j, 1, np}], sol];
u = Transpose[{points, Re[sol1]}];
Show[Plot[x^2*(1 - x), {x, 0, 1}, AxesLabel -> {"x", "u"},

PlotStyle -> Blue], ListPlot[u, PlotStyle -> Orange]]

fig1


If we use the algorithm that @Mutaz offers, then a solution for n = 2 (for n = 5, a supercomputer is needed) looks like that


phi[x_] := Piecewise[{{1, 0 <= x < 1}}, 0]
psi1[x_] := (phi[2 x] - phi[2 x - 1]);
psijk[x_, j_, k_] :=
Piecewise[{{(Sqrt[2])^j psi1[2^j x - k],
0 <= j}, {2^j psi1[2^j (x - k)], j < 0}}]
f[x_] := 1/

1155 (112 (-1 + x)^(3/4) +
x (144 (-1 + x)^(3/4) +
x (1155 + 256 (-1 + x)^(3/4) -
1280 x^(3/4) - (1155 + 512 (-1 + x)^(3/4)) x +
1024 x^(7/4))));
exactsoln[x_] := x^2 (1 - x);
(*u[x]-Integrate[(x-t)^(-1/4)*u[t],{t,0,x}]-Integrate[(x-t)^(-1/4)*u[\
t],{t,0,1}]=f[x];*)
sol[x_, n_] :=


Sum[c[j, k]*psijk[x, j, k], {j, -n, n}, {k, -2^n, 2^n - 1}]
n = 2; var =
Flatten[Table[c[j, k], {j, -n, n, 1}, {k, -2^n, 2^n - 1, 1}]];np =
Length[var]; points =
Table[Null, {np}];
Table[points[[i]] = i/np, {i, np}];
eq = ParallelTable[
sol[points[[i]], n] -
Integrate[(points[[i]] - t)^(-1/4)*sol[t, n], {t, 0,
points[[i]]}] -

Integrate[(points[[i]] - t)^(-1/4)*sol[t, n], {t, 0, 1}] ==
f[points[[i]]], {i, 1, np}];
{b, m} = N[CoefficientArrays[eq, var]];
sol1 = LinearSolve[m, -b];
u = Sum[c[j, k]*psijk[x, j, k], {j, -n, n}, {k, -2^n, 2^n - 1}] /.
Table[var[[i]] -> sol1[[i]], {i, Length[var]}];
Show[Plot[x^2*(1 - x), {x, 0, 1}, AxesLabel -> {"x", "u"},
PlotStyle -> Blue, PlotLabel -> Row[{"n = ", n}]],
Plot[Re[u], {x, 0, 1}, PlotStyle -> Orange]]


fig2


I will show another method that is in the middle position between what Roman suggested and what the author wants. This method is very accurate.Figure 3 on the right shows the difference between the exact solution and the numerical one with 'n = 3'. This difference is of the order of 1016.


psijk[x_, j_] := x^j
f[x_] := 1/
1155 (112 (-1 + x)^(3/4) +
x (144 (-1 + x)^(3/4) +
x (1155 + 256 (-1 + x)^(3/4) -
1280 x^(3/4) - (1155 + 512 (-1 + x)^(3/4)) x +
1024 x^(7/4))));
exactsoln[x_] := x^2 (1 - x);

(*u[x]-Integrate[(x-t)^(-1/4)*u[t],{t,0,x}]-Integrate[(x-t)^(-1/4)*u[\
t],{t,0,1}]=f[x];*)

sol[x_, n_] := Sum[c[j]*psijk[x, j], {j, 0, n}]

n = 3; var = Flatten[Table[c[j], {j, 0, n, 1}]]; np =
Length[var]; points = Table[Null, {np}];
Table[points[[i]] = i/np, {i, np}];
eq = ParallelTable[
sol[points[[i]], n] -

Integrate[(points[[i]] - t)^(-1/4)*sol[t, n], {t, 0,
points[[i]]}] -
Integrate[(points[[i]] - t)^(-1/4)*sol[t, n], {t, 0, 1}] ==
f[points[[i]]], {i, 1, np}]; // AbsoluteTiming

{b, m} = N[CoefficientArrays[eq, var]];
sol1 = LinearSolve[m, -b];


u = Sum[c[j]*psijk[x, j], {j, 0, n}] /.

Table[var[[i]] -> sol1[[i]], {i, Length[var]}];
Show[Plot[x^2*(1 - x), {x, 0, 1}, AxesLabel -> {"x", "u"},
PlotStyle -> Blue, PlotLabel -> Row[{"n = ", n}]],
Plot[Re[u], {x, 0, 1}, PlotStyle -> Orange]]
Plot[x^2*(1 - x) - Re[u], {x, 0, 1}, AxesLabel -> {"x", "\[Delta]u"},
PlotStyle -> Blue, PlotLabel -> Row[{"n = ", n}]]

fig3


Comments

Popular posts from this blog

functions - Get leading series expansion term?

Given a function f[x] , I would like to have a function leadingSeries that returns just the leading term in the series around x=0 . For example: leadingSeries[(1/x + 2)/(4 + 1/x^2 + x)] x and leadingSeries[(1/x + 2 + (1 - 1/x^3)/4)/(4 + x)] -(1/(16 x^3)) Is there such a function in Mathematica? Or maybe one can implement it efficiently? EDIT I finally went with the following implementation, based on Carl Woll 's answer: lds[ex_,x_]:=( (ex/.x->(x+O[x]^2))/.SeriesData[U_,Z_,L_List,Mi_,Ma_,De_]:>SeriesData[U,Z,{L[[1]]},Mi,Mi+1,De]//Quiet//Normal) The advantage is, that this one also properly works with functions whose leading term is a constant: lds[Exp[x],x] 1 Answer Update 1 Updated to eliminate SeriesData and to not return additional terms Perhaps you could use: leadingSeries[expr_, x_] := Normal[expr /. x->(x+O[x]^2) /. a_List :> Take[a, 1]] Then for your examples: leadingSeries[(1/x + 2)/(4 + 1/x^2 + x), x] leadingSeries[Exp[x], x] leadingSeries[(1/x + 2 + (1 - 1/x...

mathematical optimization - Minimizing using indices, error: Part::pkspec1: The expression cannot be used as a part specification

I want to use Minimize where the variables to minimize are indices pointing into an array. Here a MWE that hopefully shows what my problem is. vars = u@# & /@ Range[3]; cons = Flatten@ { Table[(u[j] != #) & /@ vars[[j + 1 ;; -1]], {j, 1, 3 - 1}], 1 vec1 = {1, 2, 3}; vec2 = {1, 2, 3}; Minimize[{Total@((vec1[[#]] - vec2[[u[#]]])^2 & /@ Range[1, 3]), cons}, vars, Integers] The error I get: Part::pkspec1: The expression u[1] cannot be used as a part specification. >> Answer Ok, it seems that one can get around Mathematica trying to evaluate vec2[[u[1]]] too early by using the function Indexed[vec2,u[1]] . The working MWE would then look like the following: vars = u@# & /@ Range[3]; cons = Flatten@{ Table[(u[j] != #) & /@ vars[[j + 1 ;; -1]], {j, 1, 3 - 1}], 1 vec1 = {1, 2, 3}; vec2 = {1, 2, 3}; NMinimize[ {Total@((vec1[[#]] - Indexed[vec2, u[#]])^2 & /@ R...

plotting - Plot 4D data with color as 4th dimension

I have a list of 4D data (x position, y position, amplitude, wavelength). I want to plot x, y, and amplitude on a 3D plot and have the color of the points correspond to the wavelength. I have seen many examples using functions to define color but my wavelength cannot be expressed by an analytic function. Is there a simple way to do this? Answer Here a another possible way to visualize 4D data: data = Flatten[Table[{x, y, x^2 + y^2, Sin[x - y]}, {x, -Pi, Pi,Pi/10}, {y,-Pi,Pi, Pi/10}], 1]; You can use the function Point along with VertexColors . Now the points are places using the first three elements and the color is determined by the fourth. In this case I used Hue, but you can use whatever you prefer. Graphics3D[ Point[data[[All, 1 ;; 3]], VertexColors -> Hue /@ data[[All, 4]]], Axes -> True, BoxRatios -> {1, 1, 1/GoldenRatio}]