Proving Null Spaces and Transformations

The correct proof would be:(a) Let x be an element of N(T), then T(x) = 0. By linearity, we have -T(x) = -0 = 0, so x is also an element of N(-T). Therefore, N(T) is a subset of N(-T).Conversely, let x be an element of N(-T), then -T(x) = 0. By linearity, we have T(x) = -0 = 0, so x is also an element of N(T). Therefore, N(-T) is a subset of N(T).Since N(T) is a subset of N(-T) and N(-T) is a subset
  • #1
redyelloworange
20
0

Homework Statement


Let T:V  W be a linear transformation. Prove the following results.

(a) N(T) = N(-T)
(b) N(T^k) = N((-T)^k)
(c) If V = W and t is an eigenvalue of T, then for any positive integer k
N((T-tI)^k) = N((tI-T)^k) where I is the identity transformation

The Attempt at a Solution


(a) for every x in V:
If T(x) = y, then –T(x) = -y
So then, T(0) = 0 = -T(0)
Is this right? On the right track?

I’m not sure how to approach the rest of them?

Thanks for your help!
 
Physics news on Phys.org
  • #2
a) is right. b) is done essentially the same way. If Tkx = y, then (-T)kx = ___? It should be pretty easy. c) follows immediately from b).
 
  • #3
AKG said:
a) is right.
Well, everything he said is right, but he hasn't proven what he set out to prove: that N(T) and N(-T) are equal sets.
 
  • #4
Sorry, my mistake. Hurkyl is correct, redyelloworange has not yet answered part a) fully.
 

Related to Proving Null Spaces and Transformations

What is a null space?

A null space, also known as a kernel, is the set of all vectors in a vector space that when multiplied by a transformation matrix result in the zero vector. In other words, it is the set of all vectors that are mapped to the origin by the transformation.

How do you find the null space of a matrix?

To find the null space of a matrix, you can use row reduction to put the matrix into reduced row echelon form. Then, the columns that do not contain pivot positions represent the basic variables for the null space. The remaining variables can be assigned any value and a vector can be created from these values to represent the null space.

What is the relationship between null spaces and linear transformations?

The null space of a matrix represents all of the vectors that are mapped to the zero vector by the linear transformation represented by that matrix. In other words, the null space is the set of all vectors that do not change direction or length when transformed by the matrix.

Can a null space be empty?

Yes, a null space can be empty. This means that there are no vectors that are mapped to the zero vector by the transformation represented by the matrix. This can occur if the matrix is invertible or if all of the vectors in the vector space are mapped to non-zero vectors by the transformation.

What is the significance of null spaces in linear algebra?

Null spaces are important in linear algebra because they help us to understand and analyze linear transformations. They can also be used to find solutions to systems of linear equations and to determine the rank and invertibility of a matrix.

Similar threads

  • Calculus and Beyond Homework Help
Replies
0
Views
462
  • Calculus and Beyond Homework Help
Replies
8
Views
646
  • Calculus and Beyond Homework Help
Replies
24
Views
826
  • Calculus and Beyond Homework Help
Replies
2
Views
310
  • Calculus and Beyond Homework Help
Replies
1
Views
470
  • Calculus and Beyond Homework Help
Replies
11
Views
1K
  • Calculus and Beyond Homework Help
Replies
1
Views
621
  • Calculus and Beyond Homework Help
Replies
3
Views
510
  • Calculus and Beyond Homework Help
2
Replies
43
Views
3K
  • Calculus and Beyond Homework Help
Replies
1
Views
248
Back
Top