Are There Relationships Between the Column Vectors of a Matrix and Its Inverse?

In summary, there is no specific relationship between the column vectors of a matrix and the corresponding column vectors of its inverse. This can be observed by looking at simple examples and generalizing to cofactors, but it is difficult to prove the absence of any relationship without a specific definition of what that relationship would entail.
  • #1
srfriggen
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Are there any special relationships between the column vectors of a matrix and the corresponding column vectors of its inverse?
 
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  • #2
srfriggen said:
Are there any special relationships between the column vectors of a matrix and the corresponding column vectors of its inverse?

Hey sfriggen.

Are you talking about the most general non-singular matrix or a specific class of non-singular matrices?

For example rotation matrices have the property that the tranpose of the matrix is the inverse which means that the inverse matrix of a rotation matrix has the columns as the rows of the original.
 
  • #3
I'm asking for any invertible matrix.
 
  • #4
Why should there be any relationship?

Look at the simplest example. The inverse of ##\begin{bmatrix}a & b \\ c & d\end{bmatrix}## is ##1 / (ad - bc)\begin{bmatrix}\phantom{-}d & -b \\ -c & \phantom{-}a\end{bmatrix}##

There's no relatioship between the columns that I can see. There is a relationship between the ROWS of the inverse and the columns of the matrix, of course.
 
  • #5
Thanks AlephZero,

I wasn't implying there should be any relationship, just asking if there was one.

How could one generalize the 2x2 example you showed?
 
  • #6
You could write the inverse in terms of cofactors. That certainly shows each column depends on every element of the matrix in a rather complicated way.

But if you want to "prove" there is no relationship, the first problem is trying to define what you mean by "any possible sort of relationship". You can't prove something doesn't exist unless you can define it somehow.
 

FAQ: Are There Relationships Between the Column Vectors of a Matrix and Its Inverse?

What are column vectors and how are they related?

Column vectors are mathematical objects used to represent a list of numbers in a specific order. They are related to each other through their positions in a matrix, where each column represents a different vector. The order of the vectors in the matrix is important, as it determines their relationship to each other.

What is the importance of column vectors in linear algebra?

Column vectors play a crucial role in linear algebra as they are used to represent and manipulate systems of linear equations. They allow for the efficient and concise representation of data and are essential in solving problems involving vectors, matrices, and transformations.

How do you perform operations on column vectors?

Operations on column vectors are performed by manipulating the individual elements of the vectors. Addition and subtraction can be done by adding or subtracting the corresponding elements, while scalar multiplication involves multiplying each element by a constant. To perform matrix-vector multiplication, the elements of the vector are multiplied by the corresponding elements in each column of the matrix and then added together.

Can column vectors be visualized in 3D space?

Yes, column vectors can be visualized in 3D space as they represent a direction and magnitude in three-dimensional coordinate systems. Each element of the vector corresponds to one of the three axes (x, y, z), and the magnitude of the vector represents the distance and direction from the origin point.

How are column vectors used in applications?

Column vectors have numerous applications in various fields such as physics, engineering, computer graphics, and economics. They are used to represent physical quantities such as forces, velocities, and displacements, as well as to solve systems of linear equations and perform transformations in computer graphics. In economics, column vectors are used to represent supply and demand curves and to analyze the relationships between different variables.

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