Linear Algebra: Linear Transformation Problem

In summary: If T(V) is a subset of T2, then T2(V) is also a subset of T(V). So, if T(V)\subsetn(T) then T2(V) \subset T(V). In summary, if T2=0, then T(V)\subsetn(T).
  • #1
Ertosthnes
49
0

Homework Statement


Let T[tex]\in[/tex]L(V,V). Prove that T[tex]^{2}[/tex]=0 iff T(V)[tex]\subset[/tex]n(T).

Homework Equations


dim T(V) + dim n(T) = dim V comes to mind.

The Attempt at a Solution


Honestly, I don't know where to start. I have no idea what I'm doing. My book and my professor are both utterly useless and I'm frustrated at how badly I am failing at this.
 
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  • #2
Ertosthnes said:

Homework Statement


Let T[tex]\in[/tex]L(V,V). Prove that T[tex]^{2}[/tex]=0 iff T(V)[tex]\subset[/tex]n(T).

Homework Equations


dim T(V) + dim n(T) = dim V comes to mind.

The Attempt at a Solution


Honestly, I don't know where to start. I have no idea what I'm doing. My book and my professor are both utterly useless and I'm frustrated at how badly I am failing at this.
Does your book have any definitions? For example does it give a definition of "n(T)"? You did not here, but I am going to assume that n(T) is the null space of T: the set of all vectors, v, such that T(v)= 0. One direction should be obvious. If T(v)= 0, then T2(v)= T(T(v))= T(0)= 0. Now the other way. Suppose that T2(v)= T((T(v))= 0. What does that tell you about the T(V)?
 
  • #3
Ah yes. n(T) is the null space of T.

Okay, suppose T[tex]^{2}[/tex](V) = T(T(V)) = 0:

Let another vector space W = T(V), so T(W) = 0. Then W [tex]\subset[/tex] n(T). Substituting we obtain T(V) [tex]\subset[/tex] n(T).

Does that work?
 
  • #4
Strictly speaking, either T(W)= {0} or T(v)=0 for all v in W. It might be better to say "if v is in T(V) then v= T(u) for some u in V. Then T(v)= T(T(u))= T2(u).

That proves "If T2= 0, then T(V)[itex]\subset[/itex]n(T). But you still need to prove "If T(V)[itex]\subset[/itex]n(T) then If T2= 0". Of course, that's pretty easy.
 

1. What is a linear transformation in linear algebra?

A linear transformation is a function that maps one vector space to another, while preserving the basic structure of the vector space. It is a fundamental concept in linear algebra and is used to study the properties and behavior of vector spaces.

2. How do you represent a linear transformation?

A linear transformation can be represented by a matrix, where each column of the matrix represents the image of the corresponding basis vector of the input vector space. Another way to represent a linear transformation is by using a set of equations, known as the transformation's standard form, which describes the output of the transformation in terms of the input coordinates.

3. What are the properties of a linear transformation?

The properties of a linear transformation include preserving addition and scalar multiplication, meaning that the transformation of a sum of vectors is equal to the sum of the individual transformations, and the transformation of a scalar multiple of a vector is equal to the same scalar multiple of the transformation of the vector. Additionally, a linear transformation maps the zero vector to the zero vector and preserves the identity element.

4. How do you determine if a matrix represents a linear transformation?

A matrix represents a linear transformation if it satisfies the properties of a linear transformation. This means that the columns of the matrix must be linearly independent and that the matrix must preserve addition and scalar multiplication. Additionally, for a matrix to represent a linear transformation, it must have the same number of columns as the dimension of the input vector space.

5. What are some applications of linear transformations?

Linear transformations have various applications in fields such as computer graphics, data compression, and machine learning. They are also used in solving systems of linear equations and in studying the geometry of vector spaces. Additionally, linear transformations are essential in understanding the behavior of linear systems and in solving problems in physics and engineering.

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