Proving the Invertibility of Non-Singular Matrices

In summary, a matrix is non-singular if and only if its determinant is non-zero. To prove this, it must be shown that the matrix has an inverse, which is defined as the adjoint divided by the determinant. Therefore, the determinant cannot equal zero in order for the matrix to be non-singular. Additionally, it must also be shown that if the determinant is non-zero, the matrix is invertible.
  • #1
newtomath
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a matrix is non singular only if its det does not equal zero. Calculate its inverse.

How do I go about proving this? I can only think of a counter example where matrix is singular given identical rows or columns or multiples of each other, which will generate a det of 0.

What do you think?
 
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  • #2
Prove what? That a matrix is non-singular if and only if its determinant is non-zero? What is your definition of "non-singular". I suspect, from that addtional "Calculate its inverse" that "non-singular" is defined as "has an inverse" (or, more precisely, that "singular" is defined as "does not have an inverse" and "non-singular" is the reverse of that. Okay, how would you find the inverse of a matrix? Does the determinant come into that?
 
  • #3
By non singular I mean a inverse exists. I believe the inverse is the adjoint/ det of the matrix. So the det can't be 0.
 
  • #4
That's half way. You also need to show that if the determinant is non-zero then the matrix is invertible. Since if the determinant is non-zero, 1/det exists, all you need to do is show that "adjoint" always exists.
 

FAQ: Proving the Invertibility of Non-Singular Matrices

What is a non-singular matrix?

A non-singular matrix is a square matrix that has a non-zero determinant, meaning that it is invertible and has a unique solution.

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

To prove that a matrix is non-singular, you can either calculate its determinant and show that it is non-zero, or you can use Gaussian elimination to reduce the matrix to row-echelon form and ensure that there are no rows of zeros.

What is the significance of a non-singular matrix?

A non-singular matrix is important because it represents a system of linear equations that has a unique solution. This means that the equations are not dependent on each other and can be solved accurately.

Can a non-singular matrix become singular?

No, a non-singular matrix cannot become singular. Once a matrix has a non-zero determinant, it will always have a non-zero determinant and be non-singular.

How is a non-singular matrix used in real-world applications?

Non-singular matrices are commonly used in engineering, physics, and other scientific fields to solve systems of equations and model real-world scenarios. They are also used in computer graphics and data analysis to manipulate and transform data.

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