What is the connection between the Wronskian and linear independence?

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In summary, the Wronskian indicates linear independence when it is not equal to zero and linear dependence when it is equal to zero. This can be understood by considering the Wronskian as the determinant of a square matrix of functions, where a nonzero determinant indicates a unique solution to a system of equations. However, proving this for differential equations would require further analysis and considerations.
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I was just curious and had a question: why does the Wronskian indicate linear independence if ## W ≠ 0 ## but is linearly dependent if ## W = 0 ##? Is there a proof to help understand the exact operations of the Wronskian and why it conveys these properties based on these results alone? Thank you!
 
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First, think about systems of simultaneous linear equations and how they analyzed with matrices. Traditionally, we write the system in the form [itex] M\ x = b [/itex] with the left hand side being the product of a matrix multiplied on the right by a column vector (as opposed to a matrix multiplied on the left by a row vector). The product [itex] M\ x [/itex] of a matrix times a column vector can be viewed as a linear combination of the columns of [itex] M [/itex] with coefficients taken from the entries of [itex] x [/itex].

Writing the jth column of [itex] M_{*.j} [/itex]

[itex] M\ x = x_1 M_{*,1} + x_2 M_{*.2} + ... x_n M_{*,n} [/itex]

If we have more or fewer unknowns than equations, the matrix [itex] M [/itex] isn't square, so we can't do an analysis by taking its determinant. When [itex] M [/itex] is a square matrix and its derminant is non-zero, we can find a unique solution for variables [itex] x [/itex]. In particular , we can find a unique solution for the system [itex] M\ x = b [/itex] when [itex] b [/itex] is the column vector of zeroes. The unique solution to [itex] M\ x = 0 [/itex] would be [itex] x_j = 0 [/itex] for all [itex] j [/itex]..

If the column vectors of [itex] M [/itex] were dependent then solution for [itex] M\ x = 0 [/itex] would not be unique. For example if [itex] M_{*,1} = \sum_{j=2}^n a_j M_{*,j} [/itex] with at least one of the [itex]a_j [/itex] nonzero then the values [itex] x_1 = 1 [/itex] and [itex] x_j = -a_j [/itex] for [itex] j > 1 [/itex] would be a nonzero solution to [itex] M\ x = 0 [/itex].

By analogy, the Wronskian [itex] W [/itex] is the derminant of a square matrix of functions [itex] M [/itex] . A column vector of [itex] M [/itex] gives a function and it's successive derivatives. If [itex] W [/itex] is nonzero then [itex] M\ x = 0 [/itex] has the unique solution [itex] x= 0 [/itex] , so the column vectors of [itex] M [/itex] are independent.

That's just "by analogy". There would be lots of technicalities to consider if we want to prove anything about solutions to a differential equation. At least the analogy reminds us that a given column has entries all relate to the same function ( and a given row has entries that all relate to the same order of differentiation).
 
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Related to What is the connection between the Wronskian and linear independence?

What is the Wronskian?

The Wronskian is a mathematical tool used in determining the linear independence of a set of functions. It is also used in solving differential equations and testing for the existence of the general solution.

What is the importance of the Wronskian in methodology?

The Wronskian is important in methodology as it allows us to determine if a set of functions is linearly independent or not, which is crucial in solving differential equations and finding general solutions.

What is the formula for calculating the Wronskian?

The formula for calculating the Wronskian of a set of n functions is W(f1, f2, ..., fn) = det(A), where A is an n x n matrix with the functions as its entries.

What are the properties of the Wronskian?

The Wronskian has several important properties, including: it is always zero if the functions are linearly dependent, it is non-zero if the functions are linearly independent, and it is constant if the functions are solutions to a homogeneous linear differential equation.

How is the Wronskian used in solving differential equations?

The Wronskian is used in solving differential equations by determining if a set of functions is linearly independent, which allows us to find the general solution. It can also be used to test for the existence of the general solution and to find particular solutions using the method of variation of parameters.

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