Difference between revisions of "Frobenius method"
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\begin{equation} \tag{a9} L = a ^ { [ 2 ] } ( z ) z ^ { 2 } \left( \frac { d } { d z } \right) ^ { 2 } + a ^ { [ 1 ] } ( z ) z \left( \frac { d } { d z } \right) + a ^ { [ 0 ] } ( z ). \end{equation} | |||
− | Here, one has | + | Here, one has to assume that a ^ { 2_0 } \neq 0 to obtain a regular singular point. The indicial polynomial is simply |
\begin{equation*} \pi ( \lambda ) = ( \lambda + 2 ) ( \lambda + 1 ) a ^ { 2_0 } + ( \lambda + 1 ) a ^ { 1_0 } + a ^ { 0_0 } = \end{equation*} | \begin{equation*} \pi ( \lambda ) = ( \lambda + 2 ) ( \lambda + 1 ) a ^ { 2_0 } + ( \lambda + 1 ) a ^ { 1_0 } + a ^ { 0_0 } = \end{equation*} |
Revision as of 22:42, 12 December 2020
This method enables one to compute a fundamental system of solutions for a holomorphic differential equation near a regular singular point (cf. also Singular point).
Suppose one is given a linear differential operator
\begin{equation} \tag{a1} L = \sum _ { n = 0 } ^ { N } a ^ { [ n ] } ( z ) z ^ { n } \left( \frac { d } { d z } \right) ^ { n }, \end{equation}
where for n = 0 , \ldots , N and some r > 0, the functions
\begin{equation} \tag{a2} a ^ { [ n ] } ( z ) = \sum _ { i = 0 } ^ { \infty } a _ { i } ^ { n } z ^ { i } \end{equation}
are holomorphic for | z | < r and a ^ { N_ 0} \neq 0 (cf. also Analytic function). The point z = 0 is called a regular singular point of L. Formula (a1) gives the differential operator in its Frobenius normal form if a ^ { [ N ] } ( z ) \equiv 1.
The Frobenius method is useful for calculating a fundamental system for the homogeneous linear differential equation
\begin{equation} \tag{a3} L ( u ) = 0 \end{equation}
in the domain \{ z \in \mathbf{C} : | z | < \epsilon \} \backslash ( - \infty , 0 ] near the regular singular point at z = 0. Here, \epsilon > 0, and for an equation in normal form, actually \epsilon \geq r. The cut along some ray is introduced because the solutions u are expected to have an essential singularity at z = 0.
The Frobenius method is a generalization of the treatment of the simpler Euler–Cauchy equation
\begin{equation} \tag{a4} L _ { 0 } ( u ) = 0, \end{equation}
where the differential operator L_0 is made from (a1) by retaining only the leading terms. The Euler–Cauchy equation can be solved by taking the guess z = u ^ { \lambda } with unknown parameter \lambda \in \mathbf{C}. One gets L _ { 0 } ( u ^ { \lambda } ) = \pi ( \lambda ) z ^ { \lambda } with the indicial polynomial
\begin{equation} \tag{a5} \pi ( \lambda ) = \sum _ { n = 0 } ^ { N } ( \lambda + n ) ( \lambda + n - 1 ) \ldots ( \lambda + 1 ) a ^ { n _0} = \end{equation}
\begin{equation*} = a _ { 0 } ^ { N } \prod _ { i = 1 } ^ { \nu } ( \lambda - \lambda _ { i } ) ^ { n _ { i } }. \end{equation*}
In the following, the zeros \lambda _ { i } of the indicial polynomial will be ordered by requiring
\begin{equation*} \operatorname { Re } \lambda _ { 1 } \geq \ldots \geq \operatorname { Re } \lambda _ { \nu }. \end{equation*}
It is assumed that all \nu roots are different and one denotes their multiplicities by n_i.
The method of Frobenius starts with the guess
\begin{equation} \tag{a6} u ( z , \lambda ) = z ^ { \lambda } \sum _ { k = 0 } ^ { \infty } c _ { k } ( \lambda ) z ^ { k }, \end{equation}
with an undetermined parameter \lambda \in \mathbf{C}. The coefficients have to be calculated by requiring that
\begin{equation} \tag{a7} L ( u ( z , \lambda ) ) = \pi ( \lambda ) z ^ { \lambda }. \end{equation}
This requirement leads to c _ { 0 } \equiv 1 and
\begin{equation} \tag{a8} c _ { j } ( \lambda ) = - \sum _ { k = 0 } ^ { j - 1 } \frac { c _ { k } ( \lambda ) p _ { j - k } ( \lambda + k ) } { \pi ( \lambda + j ) } \end{equation}
as a recursion formula for c_{j} for all j \geq 1. Here, p _ { j } ( \lambda ) are polynomials in \lambda of degree at most N, which are given below.
The easy generic case occurs if the indicial polynomial has only simple zeros and their differences \lambda _ { i } - \lambda _ { j } are never integer valued. Under these assumptions, the N functions
\begin{equation*} u ( z , \lambda _ { 1 } ) = z ^ { \lambda _ { 1 } } + \ldots , \ldots , u ( z , \lambda _ { N } ) = z ^ { \lambda _ { N } } +\dots \end{equation*}
are a fundamental system of solutions of (a3).
Complications.
Complications can arise if the generic assumption made above is not satisfied. Putting \lambda = \lambda _ { i } in (a6), obtaining solutions of (a3) can be impossible because of poles of the coefficients c_j ( \lambda ). These solutions are rational functions of \lambda with possible poles at the poles of c _ { 1 } ( \lambda ) , \ldots , c _ { j - 1} ( \lambda ) as well as at \lambda _ { 1 } + j , \ldots , \lambda _ { \nu } + j.
The poles are compensated for by multiplying u ( z , \lambda ) at first with powers of \lambda - \lambda _ { i } and differentiation by the parameter \lambda before setting \lambda = \lambda _ { i }.
Since the general situation is rather complex, two special cases are given first. Let \mathbf{N} denote the set of natural numbers starting at 1 (i.e., excluding 0). Note that neither of the special cases below does exclude the simple generic case above.
All solutions have expansions of the form
\begin{equation*} u _ { i l } = z ^ { \lambda _ { i } } \sum _ { j = 0 } ^ { l } \sum _ { k = 0 } ^ { \infty } b _ { j k } ( \operatorname { log } z ) ^ { j } z ^ { k }. \end{equation*}
The leading term b _ { l0 } ( \operatorname { log } z ) ^ { l } z ^ { \lambda _ { i } } is useful as a marker for the different solutions. Because for i = 1 , \dots , \nu and l = 0 , \dots , n _ { i } - 1, all leading terms are different, the method of Frobenius does indeed yield a fundamental system of N linearly independent solutions of the differential equation (a3).
Special case 1.
For any i = 1 , \dots , \nu, the zero \lambda _ { i } of the indicial polynomial has multiplicity n _ { i } \geq 1, but none of the numbers \lambda _ { 1 } - \lambda _ { i } , \ldots , \lambda _ { i - 1 } - \lambda _ { i } is a natural number.
In this case, the functions
\begin{equation*} u ( z , \lambda _ { i } ) = z ^ { \lambda _ { i } } + \ldots , \end{equation*}
\begin{equation*} \frac { \partial } { \partial \lambda } u ( z , \lambda _ { i } ) = ( \operatorname { log } z ) z ^ { \lambda_i } +\dots \dots \end{equation*}
\begin{equation*} \left( \frac { \partial } { \partial \lambda } \right) ^ { ( n _ { i } - 1 ) } u ( z , \lambda _ { i } ) = ( \operatorname { log } z ) ^ { n _ { i } - 1 } z ^ { \lambda _ { i } } +\dots \end{equation*}
are n_i linearly independent solutions of the differential equation (a3).
Special case 2.
Suppose \lambda _ { 1 } - \lambda _ { 2 } \in \mathbf{N}.
Then the functions
\begin{equation*} ( \frac { \partial } { \partial \lambda } ) ^ { n _ { 1 } + l } [ u ( z , \lambda ) ( \lambda - \lambda _ { 2 } ) ^ { n _ { 1 } } ] = \end{equation*}
\begin{equation*} = \frac { ( n _ { 1 } + l ) ! } { l ! } ( \operatorname { log } z ) ^ { l } z ^ { \lambda _ { 2 } } + \ldots, \end{equation*}
all with \lambda = \lambda _ { 2 } and l = 0 , \dots , n _ { 2 } - 1, are n_{2} linearly independent solutions of the differential equation (a3). The solution for l = 0 may contain logarithmic terms in the higher powers, starting with ( \operatorname { log } z ) z ^ { \lambda _ { 1 } }.
Special case 3.
Let 1 \leq j \leq \nu and let \lambda _ { i } be a zero of the indicial polynomial of multiplicity n_i for i = 1 , \dots , j - 1.
In this case, define m_j to be the sum of those multiplicities for which \lambda _ { i } - \lambda _ { j } \in \mathbf{N}. Hence,
\begin{equation*} m _ { j } = \sum \{ n _ { i } : 1 \leq i < j \ \text{ and } \ \lambda _ { i } - \lambda _ { j } \in \mathbf{N} \}. \end{equation*}
The functions
\begin{equation*} ( \frac { \partial } { \partial \lambda } ) ^ { m _ { j } + l } \left[ u ( z , \lambda ) ( \lambda - \lambda _ { j } ) ^ { m _ { j } } \right] = \end{equation*}
\begin{equation*} = \frac { ( m _ { j } + l ) ! } { l ! } ( \operatorname { log } z ) ^ { l } z ^ { \lambda _ { j } } + \ldots, \end{equation*}
with l = 0 , \dots , n _ { j } - 1 and \lambda = \lambda _ { j }, are n_j linearly independent solutions of the differential equation (a3).
The method looks simpler in the most common case of a differential operator
\begin{equation} \tag{a9} L = a ^ { [ 2 ] } ( z ) z ^ { 2 } \left( \frac { d } { d z } \right) ^ { 2 } + a ^ { [ 1 ] } ( z ) z \left( \frac { d } { d z } \right) + a ^ { [ 0 ] } ( z ). \end{equation}
Here, one has to assume that a ^ { 2_0 } \neq 0 to obtain a regular singular point. The indicial polynomial is simply
\begin{equation*} \pi ( \lambda ) = ( \lambda + 2 ) ( \lambda + 1 ) a ^ { 2_0 } + ( \lambda + 1 ) a ^ { 1_0 } + a ^ { 0_0 } = \end{equation*}
\begin{equation*} = a ^ { 2 } o ( \lambda - \lambda _ { 1 } ) ( \lambda - \lambda _ { 2 } ). \end{equation*}
Only two special cases can occur:
1) \lambda _ { 1 } = \lambda _ { 2 }. The functions
\begin{equation*} u ( z , \lambda _ { 1 } ) = z ^ { \lambda _ { 1 } } + \ldots, \end{equation*}
\begin{equation*} \frac { \partial u } { \partial \lambda } ( z , \lambda _ { 1 } ) = ( \operatorname { log } z ) z ^ { \lambda _ { 1 } } \end{equation*}
are a fundamental system.
2) \lambda _ { 1 } - \lambda _ { 2 } \in \mathbf{N}. The functions
\begin{equation*} u ( z , \lambda _ { 1 } ) = z ^ { \lambda _ { 1 } } + \ldots, \end{equation*}
\begin{equation*} ( \frac { \partial } { \partial \lambda } ) [ u ( z , \lambda ) ( \lambda - \lambda _ { 2 } ) ] = z ^ { \lambda_2 } + \ldots , \end{equation*}
with \lambda = \lambda _ { 2 } in the second function, are two linearly independent solutions of the differential equation (a9). The second solution can contain logarithmic terms in the higher powers starting with ( \operatorname { log } z ) z ^ { \lambda _ { 1 } }.
The Frobenius method has been used very successfully to develop a theory of analytic differential equations, especially for the equations of Fuchsian type, where all singular points assumed to be regular (cf. also Fuchsian equation). A similar method of solution can be used for matrix equations of the first order, too. An adaption of the Frobenius method to non-linear problems is restricted to exceptional cases. The approach does produce special separatrix-type solutions for the Emden–Fowler equation, where the non-linear term contains only powers.
Computation of the polynomials p _ { j } ( \lambda ).
In the guess
\begin{equation*} u ( z , \lambda ) = z ^ { \lambda } \sum _ { k = 0 } ^ { \infty } c _ { k } ( \lambda ) z ^ { k }, \end{equation*}
the coefficients have to be calculated from the requirement (a7). Indeed (a1) and (a2) imply
\begin{equation*} L ( u ( z , \lambda ) ) = \end{equation*}
\begin{equation*} = [ \sum _ { i = 0 } ^ { \infty } \sum _ { n = 0 } ^ { N } a _ { i } ^ { n } z ^ { n + i } ( \frac { \partial } { \partial z } ) ^ { n } ] [ \sum _ { k = 0 } ^ { \infty } c _ { k } ( \lambda ) z ^ { \lambda + k } ] = \end{equation*}
\begin{equation*} = \sum _ { i = 0 } ^ { \infty } \sum _ { k = 0 } ^ { \infty } c _ { k } ( \lambda ) z ^ { i } \sum _ { n = 0 } ^ { N } a _ { i } ^ { n } z ^ { n } \left( \frac { \partial } { \partial z } \right) ^ { n } z ^ { \lambda + k } = \end{equation*}
\begin{equation*} = \sum _ { i = 0 } ^ { \infty } \sum _ { k = 0 } ^ { \infty } c _ { k } ( \lambda ) z ^ { i } p _ { i } ( \lambda + k ) z ^ { \lambda + k } = \end{equation*}
\begin{equation*} = z ^ { \lambda } \sum _ { j = 0 } ^ { \infty } z ^ { j } \left[ \sum _ { i + k = j } c _ { k } ( \lambda ) p _ { i } ( \lambda + k ) \right] = \end{equation*}
\begin{equation*} = c _ { 0 } z ^ { \lambda } \pi ( \lambda ) + \end{equation*}
\begin{equation*} + z ^ { \lambda } \sum _ { j = 1 } ^ { \infty } z ^ { j } \left[ c _ { j } ( \lambda ) \pi ( \lambda + j ) + \sum _ { k = 0 } ^ { j - 1 } c _ { k } ( \lambda ) p _ { j - k } ( \lambda + k ) \right]. \end{equation*}
Here, p _ { i } ( \lambda ) are polynomials of degree at most N determined by setting
\begin{equation*} p _ { i } ( z ) z ^ { \lambda } = \sum _ { n = 0 } ^ { N } a ^ { n _ { i } } z ^ { n } ( \frac { \partial } { \partial z } ) ^ { n } z ^ { \lambda }. \end{equation*}
Because of (a7), one finds c _ { 0 } \equiv 1 and the recursion formula (a8).
References
[a1] | R. Redheffer, "Differential equations, theory and applications" , Jones and Bartlett (1991) |
[a2] | F. Rothe, "A variant of Frobenius' method for the Emden–Fowler equation" Applicable Anal. , 66 (1997) pp. 217–245 |
[a3] | D. Zwillinger, "Handbook of differential equations" , Acad. Press (1989) |
Frobenius method. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Frobenius_method&oldid=50593