Suppose V is finite-dimensional, T:V V is a linear operator, and (T-21)(T-31)(T-41) = 0. Show (without...
Exercise 7.2.9 Let T:V → V be a linear transformation where V is finite dimensional. Show that exactly one of (i) and (ii) holds: (i) T(v) = 0 for some v + 0 in V; (ii) T(x) = v has a solution x in V for every v in V.
Let V and W be finite dimensional vector spaces and let T:V → W be a linear transformation. We say a linear transformation S :W → V is a left inverse of T if ST = Iy, where Iy denotes the identity transformation on V. We say a linear transformation S:W → V is a right inverse of T if TS = Iw, where Iw denotes the identity transformation on W. Finally, we say a linear transformation S:W → V...
for a linear operator T ∈ L(V), V is finite-dimensional. let C={r(T)(v): r(x) ∈ F[x], v non zero} show that C is an invariant of T for the subspace of V.
Let V, W, and U be three finite dimensional vector spaces over R and T:V + Wand S : W → U be two linear transformations. Show that null(SoT) < null(T) + null(S)
Let V be a finite-dimensional vector space and let T L(V) be an operator. In this problem you show that there is a nonzero polynomial such that p(T) = 0. (a) What is 0 in this context? A polynomial? A linear map? An element of V? (b) Define by . Prove that is a linear map. (c) Prove that if where V is infinite-dimensional and W is finite-dimensional, then S cannot be injective. (d) Use the preceding parts to prove...
Let A be an invertible linear operator on a finite-dimensional complex vector space V. Recall that we have shown in class that in this case, there exists a unique unitary operator U such that A=UA. The point of this exercise is to prove the following result: an invertible operator A is normal if and only if U|A= |AU. a) Show that if UA = |A|U, then AA* = A*A. Now, we want to show the other direction, i.e. if AA*...
Let V and W be finite dimensional vector spaces over R and T:V + W be linear. Let V be a subspace of V and Wo = T(V). (Select ALL that are TRUE) If T is surjective then Vo = {v EV : there is w E Wo such that T(v) = w} If T is injective then dim(VO) = dim(W). dim(ker(T) n Vo) = dim(VO) - dim(Wo).
Problem 4. Give an example of a linear operator T on a finite-dimensional vector space such that T is not nilpotent, but zero is the only eigenvalue of T. Characterize all such operators. Problem 5. Let A be an n × n matrix whose characteristic polynomial splits, γ be a cycle of generalized eigenvectors corresponding to an eigenvalue λ, and W be the subspace spanned by γ. Define γ′ to be the ordered set obtained from γ by reversing the...
Let V, W, and U be three finite dimensional vector spaces over R and T:V + Wand S : W → U be two linear transformations. Show that rank( ST) > rank(T) + rank(S) - dim(W)
de(V)e(A) 6· Lot V be a finite dimensional vector space, and T : V → V be a linear oper- ator. Suppose that T2-Iv, the identity operator. Prove that T is diagonalizable and that 1 and1 are the only possible eigenvalues of T