In mathematics, the Wronskian is a determinant introduced by Józef Hoene-Wronski (1812) and named by Thomas Muir (1882, Chapter XVIII). It is used in the study of differential equations, where it can sometimes be used to show that a set of solutions is linearly independent.
The Wronskian of two differentiable functions f and g is W(f, g) = f g′ – g f′.
That is, it is the determinant of the matrix constructed by placing the functions in the first row, the first derivative of each function in the second row, and so on through the (n – 1)th derivative, thus forming a square matrix sometimes called a fundamental matrix.
The Wronskian and linear independence
If the functions fi are linearly dependent, then so are the columns of the Wronskian as differentiation is a linear operation, so the Wronskian vanishes. Thus, the Wronskian can be used to show that a set of differentiable functions is linearly independent on an interval by showing that it does not vanish identically.
A common misconception is that W = 0 everywhere implies linear dependence, but Peano (1889) pointed out that the functions x2 and |x|x have continuous derivatives and their Wronskian vanishes everywhere, yet they are not linearly dependent in any neighborhood of 0. There are several extra conditions which ensure that the vanishing of the Wronskian in an interval implies linear dependence. Peano (1889) observed that if the functions are analytic, then the vanishing of the Wronskian in an interval implies that they are linearly dependent. Bocher (1901) gave several other conditions for the vanishing of the Wronskian to imply linear dependence; for example, if the Wronskian of n functions is identically zero and the n Wronskians of n – 1 of them do not all vanish at any point then the functions are linearly dependent. Wolsson (1989a) gave a more general condition that together with the vanishing of the Wronskian implies linear dependence.
For n functions of several variables, a generalized Wronskian is the determinant of an n by n matrix with entries Di(fj) (with 0 ≤ i < n), where each Di is some constant coefficient linear partial differential operator of order i. If the functions are linearly dependent then all generalized Wronskians vanish. As in the 1 variable case the converse is not true in general: if all generalized Wronskians vanish, this does not imply that the functions are linearly dependent. However, the converse is true in many special cases. For example, if the functions are polynomials and all generalized Wronskians vanish, then the functions are linearly dependent. Roth used this result about generalized Wronskians in his proof of Roth's theorem. For more general conditions under which the converse is valid see Wolsson (1989b).
- Moore matrix, analogous to the Wronskian with differentiation replaced by the Frobenius endomorphism over a finite field.
- Variation of parameters
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- Peano, Giuseppe (1889), Sur le déterminant wronskien., Mathesis (in French) IX: 75–76, 110–112, JFM 21.0153.01
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- Wolsson, Kenneth (1989a), A condition equivalent to linear dependence for functions with vanishing Wronskian, Linear Algebra and its Applications 116: 1–8, doi:10.1016/0024-3795(89)90393-5, ISSN 0024-3795, MR 989712, Zbl 0671.15005
- Wolsson, Kenneth (1989b), Linear dependence of a function set of m variables with vanishing generalized Wronskians, Linear Algebra and its Applications 117: 73–80, doi:10.1016/0024-3795(89)90548-X, ISSN 0024-3795, MR 993032, Zbl 0724.15004