Is N(A) a Subset of N(A^t A)?: Proving Inclusion for Matrix Nullspaces

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In summary, the homework statement is trying to prove that N(A) is subset of N( A^t A). However, the homework statement was not able to prove this because Ax = 0 and A^t A x = 0, therefore x belongs to both N(A) and N(A^t A).
  • #1
inter060708
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Homework Statement



Given matrix A (size m x n), prove N(A) is subset of N( A^t A).

A^t is matrix A transposed.

Homework Equations





The Attempt at a Solution



My assumption is m < n, using definition of nullspace, I ended up with N( A^t A) = a set of zero vector, while N(A) is not entirely included in N( A^t A).

Thank You.
 
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  • #2
If ##Ax = 0##, then what is ##A^t A x##?
 
  • #3
jbunniii said:
If ##Ax = 0##, then what is ##A^t A x##?

A^t A x= 0

and how do I justify the subset part?
 
  • #4
inter060708 said:
A^t A x= 0

and how do I justify the subset part?
If ##X## and ##Y## are sets, how do you prove that ##X \subset Y## in general?
 
  • #5
jbunniii said:
If ##X## and ##Y## are sets, how do you prove that ##X \subset Y## in general?

I need to show that elements in X also belongs to Y.
 
  • #6
inter060708 said:
I need to show that elements in X also belongs to Y.
Yes, that's right. So what is the defining property of an element of ##N(A)##? In other words, ##x \in N(A)## if and only if ...?
 
  • #7
jbunniii said:
Yes, that's right. So what is the defining property of an element of ##N(A)##? In other words, ##x \in N(A)## if and only if ...?

x ε N(A) iff Ax = 0 and since A^t A x = 0 then x ε N(A^t A).
Therefore x belongs to both N(A) and N(A^t A).

Is this correct?
 
  • #8
inter060708 said:
x ε N(A) iff Ax = 0 and since A^t A x = 0 then x ε N(A^t A).
Therefore x belongs to both N(A) and N(A^t A).

Is this correct?
You have the right idea, but you need to state the logic correctly. The goal is to prove that if ##x \in N(A)## then ##x \in N(A^t A)##.

So, suppose ##x \in N(A)##. Then by definition, ##Ax = 0##. Therefore...?
 
  • #9
inter060708 said:
A^t A x= 0

Do you understand why that is zero? You stated it but didn't prove it.
 
  • #10
jbunniii said:
You have the right idea, but you need to state the logic correctly. The goal is to prove that if ##x \in N(A)## then ##x \in N(A^t A)##.

So, suppose ##x \in N(A)##. Then by definition, ##Ax = 0##. Therefore...?

Ok I think I got it.

to prove that if ##x \in N(A)## then ##x \in N(A^t A)##.

##x \in N(A)##. By definition, ##Ax = 0##
therefore ##A^t A x = 0## which means ##x \in N(A^t A)## as well.

Therefore ##N(A) \subset N(A^t A)##.

Thanks a lot jbunniii.
 
Last edited:
  • #11
Looks good!
 

1. What is the nullspace of a matrix?

The nullspace of a matrix is the set of all vectors that, when multiplied by the matrix, result in the zero vector. In other words, it is the set of all solutions to the equation Ax=0, where A is the given matrix.

2. How do you prove that a set is a subset of the nullspace?

To prove that a set is a subset of the nullspace, you must show that all vectors in the set satisfy the equation Ax=0. This can be done by plugging in the values of the vectors into the equation and showing that the resulting vector is equal to the zero vector.

3. Can a set be a subset of the nullspace if it contains non-zero vectors?

No, a set cannot be a subset of the nullspace if it contains non-zero vectors. The nullspace, by definition, only contains vectors that result in the zero vector when multiplied by the matrix. If a vector is non-zero, it cannot satisfy this condition and therefore cannot be in the nullspace.

4. Is the nullspace of a matrix always a subspace of the vector space it is contained in?

Yes, the nullspace of a matrix is always a subspace of the vector space it is contained in. This is because it satisfies the three properties of a subspace: closure under addition, closure under scalar multiplication, and contains the zero vector.

5. How can proving a subset of the nullspace be useful in scientific research?

Proving a subset of the nullspace can be useful in scientific research as it allows for the identification of linearly independent vectors that are solutions to the equation Ax=0. This can provide valuable insights into the structure and properties of the matrix, which can be used in various applications such as data analysis and image processing.

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