In this section we consider eigenvalue problems of the form
where
As in Section 13.1, , , , and are real numbers, with
, , , and are continuous, and and are positive on .
We say that is an eigenvalue of Equation if Equation has a nontrivial solution . In this case, is an eigenfunction associated with , or a -eigenfunction. Solving the eigenvalue problem means finding all eigenvalues and associated eigenfunctions of Equation .
Example 13.2.1
Solve the eigenvalue problem
Solution
The characteristic equation of Equation is
with zeros
If then and are real and distinct, so the general solution of the differential equation in Equation is
The boundary conditions require that
Since the determinant of this system is , the system has only the trivial solution. Therefore isn’t an eigenvalue of Equation .
If then , so the general solution of Equation is
The boundary condition requires that , so and the boundary condition requires that . Therefore isn’t an eigenvalue of Equation .
If then
with
In this case the general solution of the differential equation in Equation is
The boundary condition requires that , so , which holds with if and only if , where is an integer. We may assume that is a positive integer. (Why?). From Equation , the eigenvalues are , with associated eigenfunctions
Example 13.2.2
Solve the eigenvalue problem
Solution
If , the differential equation in Equation reduces to , so ,
The boundary condition requires that , so . The boundary condition requires that , so . Therefore zero isn’t an eigenvalue of Equation .
If , we write with , so Equation becomes
an Euler equation (Section 7.4) with indicial equation
Therefore
The boundary conditions require that
Since the determinant of this system is , . Therefore Equation has no negative eigenvalues.
If we write with . Then Equation becomes
an Euler equation with indicial equation
so
The boundary condition requires that . Therefore . This holds with if and only if , where is a positive integer. Hence, the eigenvalues of Equation are , with associated eigenfunctions
For theoretical purposes, it is useful to rewrite the differential equation in Equation in a different form, provided by the next theorem.
Theorem 13.2.1
If and are continuous and and are positive on a closed interval then the equation
can be rewritten as
where , , and are continuous and and are positive on
Proof
We begin by rewriting Equation as
with , , and . (Note that is positive on .) Now let , where is any antiderivative of . Then is positive on and, since ,
is continuous on . Multiplying Equation by yields
Since is positive on , this equation has the same solutions as Equation . From Equation ,
so Equation can be rewritten as in Equation , with and . This completes the proof.
It is to be understood throughout the rest of this section that , , and have the properties stated in Theorem 13.2.1
. Moreover, whenever we write in a general statement, we mean
The differential equation Equation is called a Sturm-Liouville equation, and the eigenvalue problem
which is equivalent to Equation , is called a Sturm-Liouville problem.
Example 13.2.3
Rewrite the eigenvalue problem
of Theorem 13.2.1
as a Sturm-Liouville problem.
Solution
Comparing Equation to Equation shows that , so we take and . Multiplying the differential equation in Equation by yields
Since
Equation is equivalent to the Sturm–Liouville problem
Example 13.2.4
Rewrite the eigenvalue problem
of Theorem 13.2.2
as a Sturm-Liouville problem.
Solution
Dividing the differential equation in Equation by yields
Comparing this to Equation shows that , so we take and . Multiplying the differntial equation by yields
Since
Equation is equivalent to the Sturm–Liouville problem
Problems 1–4 of Section 11.1 are Sturm–Liouville problems. (Problem 5 isn’t, although some authors use a definition of Sturm-Liouville problem that does include it.) We were able to find the eigenvalues of Problems 1-4 explicitly because in each problem the coefficients in the boundary conditions satisfy and ; that is, each boundary condition involves either or , but not both. If this isn’t true then the eigenvalues can’t in general be expressed exactly by simple formulas; rather, approximate values must be obtained by numerical solution of equations derived by requiring the determinants of certain systems of homogeneous equations to be zero. To apply the numerical methods effectively, graphical methods must be used to determine approximate locations of the zeros of these determinants. Then the zeros can be computed accurately by numerical methods.
Example 13.2.5
Solve the Sturm–Liouville problem
Solution
If , the differential equation in Equation reduces to , with general solution . The boundary conditions require that
so . Therefore zero isn’t an eigenvalue of Equation .
If , we write where , and the differential equation in Equation becomes , with general solution
so
The boundary conditions require that
The determinant of this system is
Therefore the system Equation has a nontrivial solution if and only if or, equivalently,
The graph of the right side (Figure 13.2.1
) has a vertical asymptote at . Since the two sides have different signs if , this equation has no solution in . Figure 13.2.1
shows the graphs of the two sides of Equation on an interval to the right of the vertical asymptote, which is indicated by the dashed line. You can see that the two curves intersect near , Given this estmate, you can use Newton’s to compute more accurately. We computed . Therefore is an eigenvalue of Equation . From Equation and the first equation in Equation ,
Figure 13.2.1
: and
If we write where , and differential equation in Equation becomes , with general solution
so
The boundary conditions require that
The determinant of this system is
The system Equation has a nontrivial solution if and only if or, equivalently,
Figure 13.2.2
shows the graphs of the two sides of this equation. You can see from the figure that the graphs intersect at infinitely many points (, , ,…), where the error in this approximation approaches zero as . Given this estimate, you can use Newton’s method to compute more accurately. We computed
The estimates of the corresponding eigenvalues are
From Equation and the first equation in Equation ,
is an eigenfunction associated with
Figure 13.2.2
: and
Since the differential equations in Equation and Equation are more complicated than those in Equation and Equation respectively, what is the point of Theorem 13.2.1
? The point is this: to solve a specific problem, it may be better to deal with it directly, as we did in Examples 13.2.1
and 13.2.2
; however, we’ll see that transforming the general eigenvalue problem Equation to the Sturm–Liouville problem Equation leads to results applicable to all eigenvalue problems of the form Equation .
Theorem 13.2.2
If
and and are twice continuously functions on that satisfy the boundary conditions and then
Proof
Integration by parts yields
Since the last integral equals zero,
By assumption, and . Therefore
Since and , the determinants of these two systems must both be zero; that is,
This and Equation imply Equation , which completes the proof.
The next theorem shows that a Sturm–Liouville problem has no complex eigenvalues.
Theorem 13.2.3
If with then the boundary value problem
has only the trivial solution.
Proof
For this theorem to make sense, we must consider complex-valued solutions of
If where and are real-valued and twice differentiable, we define and . We say that is a solution of Equation if the real and imaginary parts of the left side of Equation are both zero. Since and , , and are real-valued,
so if and only if
Multiplying the first equation by and the second by yields
Subtracting the first equation from the second yields
so
Since
and
and implies that
Therefore Theorem 13.2.2
implies that first integral in Equation equals zero, so Equation reduces to
Since is positive on and by assumption, this implies that and on . Therefore on , which completes the proof.
Theorem 13.2.4
If and are distinct eigenvalues of the Sturm–Liouville problem
with associated eigenfunctions and respectively then
Proof
Since and satisfy the boundary conditions in Equation , Theorem 13.2.2
implies that
Since and , this implies that
Since , this implies Equation , which completes the proof.
If and are any integrable functions on and
we say that and orthogonal onwith respect to.
Theorem 13.1.1 implies the next theorem.
Theorem 13.2.5
If and both satisfy
then for some constant
We’ve now proved parts of the next theorem. A complete proof is beyond the scope of this book.
Theorem 13.2.6
The set of all eigenvalues of the Sturm–Liouville problem
can be ordered as
and
For each if is an arbitrary -eigenfunction then every -eigenfunction is a constant multiple of If and are orthogonal with respect to that is
You may want to verify Equation for the eigenfunctions obtained in Examples 13.2.1
and 13.2.2
.
In conclusion, we mention the next theorem. The proof is beyond the scope of this book.
Theorem 13.2.7
Let be the eigenvalues of the Sturm–Liouville problem
with associated eigenvectors …, … Suppose is piecewise smooth (Definition 11.2.3) on For each let