# Wronskian

In mathematics, the **Wronskian** (or **Wrońskian**) is a determinant introduced by Template:Harvs and named by Template:Harvs. 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.

## Definition

The Wronskian of two differentiable functions *f* and *g* is *W*(*f*, *g*) = *f g*′ – *g f*′.

More generally, for *n* real- or complex-valued functions *f*_{1}, . . . , *f _{n}*, which are

*n*– 1 times differentiable on an interval

*I*, the Wronskian

*W*(

*f*

_{1}, . . . ,

*f*) as a function on

_{n}*I*is defined by

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**.

When the functions *f _{i}* are solutions of a linear differential equation, the Wronskian can be found explicitly using Abel's identity, even if the functions

*f*are not known explicitly.

_{i}## The Wronskian and linear independence

If the functions *f _{i}* 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 Template:Harvtxt pointed out that the functions *x*^{2} 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.
Template:Harvtxt observed that if the functions are analytic, then the vanishing of the Wronskian in an interval implies that they are linearly dependent. Template:Harvtxt 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. Template:Harvtxt gave a more general condition that together with the vanishing of the Wronskian implies linear dependence.

## Generalized Wronskians

For *n* functions of several variables, a **generalized Wronskian** is the determinant of an *n* by *n* matrix with entries *D _{i}*(

*f*) (with 0 ≤

_{j}*i*<

*n*), where each

*D*is some constant coefficient linear partial differential operator of order

_{i}*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 Template:Harvtxt.

## See also

- Moore matrix, analogous to the Wronskian with differentiation replaced by the Frobenius endomorphism over a finite field.
- Variation of parameters

## References

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