Skip to main content

differential equations - Extending NDSolve beyond a singularity


The $\tan$ function satisfies the following IVP:


$$y'=1+y^2 ,\quad y(0)=0 $$


and has simple poles at the points $x=\pi/2+ \pi n$ for integer $n$.


When trying to get $\tan$ via numerical integration, the command


NDSolve[{y'[x]==y[x]^2+1,y[0]==0},y[x],{x,-10,10}]

gives a solution which is defined only for $x \in(- \pi/2,\pi/2)$. Is there a way to extend the solution beyond the poles $x= \pm \pi/2$? What about singularities in the general case?


Thank you!




Answer



We can treat the variable $y$ as an element $[y_1 \colon y_2]$ of the projective line. In code, this means replacing y[x] by y1[x]/y2[x]. For an IVP $y' = f(x, y), \ y(x_0) = y_0$, we translate the initial condition as $y_1(x_0) = y_0, \ y_2(x_0) = 1$. Since the substitution yields an equation in two variables $y_1$, $y_2$, $$y_1'y_2-y_1y_2'=y_2^2\;f(x,\,y_1/y_2)\,,$$ we need another equation. So to get a unique solution, we impose the condition in code as


y1[x]^2 + y2[x]^2 == y0^2 + 1

Since this condition is satisfied initially, NDSolve will use it in conjunction with the ODE to determine y1[x] and y2[x] at each step. We can use this condition as it is and solve the system as a differential-algebraic equation (DAE); or we can differentiate it and solve the system as an ODE. The important difference is that the methods and precision available for DAEs are limited.


eqn = y'[x] == 1 + y[x]^2;
blowup = {y -> (y1[#]/y2[#] &)};

newfn = eqn /. blowup /. Equal -> Subtract // Together // Numerator;


newDAE = {newfn == 0, y1[x]^2 + y2[x]^2 == y0^2 + 1};
newODE = {newfn == 0, D[y1[x]^2 + y2[x]^2 == y0^2 + 1, x]};

Block[{x0 = 0, y0 = 0},
sol = NDSolve[{newDAE, y1[x0] == y0, y2[x0] == 1}, {y1, y2}, {x, 0, 10}]
];

Block[{x0 = 0, y0 = 0},
sol = NDSolve[{newODE, y1[x0] == y0, y2[x0] == 1}, {y1, y2}, {x, 0, 10}]
];


Both solutions yield the same plots:


Plot[y[x] /. blowup /. First@sol // Evaluate, {x, 0, 10}]

Mathematica graphics


Compare by overlaying the graph of tangent, the exact solution in this example:


Plot[{y[x] /. blowup /. First@sol, Tan[x]} // Evaluate, {x, 0, 10}]

Mathematica graphics


Update: Another view of what is happening.



A standard model of the projective line $[y_1\colon y_2]$ is a unit-diameter circle tangent to an axis. The corresponding affine line $y$ is given by $y_2 = 1$. Here we project the solution in terms of {y1[x], y2[x]} onto the desired solution y[x] (for x running from 0 to 10).



enter image description here
The projection from the circle model of the projective line onto the affine line y2 == 1. (The cylinder is the product of the interval 0 <= x <= 10 and the projective line or circle.)


cplot2 = ContourPlot3D[y1^2 + y2^2 == y2,
{x, 0, 10}, {y1, -1.05, 1.05}, {y2, -0.05, 1.05},
ContourStyle -> Opacity[0.3], Mesh -> None];
base = Show[
ParametricPlot3D[
Evaluate[{x, ( y1[x] y2[x])/(y1[x]^2 + y2[x]^2), y2[x]^2/(

y1[x]^2 + y2[x]^2)} /. First@sol], {x, 0, 10}],
ParametricPlot3D[
Evaluate[{x, y[x] /. blowup, 1} /. First@sol], {x, 0, 10},
PlotStyle -> ColorData[97, 3], Exclusions -> Cos[x] == 0],
(*cplot1,*)cplot2,
PlotRange -> {{0, 10}, {-2, 2}, {-0.1, 3.05}},
AxesLabel -> {x, y1, y2}];
(* * * * *)
Manipulate[
Show[

base,
Graphics3D[{
Gray,
Table[InfiniteLine[{{0, y, 1}, {10, y, 1}}], {y, -2, 2}],
Table[
InfiniteLine[{{x0, -1, 1}, {x0, 1, 1}}], {x0, 0, 10, Pi/2}],
Red, Thickness[Medium],
Line[{{0, 0, 0}, {10, 0, 0}}],
InfiniteLine[{{x, 0, 0}, {x, y[x] /. blowup /. First@sol, 1}}],
PointSize[Large],

Point[{{x, 0, 0}, {x, y[x], 1}, {x, ( y1[x] y2[x])/(
y1[x]^2 + y2[x]^2), y2[x]^2/(y1[x]^2 + y2[x]^2)}} /.
blowup /. First@sol]
}]
],
{x, 0, 10}
]

Comments

Popular posts from this blog

plotting - Filling between two spheres in SphericalPlot3D

Manipulate[ SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, Mesh -> None, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], {n, 0, 1}] I cant' seem to be able to make a filling between two spheres. I've already tried the obvious Filling -> {1 -> {2}} but Mathematica doesn't seem to like that option. Is there any easy way around this or ... Answer There is no built-in filling in SphericalPlot3D . One option is to use ParametricPlot3D to draw the surfaces between the two shells: Manipulate[ Show[SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], ParametricPlot3D[{ r {Sin[t] Cos[1.5 Pi], Sin[t] Sin[1.5 Pi], Cos[t]}, r {Sin[t] Cos[0 Pi], Sin[t] Sin[0 Pi], Cos[t]}}, {r, 1, 2 - n}, {t, 0, Pi}, PlotStyle -> Yellow, Mesh -> {2, 15}]], {n, 0, 1}]

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}]

plotting - Mathematica: 3D plot based on combined 2D graphs

I have several sigmoidal fits to 3 different datasets, with mean fit predictions plus the 95% confidence limits (not symmetrical around the mean) and the actual data. I would now like to show these different 2D plots projected in 3D as in but then using proper perspective. In the link here they give some solutions to combine the plots using isometric perspective, but I would like to use proper 3 point perspective. Any thoughts? Also any way to show the mean points per time point for each series plus or minus the standard error on the mean would be cool too, either using points+vertical bars, or using spheres plus tubes. Below are some test data and the fit function I am using. Note that I am working on a logit(proportion) scale and that the final vertical scale is Log10(percentage). (* some test data *) data = Table[Null, {i, 4}]; data[[1]] = {{1, -5.8}, {2, -5.4}, {3, -0.8}, {4, -0.2}, {5, 4.6}, {1, -6.4}, {2, -5.6}, {3, -0.7}, {4, 0.04}, {5, 1.0}, {1, -6.8}, {2, -4.7}, {3, -1.