Linear Algebra - Transformations

In summary, T is a transformation from the vector space of real 2x2 matrices back to that space, defined as T(X) = X - trans(X) (trans = transposed). The base for KerT is any base of the space of 2x2 symmetric matrices, with a dimension of 3. The base for ImT is the matrix [0 1; -1 0], with a dimension of 1. It can be shown that T can be diagonalized by proving that 0 is an eigenvalue with three linearly independent eigenvectors, and 2 is an eigenvalue for all vectors in the image. This is due to the fact that the space of antisymmetric matrices has a dimension
  • #1
daniel_i_l
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Homework Statement


T is a transformation from the vector space of real 2x2 matrices back to that space. T(X) = X - trans(X) (trans = transposed)
a)Find a base for KerT and ImT
b)Prove that T can be diagonalized.



Homework Equations





The Attempt at a Solution


a) If X is in KerT then X = trans(X) and so KerT is the space of all 2x2 symmetric matrices and its dimension is 3. It's base is any base of that space.
Since dimKerT = 3 , dimImT = 1 and since
[0 1]
[-1 0]
is in the image, it is a base of it.

b) obviously 0 is an eigenvalue with three linearly independant eigenvectors. It's easy to see that 2 is an eigenvalue for all the vectors in the image and so we have four linearly independent eigenvectors which means that T can be diagonalized.

Is that right? (b) seems a little shaky to me, is there any way i can say it better?
Thanks.
 
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  • #2
You can say (a) better by not referring to 'it's base', which is grammatically incorrect (you got the correct possesive earlier), and misleading since it implies it has a unique base.

(b) is fine, though you might want to mention that since 2 is a e-value, it has an e-vector, thus there is a basis of e-vectors hence the map is diagonalizable. You should also say why it is easy to see that 2 is an e-value, really, though it is clearly given by the space of antisymmetric spaces.
 

1. What is a transformation in linear algebra?

A transformation in linear algebra is a function that maps vectors from one vector space to another. It is represented by a matrix and can involve translation, rotation, scaling, or shearing of the vector.

2. What are the different types of transformations in linear algebra?

The different types of transformations in linear algebra include translation, rotation, scaling, reflection, shearing, and projection.

3. How do you represent a transformation in linear algebra?

A transformation is represented by a matrix, where each column represents the image of the corresponding basis vector in the original vector space. The transformation can then be applied to any vector by multiplying it with the transformation matrix.

4. What is the difference between a linear and non-linear transformation?

A linear transformation preserves the properties of linearity, such as scaling and addition, while a non-linear transformation does not. In other words, a linear transformation follows the rules of linear algebra, while a non-linear transformation does not.

5. How do you determine if a transformation is invertible?

A transformation is invertible if its corresponding matrix has an inverse. This means that there exists a transformation that can reverse the effect of the original transformation. In other words, if a transformation can be undone, it is invertible.

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