Differential Equations for EngineersXYZ Homework Edition

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7.3 Singular Points and the Method of Frobenius

Examples

While behavior of ODEs at singular points is more complicated, certain singular points are not especially difficult to solve. Let us look at some examples before giving a general method. We may be lucky and obtain a power series solution using the method of the previous section, but in general we may have to try other things.

Interactive figureSlope field of x y' = r y at the singular point x = 0, with the exponent r on a sliderDrag the Frobenius exponent r slider from -2 to 2.
Short slopes tile the frame and swing sharply near the vertical axis, where the equation is undefined, and three solution curves reach the origin there — one above the axis, one lower, one mirrored below — each arriving with a vertical tangent and flattening as it runs outward. Dragging the exponent changes the origin's character entirely: negative settings send the curves shooting away from it, zero flattens them into horizontal lines, and settings above one bring them in flat instead of vertically. Adjustable parameter: Frobenius exponent r (r) = 0.5. Viewing window: x from -4 to 4, y from -2.47 to 2.47.
XYZ Graph · viewer build 5edf91b
The slope field of x y′ = r y with three of its solutions y = C|x|^r drawn through it. The equation worked just below, 2xy′ − y = 0, is the case r = 1/2 — where the figure opens — because substituting y = x^r turns the ODE into the indicial equation for r. Drag the slider to watch the singular point change character: for r < 0 the solutions themselves blow up at x = 0; at r = 0 they flatten into the horizontal lines y = C; for 0 < r < 1, the range containing Lebl's r = 1/2, they reach the origin with a vertical tangent, which is why the trivial y = 0 is the only solution differentiable there; at r = 1 the two branches meet in a corner; and only for r > 1 do they arrive with zero slope and the singular point stop hurting.

Not every problem with a singular point has a solution of the form y=xry=x^r, of course. But perhaps we can combine the methods. What we will do is to try a solution of the form

y = x r f ( x ) y = x^r f(x) \nonumber

where f(x)f(x) is an analytic function.

Method of Frobenius

Before giving the general method, let us clarify when the method applies. Let

p ( x ) y + q ( x ) y + r ( x ) y = 0 p(x) y'' + q(x) y' + r(x) y = 0 \nonumber

be an ODE. As before, if p(x0)=0p(x_0) = 0, then x0x_0 is a singular point. If, furthermore, the limits

lim x x 0 ( x x 0 ) q ( x ) p ( x ) and lim x x 0 ( x x 0 ) 2 r ( x ) p ( x ) \lim_{x \to x_0} ~ (x-x_0) \dfrac{q(x)}{p(x)} \qquad \text{and} \qquad \lim_{x \to x_0} ~ (x-x_0)^2 \dfrac{r(x)}{p(x)} \nonumber

both exist and are finite, then we say that x0x_0 is a regular singular point.

Let us now discuss the general Method of Frobenius1. Let us only consider the method at the point x=0x=0 for simplicity. The main idea is the following theorem.

The method usually breaks down like this.

  1. We seek a Frobenius-type solution of the form

    y=k=0akxk+r.y = \sum_{k=0}^\infty a_k x^{k+r}. \nonumber

    We plug this yy into equation (7.3.7). We collect terms and write everything as a single series.
  2. The obtained series must be zero. Setting the first coefficient (usually the coefficient of xrx^r) in the series to zero we obtain the indicial equation, which is a quadratic polynomial in rr.
  3. If the indicial equation has two real roots r1r_1 and r2r_2 such that r1r2r_1 - r_2 is not an integer, then we have two linearly independent Frobenius-type solutions. Using the first root, we plug in

    y1=xr1k=0akxk,y_1 = x^{r_1} \sum_{k=0}^\infty a_k x^{k}, \nonumber

    and we solve for all aka_k to obtain the first solution. Then using the second root, we plug in

    y2=xr2k=0bkxk,y_2 = x^{r_2} \sum_{k=0}^\infty b_k x^{k}, \nonumber

    and solve for all bkb_k to obtain the second solution.
  4. If the indicial equation has a doubled root rr, then there we find one solution

    y1=xrk=0akxk,y_1 = x^{r} \sum_{k=0}^\infty a_k x^{k}, \nonumber

    and then we obtain a new solution by plugging

    y2=xrk=0bkxk+(lnx)y1,y_2 = x^{r} \sum_{k=0}^\infty b_k x^{k} + (\ln x) y_1, \nonumber

    into Equation (7.3.7) and solving for the constants bkb_k.
  5. If the indicial equation has two real roots such that r1r2r_1-r_2 is an integer, then one solution is

    y1=xr1k=0akxk,y_1 = x^{r_1} \sum_{k=0}^\infty a_k x^{k}, \nonumber

    and the second linearly independent solution is of the form

    y2=xr2k=0bkxk+C(lnx)y1,y_2 = x^{r_2} \sum_{k=0}^\infty b_k x^{k} + C (\ln x) y_1, \nonumber

    where we plug y2y_2 into (7.3.7) and solve for the constants bkb_k and CC.
  6. Finally, if the indicial equation has complex roots, then solving for aka_k in the solution

    y=xr1k=0akxky = x^{r_1} \sum_{k=0}^\infty a_k x^{k} \nonumber

    results in a complex-valued function---all the aka_k are complex numbers. We obtain our two linearly independent solutions2 by taking the real and imaginary parts of yy.

The main idea is to find at least one Frobenius-type solution. If we are lucky and find two, we are done. If we only get one, we either use the ideas above or even a different method such as reduction of order (Exercise 2.1.8) to obtain a second solution.

Bessel Functions

An important class of functions that arises commonly in physics are the Bessel functions3. For example, these functions appear when solving the wave equation in two and three dimensions. First we have Bessel's equation of order pp:

x 2 y + x y + ( x 2 p 2 ) y = 0 . x^2 y'' + xy' + \left(x^2 - p^2\right)y = 0. \nonumber

We allow pp to be any number, not just an integer, although integers and multiples of 12\dfrac{1}{2} are most important in applications. When we plug

y = k = 0 a k x k + r y = \sum_{k=0}^\infty a_k x^{k+r} \nonumber

into Bessel's equation of order pp we obtain the indicial equation

r ( r 1 ) + r p 2 = ( r p ) ( r + p ) = 0 . r(r-1)+r-p^2 = (r-p)(r+p) = 0. \nonumber

Therefore we obtain two roots r1=pr_1 = p and r2=pr_2 = -p. If pp is not an integer following the method of Frobenius and setting a0=1a_0 = 1, we obtain linearly independent solutions of the form

y 1 = x p k = 0 ( 1 ) k x 2 k 2 2 k k ! ( k + p ) ( k 1 + p ) ( 2 + p ) ( 1 + p ) , y 2 = x p k = 0 ( 1 ) k x 2 k 2 2 k k ! ( k p ) ( k 1 p ) ( 2 p ) ( 1 p ) . \begin{align}\begin{aligned} y_1 &= x^p \sum_{k=0}^{\infty} \dfrac{(-1)^k x^{2k}}{2^{2k}k!(k+p)(k-1+p) \cdots (2+p)(1+p)}, \\ y_2 &= x^{-p} \sum_{k=0}^{\infty} \dfrac{(-1)^k x^{2k}}{2^{2k}k!(k-p)(k-1-p) \cdots (2-p)(1-p)}.\end{aligned}\end{align} \nonumber

Bessel functions will be convenient constant multiples of y1y_1 and y2y_2. First we must define the gamma function

Γ ( x ) = 0 t x 1 e t d t . \Gamma(x) = \int_0^\infty t^{x-1} e^{-t} \, dt. \nonumber

Notice that Γ(1)=1\Gamma(1) = 1. The gamma function also has a wonderful property

Γ ( x + 1 ) = x Γ ( x ) . \Gamma(x+1) = x \Gamma(x). \nonumber

From this property, one can show that Γ(n)=(n1)!\Gamma(n) = (n-1)! when nn is an integer, so the gamma function is a continuous version of the factorial. We compute:

Γ ( k + p + 1 ) = ( k + p ) ( k 1 + p ) ( 2 + p ) ( 1 + p ) Γ ( 1 + p ) , Γ ( k p + 1 ) = ( k p ) ( k 1 p ) ( 2 p ) ( 1 p ) Γ ( 1 p ) . \begin{align}\begin{aligned} \Gamma(k+p+1)=(k+p)(k-1+p)\cdots (2+p)(1+p) \Gamma(1+p),\\ \Gamma(k-p+1)=(k-p)(k-1-p)\cdots (2-p)(1-p) \Gamma(1-p).\end{aligned}\end{align} \nonumber

We define the Bessel functions of the first kind of order pp and p-p as

J p ( x ) = 1 2 p Γ ( 1 + p ) y 1 = k = 0 ( 1 ) k k ! Γ ( k + p + 1 ) ( x 2 ) 2 k + p , J p ( x ) = 1 2 Γ ( 1 p ) y 2 = k = 0 ( 1 ) k k ! Γ ( k p + 1 ) ( x 2 ) 2 k p . \begin{align}\begin{aligned} J_p(x) &= \dfrac{1}{2^p\Gamma(1+p)} y_1=\sum_{k=0}^\infty \dfrac{{(-1)}^k}{k! \Gamma(k+p+1)}{\left(\dfrac{x}{2}\right)}^{2k+p}, \\ J_{-p}(x) &= \dfrac{1}{2^{-}\Gamma(1-p)} y_2=\sum_{k=0}^\infty \dfrac{{(-1)}^k}{k! \Gamma(k-p+1)}{\left(\dfrac{x}{2}\right)}^{2k-p}.\end{aligned}\end{align} \nonumber

As these are constant multiples of the solutions we found above, these are both solutions to Bessel's equation of order pp. The constants are picked for convenience.

When pp is not an integer, JpJ_p and JpJ_{-p} are linearly independent. When nn is an integer we obtain

J n ( x ) = k = 0 ( 1 ) k k ! ( k + n ) ! ( x 2 ) 2 k + n . J_n(x) =\sum_{k=0}^\infty \dfrac{{(-1)}^k}{k! (k+n)!}{\left(\dfrac{x}{2}\right)}^{2k+n}. \nonumber

In this case it turns out that

J n ( x ) = ( 1 ) n J n ( x ) , J_n(x) = {(-1)}^nJ_{-n}(x), \nonumber

and so we do not obtain a second linearly independent solution. The other solution is the so-called Bessel function of second kind. These make sense only for integer orders nn and are defined as limits of linear combinations of Jp(x)J_p(x) and Jp(x)J_{-p}(x) as pp approaches nn in the following way:

Y n ( x ) = lim p n cos ( p π ) J p ( x ) J p ( x ) sin ( p π ) . Y_n(x) = \lim_{p\to n} \dfrac{\cos(p \pi) J_p(x) - J_{-p}(x)}{\sin(p \pi)}. \nonumber

As each linear combination of Jp(x)J_p(x) and Jp(x)J_{-p}(x) is a solution to Bessel's equation of order pp, then as we take the limit as pp goes to nn, Yn(x)Y_n(x) is a solution to Bessel's equation of order nn. It also turns out that Yn(x)Y_n(x) and Jn(x)J_n(x) are linearly independent. Therefore when nn is an integer, we have the general solution to Bessel's equation of order nn

y = A J n ( x ) + B Y n ( x ) , y = A J_n(x) + B Y_n(x), \nonumber

for arbitrary constants AA and BB. Note that Yn(x)Y_n(x) goes to negative infinity at x=0x=0. Many mathematical software packages have these functions Jn(x)J_n(x) and Yn(x)Y_n(x) defined, so they can be used just like say sin(x)\sin(x) and cos(x)\cos(x). In fact, they have some similar properties. For example, J1(x)-J_1(x) is a derivative of J0(x)J_0(x), and in general the derivative of Jn(x)J_n(x) can be written as a linear combination of Jn1(x)J_{n-1}(x) and Jn+1(x)J_{n+1}(x). Furthermore, these functions oscillate, although they are not periodic. See Figure 1\PageIndex{1} for graphs of Bessel functions.

Two side-by-side plots for x from 0 to 10, each a pair of decaying oscillations about a quarter period out of step. On the left the blue curve starts at 1 and the green at 0, peaking near 0.58; on the right both plunge toward minus infinity as x approaches 0.
Figure 1\PageIndex{1}: Plot of the J0(x)J_{0}(x) and J1(x)J_{1}(x) in the first graph and Y0(x)Y_{0}(x) and Y1(x)Y_{1}(x) in the second graph.

Footnotes

[1] Named after the German mathematician Ferdinand Georg Frobenius (1849 – 1917).

[2] See Joseph L. Neuringera, The Frobenius method for complex roots of the indicial equation, International Journal of Mathematical Education in Science and Technology, Volume 9, Issue 1, 1978, 71–77.

[3] Named after the German astronomer and mathematician Friedrich Wilhelm Bessel (1784 – 1846).

Adapted from Differential Equations for Engineers by Jiří Lebl (https://www.jirka.org/diffyqs/), © Jiří Lebl, licensed under CC BY-SA 4.0. Changes were made. License: CC-BY-SA-4.0.

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