Can Injectivity of a Matrix Guarantee a Left Inverse?

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In summary, X\in R^{s\times n}, A\in R^{n\times s}, and I\in R^{s\times s}. If rank(A)=s, there exists a solution X to the matrix equation XA=I. This can be proven by considering the linear map T with matrix A and finding a linear map S that maps R^{n} to R^{s} such that ST is an identity operator in R^{s}. The matrix of S can be written as X = V\hat{\Sigma}U^T, where A=U\Sigma V^T and \hat{\Sigma} has the reciprocals of the original on the diagonal. This can be further explored by
  • #1
y_lindsay
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We have [tex]X\in R^{s\times n}[/tex], [tex]A\in R^{n\times s}[/tex], [tex]I\in R^{s\times s}[/tex], where [tex]I[/tex] stands for the indentity matrix.
Now if we assume that [tex]rank(A)=s[/tex], can we conclude that there must exist a solution [tex]X[/tex] to matrix equation [tex]XA=I[/tex]?

For me the answer is obviously "yes" if we think this problem in the language of linear map instead of matrices.

Let [tex]T[/tex] be the linear map whose matrix is [tex]A[/tex] with respect to the standard basis. Then the above question is converted into if [tex]T[/tex] is injective, can we always find an [tex]S[/tex] maping [tex]R^{n}[/tex] to [tex]R^{s}[/tex], such that [tex]ST[/tex] is an identity operator in [tex]R^{s}[/tex]?

The linear map [tex]S[/tex] is defined as follows:
for any [tex]x\in range(T)[/tex], [tex]Sx[/tex] is the unique vector [tex]y\in R^{s}[/tex] such that [tex]Ty=x[/tex]. this is ensured because [tex]T[/tex] is injective.
for other [tex]x\in R^{n}[/tex], [tex]Sx=0[/tex].

Though knowing for sure how [tex]S[/tex] behaves, is there any way to write out the matrix of [tex]S[/tex] with respect to the standard basis?
i.e. what does the solution [tex]X[/tex] to matrix equation [tex]XA=I[/tex] look like?
 
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  • #2
Use singular value decomposition,

[tex]A=U\Sigma V^T \Longrightarrow X = V\hat{\Sigma}U^T[/tex]

where [tex]\hat{\Sigma}[/tex] has the reciprocals of the original on the diagonal. Note that there is a technical peculiarity but I guess you can figure it out. Search for left inverse (or pseudo-inverseor Moore-Penrose inverse). It is almost fun .
 
  • #3


Yes, we can write out the matrix of S in terms of the standard basis. Since T is injective and has rank s, it is also surjective and has a left inverse. Let's call this left inverse matrix L, which has dimensions s x n. Then the matrix of S with respect to the standard basis is given by S = L^{T}. This means that the solution X to the matrix equation XA=I will have the form X = S^{-1} = L^{T}. Therefore, we can conclude that there exists a solution X to the matrix equation as long as rank(A) = s.
 

FAQ: Can Injectivity of a Matrix Guarantee a Left Inverse?

What is a matrix equation?

A matrix equation is an equation in which at least one of the variables is a matrix. It is written in the form AX = B, where A and B are matrices and X is the unknown matrix that we are trying to solve for.

What is the identity matrix?

The identity matrix, denoted as I, is a square matrix with 1s on the main diagonal and 0s elsewhere. When multiplied with any matrix, it results in the same matrix. In other words, the identity matrix serves as the "identity" element for matrix multiplication, just like the number 1 is the identity element for multiplication of real numbers.

How do I solve a matrix equation?

To solve a matrix equation, we use various matrix operations such as multiplication, addition, and subtraction to manipulate the given equation and isolate the unknown matrix on one side. The resulting equation will be in the form of X = (matrix), which gives us the solution for the unknown matrix.

What is the purpose of solving matrix equations?

Solving matrix equations is useful in many areas of mathematics, physics, and engineering. It allows us to find unknown variables and solve complex systems of equations. Matrices are also used to represent data and perform calculations in computer graphics, statistics, and machine learning.

Can all matrix equations be solved?

No, not all matrix equations can be solved. Some equations may have no solution, while others may have infinite solutions. For a matrix equation to have a unique solution, the matrix on the left side (A) must be invertible, meaning it has an inverse matrix. If A is not invertible, the equation may have no solution or infinite solutions.

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