A more natural setting for the Laplace equation \(\Delta u = 0\) is a circle rather than a rectangle. On the other hand, what makes the problem somewhat more difficult is that we need polar coordinates.

Recall that the polar coordinates for the \((x,y)\)-plane are \((r,\theta)\text{:}\)

\begin{equation*}
x = r \cos \theta , \quad y = r \sin \theta ,
\end{equation*}

where \(r \geq 0\) and \(-\pi < \theta \leq \pi\text{.}\) So the point \((x,y)\) is distance \(r\) from the origin at an angle \(\theta\) from the positive \(x\)-axis.

Now that we know our coordinates, let us give the problem we wish to solve. We have a circular region of radius 1, and we are interested in the Dirichlet problem for the Laplace equation for this region. Let \(u(r,\theta)\) denote the temperature at the point \((r,\theta)\) in polar coordinates.

The first issue we face is that we do not know the Laplacian in polar coordinates. Normally we would find \(u_{xx}\) and \(u_{yy}\) in terms of the derivatives in \(r\) and \(\theta\text{.}\) We would need to solve for \(r\) and \(\theta\) in terms of \(x\) and \(y\text{.}\) In this case it is more convenient to work in reverse. We compute derivatives in \(r\) and \(\theta\) in terms of derivatives in \(x\) and \(y\) and then we solve. The computations are easier this way. First

Let us now try to solve for \(u_{xx} + u_{yy}\text{.}\) We start with \(\frac{1}{r^2} u_{\theta\theta}\) to get rid of those pesky \(r^2\text{.}\) If we add \(u_{rr}\) and use the fact that \(\cos^2(\theta) +\sin^2(\theta) = 1\text{,}\) we get

Let us first focus on \(\Theta\text{.}\) We know that \(u(r,\theta)\) ought to be \(2\pi\)-periodic in \(\theta\text{,}\) that is, \(u(r,\theta) = u(r,\theta+2\pi)\text{.}\) Therefore, the solution to \(\Theta'' + \lambda \Theta = 0\) must be \(2\pi\)-periodic. We have seen such a problem in Example 4.1.5. We conclude that \(\lambda = n^2\) for a nonnegative integer \(n=0,1,2,3,\ldots\text{.}\) The equation becomes \(\Theta'' + n^2 \Theta = 0\text{.}\) When \(n=0\) the equation is just \(\Theta'' = 0\text{,}\) so we have the general solution \(A \theta + B\text{.}\) As \(\Theta\) is periodic, \(A=0\text{.}\) For convenience we write this solution as

\begin{equation*}
r^2 R'' + r R' - n^2 R = 0.
\end{equation*}

This equation appeared in exercises before—we solved it in Exercise 2.1.6 and Exercise 2.1.7. The idea is to try a solution \(r^s\) and if that does not give us two solutions, also try a solution of the form \(r^s \ln r\text{.}\) Let us name the solution for \(R_n\text{.}\) When \(n=0\) we obtain

\begin{equation*}
R_0 = A r^0 + B r^0 \ln r = A + B \ln r ,
\end{equation*}

and if \(n > 0\text{,}\) we get

\begin{equation*}
R_n = A r^n + B r^{-n} .
\end{equation*}

The function \(u(r,\theta)\) must be finite at the origin, that is, when \(r=0\text{.}\) So \(B=0\) in both cases. Set \(A=1\) in both cases as well; the constants in \(\Theta_n\) will pick up the slack so nothing is lost. Let

Therefore, to solve (4.26) we expand \(g(\theta)\text{,}\) which is a \(2\pi\)-periodic function, as a Fourier series, and then multiply the \(n^{\text{th}}\) term by \(r^n\text{.}\) To find the \(a_n\) and the \(b_n\) we compute

See the plot in Figure 4.26. The thing to notice in this example is that the effect of a high frequency is mostly felt at the boundary. In the middle of the disc, the solution is very close to zero. That is because \(r^{10}\) is rather small when \(r\) is close to 0.

Example4.10.2.

Let us solve a more difficult problem. Consider a long rod with circular cross section of radius 1. Suppose we wish to solve the steady state heat problem in the rod. If the rod is long enough, we simply need to solve the Laplace equation in two dimensions. Let us put the center of the rod at the origin and we have exactly the region we are currently studying—a circle of radius 1. For the boundary conditions, suppose in Cartesian coordinates \(x\) and \(y\text{,}\) the temperature on the boundary is 0 when \(y < 0\text{,}\) and it is \(2y\) when \(y > 0\text{.}\)

Let us set the problem up. As \(y = r\sin(\theta)\text{,}\) then on the circle of radius 1, that is, where \(r=1\text{,}\) we have \(2y = 2\sin(\theta)\text{.}\) So

We must now compute the Fourier series for the boundary condition. By now the reader has plentiful experience in computing Fourier series and so we simply state that

There is another way to solve the Dirichlet problem with the help of an integral kernel. That is, we will find a function \(P(r,\theta,\alpha)\) called the Poisson kernel^{ 1 }

While the integral will generally not be solvable analytically, it can be evaluated numerically. In fact, unless the boundary data is given as a Fourier series already, it may be much easier to numerically evaluate this formula as there is only one integral to evaluate.

The formula also has theoretical applications. For instance, as \(P(r,\theta,\alpha)\) will have infinitely many derivatives, then via differentiating under the integral we find that the solution \(u(r,\theta)\) has infinitely many derivatives, at least when inside the circle, \(r < 1\text{.}\) By “having infinitely many derivatives,” what you should think of is that \(u(r,\theta)\) has “no corners” and all of its partial derivatives of all orders exist and also have “no corners.”

We will compute the formula for \(P(r,\theta,\alpha)\) from the series solution, and this idea can be applied anytime you have a convenient series solution where the coefficients are obtained via integration. Hence you can apply this reasoning to obtain such integral kernels for other equations, such as the heat equation. The computation is long and tedious, but not overly difficult. Since the ideas are often applied in similar contexts, it is good to understand how this computation works.

What we do is start with the series solution and replace the coefficients with the integrals that compute them. Then we try to write everything as a single integral. We must use a different dummy variable for the integration and hence we use \(\alpha\) instead of \(\theta\text{.}\)

OK, so we have what we wanted, the expression in the parentheses is the Poisson kernel, \(P(r,\theta,\alpha)\text{.}\) However, we can do a lot better. It is still given as a series, and we would really like to have a nice simple expression for it. We must work a little harder. The trick is to rewrite everything in terms of complex exponentials. Let us work just on the kernel.

In the expression above, we recognize the geometric series. Recall from calculus that if \(z\) is a complex number where \(\lvert z \rvert < 1\text{,}\) then

Note that \(n\) starts at \(1\) and that is why we have the \(z\) in the numerator. It is the standard geometric series multiplied by \(z\text{.}\) We can use \(z = re^{i(\theta-\alpha)}\text{,}\) as lo and behold \(\lvert re^{i(\theta-\alpha)} \rvert = r < 1\text{.}\) Let us continue with the computation.

Sometimes the formula for the Poisson kernel is given together with the constant \(\frac{1}{2\pi}\text{,}\) in which case we should of course not leave it in front of the integral. Also, often the limits of the integral are given as 0 to \(2\pi\text{;}\) everything inside is \(2\pi\)-periodic in \(\alpha\text{,}\) so this does not change the integral.

Let us not leave the Poisson kernel without explaining its geometric meaning. Let \(s\) be the distance from \((r,\theta)\) to \((1,\alpha)\text{.}\) You may recall from calculus that this distance \(s\) in polar coordinates is given precisely by the square root of \(1 - 2r\cos(\theta-\alpha) +r^2\text{.}\) That is, the Poisson kernel is really the formula

One final note we make about the formula is that it is really a weighted average of the boundary values. First let us look at what happens at the origin, that is when \(r=0\text{.}\)

So \(u(0,0)\) is precisely the average value of \(g(\theta)\) and therefore the average value of \(u\) on the boundary. This is a general feature of harmonic functions, the value at some point \(p\) is equal to the average of the values on a circle centered at \(p\text{.}\)

What the formula says is that the value of the solution at any point in the circle is a weighted average of the boundary data \(g(\theta)\text{.}\) The kernel is bigger when \((1,\alpha)\) is closer to \((r,\theta)\text{.}\) Therefore when computing \(u(r,\theta)\text{,}\) we give more weight to the values \(g(\alpha)\) when \((1,\alpha)\) is closer to \((r,\theta)\) and less weight to the values \(g(\alpha)\) when \((1,\alpha)\) far from \((r,\theta)\text{.}\)

Exercises4.10.4Exercises

4.10.2.

Using series solve \(\Delta u = 0\text{,}\)\(u(1,\theta) = \lvert \theta \rvert\text{,}\) for \(-\pi < \theta
\leq \pi\text{.}\)

4.10.3.

Using series solve \(\Delta u = 0\text{,}\)\(u(1,\theta) = g(\theta)\) for the following data. Hint: trig identities.

Using the Poisson kernel, give the solution to \(\Delta u = 0\text{,}\) where \(u(1,\theta)\) is zero for \(\theta\) outside the interval \([-\nicefrac{\pi}{4},\nicefrac{\pi}{4}]\) and \(u(1,\theta)\) is 1 for \(\theta\) on the interval \([-\nicefrac{\pi}{4},\nicefrac{\pi}{4}]\text{.}\)

4.10.5.

Draw a graph for the Poisson kernel as a function of \(\alpha\) when \(r=\nicefrac{1}{2}\) and \(\theta = 0\text{.}\)

Describe what happens to the graph when you make \(r\) bigger (as it approaches 1).

Knowing that the solution \(u(r,\theta)\) is the weighted average of \(g(\theta)\) with Poisson kernel as the weight, explain what your answer to part b) means.

4.10.6.

Let \(g(\theta)\) be the function \(xy = \cos \theta \sin
\theta\) on the boundary. Use the series solution to find a solution to the Dirichlet problem \(\Delta u = 0\text{,}\)\(u(1,\theta) = g(\theta)\text{.}\) Now convert the solution to Cartesian coordinates \(x\) and \(y\text{.}\) Is this solution surprising? Hint: use your trig identities.

4.10.7.

Carry out the computation we needed in the separation of variables and solve \(r^2 R'' + r R' - n^2 R = 0\text{,}\) for \(n=0,1,2,3,\ldots\text{.}\)

4.10.8.

(challenging) Derive the series solution to the Dirichlet problem if the region is a circle of radius \(\rho\) rather than 1. That is, solve \(\Delta u = 0\text{,}\)\(u(\rho,\theta) = g(\theta)\text{.}\)

4.10.9.

(challenging)

Find the solution for \(\Delta u = 0\text{,}\)\(u(1,\theta) = x^2y^3 + 5 x^2\text{.}\) Write the answer in Cartesian coordinates.

Now solve \(\Delta u = 0\text{,}\)\(u(1,\theta) = x^k y^\ell\text{.}\) Write the solution in Cartesian coordinates.

Suppose you have a polynomial \(P(x,y) = \sum_{j=0}^m \sum_{k=0}^n c_{j,k}
x^j y^k\text{,}\) solve \(\Delta u = 0\text{,}\)\(u(1,\theta) = P(x,y)\) (that is, write down the formula for the answer). Write the answer in Cartesian coordinates.

Notice the answer is again a polynomial in \(x\) and \(y\text{.}\) See also Exercise 4.10.6.

4.10.101.

Using series solve \(\Delta u = 0\text{,}\)\(u(1,\theta) = 1+ \sum\limits_{n=1}^\infty \frac{1}{n^2}\sin(n\theta)\text{.}\)

Using the series solution find the solution to \(\Delta u = 0\text{,}\)\(u(1,\theta) = 1- \cos(\theta)\text{.}\) Express the solution in Cartesian coordinates (that is, using \(x\) and \(y\)).

Answer.

\(u = 1-x\)

4.10.103.

Try and guess a solution to \(\Delta u = -1\text{,}\)\(u(1,\theta) = 0\text{.}\) Hint: try a solution that only depends on \(r\text{.}\) Also first, don’t worry about the boundary condition.

Now solve \(\Delta u = -1\text{,}\)\(u(1,\theta) = \sin(2\theta)\) using superposition.

Answer.

a) \(u = \frac{-1}{4} r^2 + \frac{1}{4}\) b) \(u = \frac{-1}{4} r^2 + \frac{1}{4} + r^2 \sin(2\theta)\)

4.10.104.

(challenging) Derive the Poisson kernel solution if the region is a circle of radius \(\rho\) rather than 1. That is, solve \(\Delta u = 0\text{,}\)\(u(\rho,\theta) = g(\theta)\text{.}\)