Linear - from a charpoly, determine if T is one to one, and nullity T

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In summary, the conversation discusses a linear operator T on a vector space V with a dimension of 4 and a characteristic polynomial of t^2(t-1)(t+7). It is determined that T is not one-to-one and the dimension of the null space of T is either 1 or 2, as determined by the characteristic polynomial. However, it is not possible to determine the exact dimension of the null space from the characteristic polynomial alone.
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bennyska
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Homework Statement


if T is a linear operator on V and dim V = 4 and charpoly(T)=t2(t-1)(t+7), then is T one-to-one? What is the dimension of the nullspace of T?


Homework Equations





The Attempt at a Solution


So i know T has 3 eigenvalues, 0, 1, -7. Since 0 is an eigenvalue, i know there's at least one vector v in V, v =! 0, such that T(v) = 0v = 0. so i know T is not one to one.
now i need to figure out the dimension of the null space. but i don't know anything about T, other than the charpoly splits. if i knew dim eigenspace corresponding to 0 = 2, then i would be able to construct a basis, and show that null space of T has dim 2. so, I'm a little lost.
 
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  • #2
I think all you can know from the characteristic polynomial having a factor of t^2 is that the null space of T has either dimension 1 or 2. [[0,0],[0,0]] has characteristic polynomial t^2 and has null space dimension 2. [[0,1],[0,0]] has characteristic polynomial t^2 and has null space dimension 1. No way to tell the difference from the characteristic polynomial.
 
  • #3
cool. that's kind of what i was thinking.
 

1. What is a charpoly and how is it related to linear transformations?

A charpoly, short for characteristic polynomial, is a polynomial that is associated with a linear transformation T. It is obtained by finding the determinant of the matrix A - λI, where A is the standard matrix of T and λ is a variable. The roots of the charpoly are important in determining the eigenvalues and eigenvectors of T.

2. How do you determine if a linear transformation T is one-to-one?

A linear transformation T is one-to-one if and only if the nullity of T is equal to 0. This means that the only solution to the equation T(x) = 0 is the trivial solution (x = 0). In other words, T maps distinct inputs to distinct outputs, and there are no "collisions" where multiple inputs are mapped to the same output.

3. What is the nullity of a linear transformation T?

The nullity of a linear transformation T is the dimension of the null space of T. In other words, it is the number of linearly independent vectors that are mapped to 0 by T. It is denoted by nullity(T) or dim(null(T)).

4. What does the nullity of T tell us about the rank of T?

The rank-nullity theorem states that the rank of a linear transformation T, denoted by rank(T) or dim(range(T)), is equal to the difference between the dimension of the domain and the nullity of T. In other words, rank(T) + nullity(T) = dim(domain(T)). So, knowing the nullity of T can help us determine the rank of T.

5. Can a linear transformation T be both one-to-one and onto?

Yes, a linear transformation T can be both one-to-one and onto, in which case it is said to be an isomorphism. This means that T maps distinct inputs to distinct outputs and also covers the entire range of the codomain. In this case, the nullity of T is 0 and the rank of T is equal to the dimension of the codomain.

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