Proving Non Singularity of Square Matrix is Necessary for Invertibility

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In summary, the provided answer did not use the definition of "invertible" in the proof, and also did not address the fact that invertible and nonsingular are often used interchangeably. Additionally, it is unclear whether the answer was given during an exam or as a review.
  • #1
johncena
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Q:Prove that a square matrix A is invertible iff A is non singular.
My Ans: Since the inverse of a square matrix is given by,
A^ = (1/|A|)adj.A (Where A^ is A inverse)
If |A|=0, A^ is not defined.
i.e, A^ exist only if A is non singular. In other words, a square matrix A is invertible iff A is non singular.
Conversly, Let |A|=0, i.e., let A be singular.
then, A^=(1/|A|)adj.A = (1/0)adj.A (not defined)
Hence we conclude that A^ exist only if A is non singular.

I got only 1 out of 5 marks for this answer. What is missing in my answer?
 
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  • #2
johncena said:
Q:Prove that a square matrix A is invertible iff A is non singular.
My Ans: Since the inverse of a square matrix is given by,
A^ = (1/|A|)adj.A (Where A^ is A inverse)
If |A|=0, A^ is not defined.
i.e, A^ exist only if A is non singular. In other words, a square matrix A is invertible iff A is non singular.
Conversly, Let |A|=0, i.e., let A be singular.
then, A^=(1/|A|)adj.A = (1/0)adj.A (not defined)
Hence we conclude that A^ exist only if A is non singular.

I got only 1 out of 5 marks for this answer. What is missing in my answer?

Let A be a square invertible matrix.
Then there exist a finite number of elementary operations on A that will transform A to I. That is, E1E2...EnA=I. Hence, there exists an inverse of A, namely E1E2...En. So A is nonsingular.
Thus, if A is invertible, then A is nonsingular.

Conversely, let A be nonsingular.
Then there exists an inverse of A.
Hence there exist a finite number of elementary operations on A such that A is transformed to I. That is A^-1 = E1E2...En and (A^-1)A=I. So A is invertible.
Thus, if A is nonsingular, then A is invertible.

Therefore, A is invertible iff A is nonsingular.
 
  • #3
Why my answer is incorrect?
 
  • #4
johncena said:
Why my answer is incorrect?

Strictly speaking, "invertible" means that a matrix can be transformed into the identity matrix by a finite series of elementary operations. Your proof did not use the definition.

One problem with constructing the proof is that invertible and nonsigular are often used interchangeably. But this is precisely because of the bi-implication.

Are you taking linear algebra this summer or are you rehashing an old exam?
 
  • #5


Your answer is technically correct, but it lacks explanation and elaboration. To improve your answer, you could provide more context and background information about the concepts of singularity and invertibility. Additionally, you could explain why the determinant (|A|) being equal to zero leads to the inverse not being defined. Lastly, you could provide an example to illustrate your point. Overall, adding more details and explanation would make your answer more comprehensive and earn you more marks.
 

1. Why is proving non-singularity important for matrix invertibility?

Proving non-singularity is important because it ensures that the matrix has a unique solution when it is inverted. A singular matrix has no inverse, meaning that it cannot be inverted and therefore does not have a unique solution.

2. What does it mean for a matrix to be singular?

A singular matrix is a square matrix that does not have an inverse. This means that it cannot be inverted and does not have a unique solution.

3. How do you prove that a square matrix is non-singular?

To prove that a square matrix is non-singular, you can use various methods such as row reduction, determinant calculation, or eigenvalue analysis. These methods will show that the matrix has a non-zero determinant, which is necessary for a matrix to be non-singular.

4. Can a non-square matrix be singular?

No, a non-square matrix cannot be singular. Singularity is a property that only applies to square matrices. Non-square matrices may have different properties such as being invertible or having a left or right inverse.

5. What are the consequences of using a singular matrix in calculations?

If a singular matrix is used in calculations, it can lead to inaccurate or undefined results. This is because a singular matrix does not have a unique solution, and therefore cannot be inverted to solve equations or perform other operations.

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