Matrix corresponding to linear transformation is invertible iff it is onto?

Quora: In summary, A is a nxn matrix corresponding to a linear transformation. It is true that A is invertible if and only if it is onto, meaning that the image of A is the entire codomain of the transformation. This can also be shown by proving that A is onto if and only if the dimension of its image is n and the dimension of its kernel is 0, which is equivalent to A being a one-to-one transformation.
  • #1
Aziza
190
1
Let A be a nxn matrix corresponding to a linear transformation.
Is it true that A is invertible iff A is onto? (ie, the image of A is the entire codomain of the transformation)
In other words, is it sufficient to show that A is onto so as to show that A is invertible?
That was what my professor said but I am having trouble understanding this..could someone please prove this or direct me to a proof?
 
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  • #2
Aziza said:
Let A be a nxn matrix corresponding to a linear transformation.
Is it true that A is invertible iff A is onto? (ie, the image of A is the entire codomain of the transformation)

Yes

In other words, is it sufficient to show that A is onto so as to show that A is invertible?
That was what my professor said but I am having trouble understanding this..could someone please prove this or direct me to a proof?


$$A\,\,\text{is onto}\,\,\Longleftrightarrow \dim(Im A)=n\Longleftrightarrow \dim(\ker A)=0\Longleftrightarrow A\,\,\text{ is }\,\,1-1$$

DonAntonio
 

FAQ: Matrix corresponding to linear transformation is invertible iff it is onto?

What is a matrix corresponding to a linear transformation?

A matrix corresponding to a linear transformation is a square matrix that represents a linear transformation between two vector spaces. Each entry in the matrix represents the coefficient of a variable in the transformation equation.

What does it mean for a matrix to be invertible?

A matrix is invertible if it has an inverse matrix, which means that when multiplied together, they result in the identity matrix. This allows for the matrix to be "undone" or reversed in its transformation.

How is invertibility related to a matrix being onto?

A matrix is onto if the range of the transformation covers the entire codomain. This means that there exists a solution for every vector in the codomain. In order for a matrix to be invertible, it must also be onto, as every vector in the codomain must have a corresponding vector in the domain for the inverse to exist.

Is it possible for a matrix to be onto but not invertible?

No, if a matrix is onto, it must also be invertible. This is because an invertible matrix must have a unique solution for every vector in the codomain, and an onto matrix satisfies this condition.

Why is it important for a matrix to be onto and invertible in a linear transformation?

It is important for a matrix to be both onto and invertible in a linear transformation because it allows for the transformation to be "undone" or reversed, and also ensures that the transformation covers the entire codomain. This is crucial in many applications, such as solving systems of equations and finding the inverse of a function.

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