Linear Algebra proof (nonsingular matrices)

In summary, the conversation discusses how to prove that if B is singular, then C must also be singular when C = AB. It is mentioned that this proof can be done using row equivalence or by contradiction. The concept of a matrix being singular and non-singular is also discussed, with the understanding that a non-singular matrix has only one solution to Bx = 0 while a singular matrix has infinitely many non-zero solutions. The use of determinants is also suggested as a possible approach to the proof. The conversation ends with a question about the various terms used to describe singular and non-singular matrices.
  • #1
seang
184
0
Let A and B be n x n matrices and let C = AB. Prove that if B is singular then C must be singular.

I have no idea how to prove this. I also don't understand how you can make such a claim without making some stipulations about A. I mean, if A were the 0 matrix, then C doesn't equal AB. And if A is singular, couldn't C also be singular? I was trying to prove this using row equivalence but I couldn't get there. Thanks
 
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  • #2
I mean, if A were the 0 matrix, then C doesn't equal AB.
What? C = AB by hypothesis, so if A = 0, then C = 0B = 0.
And if A is singular, couldn't C also be singular?
Yes, but that has nothing to do with anything.

Do you know what it means for a matrix to be singular?
 
  • #3
I think so. I think it means that it doesn't have an inverse. Doesn't it also mean that there is a 0 in the diagonal? I'm not good at writing proofs.
 
  • #4
seang said:
Let A and B be n x n matrices and let C = AB. Prove that if B is singular then C must be singular.

...in other words, if C=AB is invertible then B is invertible. that's how i would do it. if i had to do it exactly as stated i might use contradiction. suppose B is singular & AB is invertible, that is, [tex](AB)^{-1} = B^{-1}A^{-1}[/tex]. maybe it's easier that way. :confused:
 
  • #5
Singular means there's no inverse, correct. It doesn't mean there's a zero on the diagonal, and there are singular matrices with no zeroes on the diagonal.

If B is singular, what can you say about the solutions to Bx = 0?
 
  • #6
the only solution is 0
 
  • #7
If B is non-singular, what can you say abou the solutions to Bx = 0?
 
  • #8
its zero? I might see where this is going
 
  • #9
I don't mean to confuse you too much. If B is non-singular, then Bx = 0 has only one solution, x=0, so post 8 is correct. If B is singular, then Bx = 0 has infinitely many non-zero solutions, so post 7 is incorrect. In fact, B is singular iff Bx = 0 has infinitely many non-zero solutions. This means that B is non-singular iff Bx = 0 has only the zero-solution. Don't you have any theorems like these?
 
  • #10
Yes, I actually misread post 5, I thought you had wrote nonsingular. I know the theorems. This is just the first course where I have to write proofs since 7th grade, also, I'm not particularly good at math and am taking linear algebra for mostly applications. (I don't deny that studying the proofs and theory will be a strong foundations for the applications.)

So where do I start? a hint?
 
  • #11
You can also do this by looking at determinants:det(C)= det(AB)= det(A)det(B)
 
  • #12
is it just me or is the math department lame.
Why do we need so many contradicting words for the same thing
correct me if I am wrong
"non-singular"="One single trival solution"= "invertible"
"singular" = "many solutions" ="not invertible"
 

1. What is a nonsingular matrix in linear algebra?

A nonsingular matrix, also known as an invertible or nondegenerate matrix, is a square matrix that has a unique solution for its inverse. In other words, it is a matrix that can be inverted to obtain a unique solution for its variables.

2. How do you prove that a matrix is nonsingular?

One way to prove that a matrix is nonsingular is by showing that its determinant is nonzero. If the determinant of a square matrix is zero, then the matrix is singular and cannot be inverted. Therefore, a nonzero determinant is a necessary condition for a matrix to be nonsingular.

3. What is the purpose of studying nonsingular matrices in linear algebra?

Nonsingular matrices play a crucial role in many areas of mathematics and science, including solving systems of linear equations, calculating eigenvalues and eigenvectors, and finding the inverse of a matrix. They also have applications in computer science, economics, and physics.

4. Can a square matrix be nonsingular and singular at the same time?

No, a matrix cannot be both nonsingular and singular at the same time. A matrix is either nonsingular, where its determinant is nonzero, or singular, where its determinant is zero. There is no overlap between the two categories.

5. What are some common properties of nonsingular matrices?

Some common properties of nonsingular matrices include the existence of a unique solution for their inverse, the ability to perform row operations without changing the determinant, and the fact that their eigenvalues are all nonzero. Additionally, the product of two nonsingular matrices is also a nonsingular matrix.

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